1. Field of the Invention
The present invention relates to an authentication method, an authentication device, and a recording medium.
2. Description of the Related Art
The recent years have witnessed the increasing pervasiveness of user-participation-type content generating systems on the Internet, such as electronic bulletin boards, weblogs, and Wikis. Many of these systems not only allow users to view information, but also to freely post information upon undergoing a simple user registration operation.
However, public nuisances are also increasing, which are made by taking advantage of such features. For example, a computer program called “bot” is used, which automatically interacts with the server to indiscriminately acquire a large number of accounts of such websites, and to post advertisements that are totally unrelated to the respective websites. Furthermore, the “bot” uses a charge-free e-mail address acquiring service to automatically and fraudulently acquire a large number of e-mail addresses. The acquired e-mail addresses are used for making various nuisances on the Internet, such as indiscriminately sending junk e-mails to a large indefinite number of addresses, or for making nuisances in the user-participation-type content generating systems.
In order to prevent such nuisances, there has been conceived a system for determining whether the user is actually a human being or the above-described “bot”, and allowing posting only when the user is determined to be a human being. This system is generally referred to as an anti-robot test. Information that can be identified by human beings, but not by currently-available computer programs (or difficult to be identified by computer programs), is displayed as a test. Only when this information is identified, the user is allowed to post information. Specifically, the program called “bot” analyzes messages exchanged in the form of character information between the clients and the server, and automatically generates a camouflaged message from the client. Therefore, in order for the client to send a message, the system requires a result indicating that information from the server other than character information, which can only be identified by an actual human being, has been identified.
A visual type anti-robot test is often used. Specifically, an image including rasterized characters and symbols is displayed, and the user is prompted to read the characters and symbols in the image, and to input the read results into an input form. This system is based on the fact that a human being can easily read characters in the image, whereas it is difficult for a computer program to read such characters. This system may also be based on the fact that the profit gained by making the above-described nuisances may not be worth the cost required for executing such a program.
However, with the advancement of the technology that enables a computer to recognize characters in images, such as OCR (Optical Character Recognition), the above-described defense against nuisances is becoming weaker year after year. In an attempt to prevent character recognition by OCR, a technology referred to as Captcha (registered trademark) has been developed, which uses image data with characters and symbols that are distorted or covered.
Patent Document 1: Japanese Laid-Open Patent Application No. 2005-322214
However, given the recent advancement in the technology that enables computers to recognize images, it is presumed that in the near future, there may be devised an easy and low-cost technology for deceiving and breaking through the system of the visual type anti-robot test described in patent document 1 and in “the description of the related art”. Accordingly, such a system may inevitably become weaker.
The present invention provides an authentication method, an authentication device, and a recording medium, in which one or more of the above-described disadvantages are eliminated.
A preferred embodiment of the present invention provides an authentication method, an authentication device, and a recording medium, which can reinforce security by making it difficult for a “bot”, which has a function of recognizing characters in an image to make a nuisance.
According to an aspect of the present invention, there is provided an authentication method performed by an authentication device to authenticate a user, the authentication method including an authentication-use image generating step of generating an authentication-use image including authentication-use information corresponding to an image expressing one or more characters and/or symbols which is provided on a background, wherein an edge formed by a difference in image density does not exist between the background and the image expressing the characters and/or the symbols; an authentication-use image presenting step of presenting, to the user, the authentication-use image generated at the authentication-use image generating step; and an authentication step of performing authentication by comparing character and/or symbol information input by the user based on the authentication-use image presented at the authentication-use image presenting step, with the characters and/or the symbols in the authentication-use image.
According to an aspect of the present invention, there is provided an authentication method performed by an authentication device to authenticate a user, the authentication method including an authentication-use video generating step of generating an authentication-use video including authentication-use information corresponding to an image expressing one or more characters and/or symbols constituted by a second texture which is provided on a background constituted by a first texture, wherein a positional relationship between the background and the authentication-use information changes with time; an authentication-use video presenting step of presenting, to the user, the authentication-use video generated at the authentication-use video generating step; and an authentication step of performing authentication by comparing character and/or symbol information input by the user based on the authentication-use video presented at the authentication-use video presenting step, with the characters and/or the symbols in the authentication-use video.
According to an aspect of the present invention, there is provided an authentication device for authenticating a user, the authentication device including an authentication-use image/video generating unit configured to generate any one of an authentication-use image including authentication-use information corresponding to an image expressing one or more characters and/or symbols which is provided on a background, wherein an edge formed by a difference in image density does not exist between the background and the image expressing the characters and/or the symbols, the authentication-use image wherein the background is constituted by a first texture and the authentication-use information corresponding to the image expressing the characters and/or the symbols is constituted by a second texture that is different from the first texture, the authentication-use image corresponding to a stereogram image in which the image expressing the characters and/or the symbols is embedded, the authentication-use image wherein in the image expressing the characters and/or the symbols, each of the characters and/or the symbols is constituted by plural characters and/or symbols, and an authentication-use video including the authentication-use information corresponding to the image expressing the characters and/or symbols constituted by the second texture which is provided on the background constituted by the first texture, wherein a positional relationship between the background and the authentication-use information changes with time; an authentication-use image/video presenting unit configured to present, to the user, the authentication-use image or the authentication-use video generated by the authentication-use image/video generating unit; and
an authentication unit configured to perform authentication by comparing character and/or symbol information input by the user based on the authentication-use image or the authentication-use video presented by the authentication-use image/video presenting unit, with the characters and/or the symbols in the authentication-use image or the authentication-use video.
According to one embodiment of the present invention, an authentication method, an authentication device, and a recording medium are provided, which can reinforce security by making it difficult for a “bot”, which has a function of recognizing characters in an image, to make a nuisance.
Other objects, features and advantages of the present invention will become more apparent from the following detailed description when read in conjunction with the accompanying drawings, in which:
A description is given, with reference to the accompanying drawings, of embodiments of the present invention. A visual anti-robot test system is taken as an example of the authentication system according to an embodiment of the present invention, although the present invention is not so limited. Furthermore, a server device which is a typical computer device is taken as an example of an authentication device according to an embodiment of the present invention, although the present invention is not so limited.
A description is given of a first embodiment of the present invention with reference to
(Authentication System)
The client device 100 and the authentication device 200 are typical computer devices including a CPU (Central Processing Unit), a RAM (Random Access Memory), and a ROM (Read Only Memory) (not shown).
With the above system configuration, the authentication system 1 can determine whether a user of the client device 100 is an actual human being or an automated computer program. Communications between the client device 100 and the server device 200 are performed by HTTP (HyperText Transfer Protocol) or HTTPS (HyperText Transfer Protocol Security) which is encrypted HTTP. The server device 200 sends information in the HTML (HyperText Markup Language) format to the client device 100, in response to a request from the client device 100.
The communication protocol used for the communication between the client device 100 and the server device 200 is not limited to HTTP or HTTPS.
(Functional Configuration)
First, a description is given of the functional units included in the client device 100.
The input unit 110 receives various instructions input by the user of the client device 100. An example is a service request for receiving services such as a Web service from the server device 200.
The display unit 120 displays a screen page on a display device such as a liquid crystal display device (not shown) of the client device 100. The communications unit 130 is an interface for performing communications with the server device 200. The control unit 140 implements various control operations for the client device 100, including those for the input unit 110, the display unit 120, and the communications unit 130.
Next, a description is given of the functional units of the server device 200.
The authentication unit 210 performs authentication based on information received from the client device 100. For example, the authentication unit 210 determines (authenticates) whether the user of the client device 100 is an actual human being or an automated computer program. Furthermore, the authentication unit 210 performs user authentication of the client device 100 based on a user name or a password received from the client device 100. These operations are described below with reference to
The authentication-use image generating unit 220 generates an authentication-use image (or an authentication-use video) according to an embodiment of the present invention. Examples of the authentication-use image (or authentication-use video) are described below with reference to
The communications unit 240 is an interface for performing communications with the client device 100. The service providing unit 250 provides services to the client device 100 in response to a service request received from the client device 100, in the event that the authentication is successful at the authentication unit 210. The control unit 260 implements various control operations for the server device 200, including those for the authentication unit 210, the authentication-use image generating unit (authentication-use video generating unit) 220, the authentication-use image presenting unit (authentication-use video presenting unit) 230, the communications unit 240, and the service providing unit 250.
(Operation Examples of Authentication System)
First, the client device 100 requests the server device 200 to perform authentication (step S1). In this example, the user sends a request from the client device 100 to the server device 200, to perform authentication. The request can be a service request for receiving a service.
In step S2, the server device 200 presents an authentication-use image (or an authentication-use video) to the client device 100 (step S2). The authentication-use image generating unit 220 generates an authentication-use image (or an authentication-use video) (for example, an image corresponding to characters and/or symbols as shown in
In step S3, the client device 100 sends test result information to the server device 200 (step S3). The user reads the characters and/or symbols in the authentication-use image presented at step S2, and inputs, with the input unit 110, information expressing the test result, i.e., the read characters and/or symbols. The test result information input with the input unit 110 is transmitted to the server device 200.
In step S4, the server device 200 determines whether the test result information received at step S3 is correct (step S4). The authentication unit 210 makes the determination (authentication) by comparing the test result information received at step S3 with the characters and/or the symbols in the authentication-use image presented at step S2, to determine whether they are the same. When it is determined that the information is correct (Yes in step S4), the process proceeds to step S5. When it is determined that the information is incorrect (No in step S4), the process returns to step S2.
In step S5, the server device 200 displays the screen page for authentication at the client device 100 (step S5). For example, the server device 200 presents a screen page for authenticating the user, which includes a user name (user identification character string) input form and a password input form, and prompts the user to input this information for user authentication.
In step S6, the client device 100 sends the user name and the password to the server device 200 (step S6). The user inputs, with the input unit 110, the user name and the password into the screen page for authentication presented at step S5. The information including the user name and the password input with the input unit 110 is transmitted to the server device 200.
In step S7, the server device 200 determines whether the user is an authorized user based on the information including the user name and the password received at step S6 (step S7). The authentication unit 210 makes the determination (authentication) by comparing the information including the user name and the password received at step S6 with user information managed in a storage unit (not shown).
When the user is determined to be an authorized user (Yes in step S7), the service providing unit 250 starts providing a service, such as displaying a content posting form, for example. When a service request has been received in step S1, the service providing unit 250 can start providing the service in accordance with the service request that has been received. When the user is determined to be an unauthorized user (No in step S7), the process returns to step S5.
By the above-described process, the server device 200 can perform the authentication operation of determining (authenticating) whether the user of the client device 100 is an actual human being.
The procedures of steps S2 through S4 and the procedures of steps S5 through S7 can be performed in the inverse order. Furthermore, when the request from the client device 100 to the server device 200 is to acquire an account from the server device 200, only the procedures of steps S11 through S14 shown in
(Authentication Operation Using Conventional Authentication-Use Image)
Next, a description is given of a conventional authentication operation (visual anti-robot test) with reference to
A human being can read the image shown in
However, such a learning process requires considerably complex technology, as well as being high cost. Therefore, it is very difficult for a low-cost computer program to indiscriminately recognize a large number of such characters/symbols.
In the above-described manner, a conventional authentication system (visual anti-robot test system) determines whether the client device 100 is an actual human being or an automated computer program. However, in view of recent advancements and price-reductions of the OCR technology, the above method may not be totally safe.
With reference to
(First Example of Authentication-Use Image)
With reference to
In the image shown in
In the example shown in
The images corresponding to the characters and/or symbols have a combination of plural characters and/or symbols that are arbitrarily selected. The selected characters and/or symbols can be different for each of the sessions (each of the operations shown in
A human being can read the image shown in
However, when the computer program uses a regular OCR program to acquire a first derivation of luminance, only the edges of each of the texture components are extracted as shown in
Therefore, in order for a “bot” to recognize the characters and/or symbols, in addition to the OCR, a complex image processing operation needs to be performed as a preprocess before the OCR. Such an image processing operation performed as the preprocess requires a large memory and a high-speed CPU, which inevitably leads to increased cost.
Accordingly, increased complexity in the technology for passing the authentication test using the first example of the authentication-use image leads to increased cost. Thus, in order to make a nuisance with the use of a “bot”, hardware of higher performance is required, or the frequency of nuisances per unit time needs to be decreased. Therefore, it will become more impractical to make a nuisance.
(Second Example of Authentication-Use Image)
With reference to
In the image shown in
In the example shown in
In this example, the difference between the first texture and the second texture is the form of the texture (in this example, the direction). Furthermore, the average density value (luminance) of the image corresponding to the characters and/or symbols is equal to or substantially equal to that of the background image.
The images corresponding to the characters and/or symbols are expressed by a combination of plural characters and/or symbols that are arbitrarily selected. The selected characters and/or symbols can be different for each of the sessions (each of the operations shown in
A human being can read the image shown in
However, it is difficult for a computer program to detect edges between characters and/or symbols and the background, based on the difference in the average density of the image corresponding to the characters and/or symbols, in addition to the reason described in the first example of the authentication-use image.
Therefore, in order for a “bot” to recognize the characters and/or symbols, it is necessary to perform, as the preprocess of regular OCR, a convolution operation for a secondary derivation filter, which requires a large memory and many calculations, inevitably leading to increased cost.
Accordingly, increased complexity in the technology for passing the authentication test using the second example of the authentication-use image leads to increased cost. Thus, in order to make a nuisance with the use of a “bot”, hardware of higher performance is required, or the frequency of nuisances per unit time needs to be decreased. Therefore, it will become more impractical to make a nuisance.
(Example of Authentication-Use Video)
With reference to
The images shown in
In the authentication-use image shown in
The foreground region of the authentication-use image is an image cut out from the image shown in
Accordingly, with the use of the authentication-use images thus generated, an authentication-use video can be generated, in which the positional relationship between the background region and the foreground region changes with time. In an example of the authentication-use video, the texture of the foreground region moves in a parallel manner in a predetermined direction with the passage of time as shown in
This example of the authentication-use video is constituted by an authentication-use image displayed by superposing the foreground region on the background region.
The authentication-use video shows random dots during a predetermined length of time. However, a human being can detect the edges by just perceiving the movement, even when there is no other visual information. Accordingly, when a human being observes this video for a certain length of time, the characters and/or symbols can be recognized.
However, in order for a “bot” to recognize the characters and/or symbols, it is necessary to calculate temporal derivations or differences from the video as the preprocess of regular OCR, which requires a large memory and a high-speed CPU, inevitably leading to increased cost.
Accordingly, increased complexity in the technology for passing the authentication test using this example of the authentication-use video leads to increased cost. Thus, in order to make a nuisance with the use of a “bot”, hardware of higher performance is required, or the frequency of nuisances per unit time needs to be decreased. Therefore, it will become more impractical to make a nuisance.
In this example of the authentication-use video, the texture of random dots which is to be cut out with the mask data shown in
Furthermore, in this example of the authentication-use video, the foreground region moves in a parallel manner in a predetermined direction with the passage of time while maintaining the positional relationships among the dots. However, the present invention is not so limited. The background region may move in a parallel manner in a predetermined direction with the passage of time while maintaining the positional relationships among the dots.
(Another Example of Authentication-Use Video)
With reference to
The images shown in
The foreground region of the authentication-use image is an image cut out from the image shown in
Accordingly, with the use of the authentication-use image thus generated, an authentication-use video can be generated, in which the positional relationship between the background region and the foreground region changes according to time. In an example of the authentication-use video, the textures of the foreground region and the background region move in a parallel manner in different directions with the passage of time as shown in
This example of the authentication-use video is constituted by an authentication-use image displayed by superposing the foreground region on the background region.
The authentication-use video shows random dots during a predetermined length of time. However, a human being can detect the edges only by perceiving the movement, even when there is no other visual information. Accordingly, when a human being observes this video for a certain length of time, the characters and/or symbols can be recognized.
Furthermore, unlike the previous example of the authentication-use video, both the texture of the foreground region and the texture of the background region move in different direction. This difference in the movement direction provides more indications for the human being to recognize the edges. Accordingly, it is even easier for the human being to recognize the characters and/or symbols.
However, even if a “bot” attempts to recognize the characters and/or symbols by calculating temporal derivations or differences from the image, the dot patterns are random, and therefore such calculation results only form random dot images. Accordingly, edges between the regions cannot be detected from temporal derivations or differences alone.
Thus, in order for a “bot” to recognize the characters and/or symbols, it is necessary to detect temporal corresponding points of the patterns and to also detect the movement direction, as the preprocess of regular OCR, which requires a large memory and a high-speed CPU, inevitably leading to increased cost.
Accordingly, increased complexity in the technology for passing the authentication test using this example of the authentication-use video leads to increased cost. Thus, in order to make a nuisance with the use of a “bot”, hardware of higher performance is required, or the frequency of nuisances per unit time needs to be decreased. Therefore, it will become more impractical to make a nuisance.
In this example of the authentication-use video, the texture of random dots which is to be cut out with the mask data shown in
(Third Example of Authentication-Use Image)
With reference to
The image shown in
The images corresponding to the characters and/or symbols are expressed by a combination of plural characters and/or symbols that are arbitrarily selected. The selected characters and/or symbols can be different for each of the sessions (each of the operations shown in
The user observes the images with both eyes by a paralleling method (observe the right image with the right eye and observe the left image with the left eye), or by a cross method (observe the left image with the right eye and observe the right image with the left eye), combines the two images, and observes the image by binocular stereopsis. Accordingly, in the example shown in
This technology utilizes the fact that the visual information processing system of a human being perceives the depth of vision, by detecting a binocular corresponding point of the two random dot stereogram images, and detecting a so-called binocular parallax, which is the parallax of the character regions of “A”, i.e. the regions of the characters and/or symbols disposed at different positions on the background region.
In such a random dot stereogram image having the above configuration, if only one of the images were provided, it would merely be an assembly of random dots, and it would be impossible to extract a region of the image corresponding to characters and/or symbols.
When the binocular parallax of the regions of the images corresponding to the characters and/or symbols is small, i.e., when the difference in the positions of the characters and/or symbols is small, if subtraction is merely performed between the two images, the regions of the characters and/or symbols may partially overlap each other as shown in
Accordingly, with this method, the edges of the image region corresponding to characters and/or symbols cannot be correctly extracted. If a “bot” were to attempt to recognize the characters and/or symbols, it would be necessary to perform operations such as detecting a binocular corresponding point among both images, as a preprocess of regular OCR. Such an operation requires a large memory and a high-speed CPU, which inevitably leads to increased cost.
Accordingly, increased complexity in the technology for passing the authentication test using the third example of the authentication-use image leads to increased cost. Thus, in order to make a nuisance with the use of a “bot”, hardware of higher performance is required, or the frequency of nuisances per unit time needs to be decreased. Therefore, it will become more impractical to make a nuisance.
In the third example of the authentication-use image, a random dot stereogram image requiring two images is described. However, the present invention is not so limited. For example, it is possible to use a single image random dot stereogram image with which binocular stereopsis can be performed with one image, or a stereogram image including a specific texture having meaning instead of random dots.
(Fourth Example of Authentication-Use Image)
With reference to
The image shown in
In the example shown in
The images corresponding to the characters and/or symbols are expressed by a combination of plural characters and/or symbols that are arbitrarily selected. The selected characters and/or symbols can be different for each of the sessions (each of the operations shown in
A human being can read the image shown in
However, when a computer program performs regular OCR to acquire a first derivation of luminance, only incomplete edges of characters and/or symbols and incomplete objects can be extracted, as shown in
Therefore, in order for a “bot” to recognize the characters and/or symbols, in addition to OCR, a more complex image processing operation needs to performed as the preprocess. Such an image processing operation performed as the preprocess requires a large memory and a high-speed CPU, which inevitably leads to increased cost.
Accordingly, increased complexity in the technology for passing the authentication test using the fourth example of the authentication-use image leads to increased cost. Thus, in order to make a nuisance with the use of a “bot”, hardware of higher performance is required, or the frequency of nuisances per unit time needs to be decreased. Therefore, it will become more impractical to make a nuisance.
(Fifth Example of Authentication-Use Image)
With reference to
The image shown in
The image shown in
In the example shown in
The images corresponding to the characters and/or symbols are expressed by a combination of plural characters and/or symbols that are arbitrarily selected. The selected characters and/or symbols can be different for each of the sessions (each of the operations shown in
A human being can read the image shown in
However, due to the reasons described in the third example of the authentication-use image, in order for a “bot” to recognize the characters and/or symbols, it is necessary to perform, as the preprocess of regular OCR, a convolution operation for a secondary derivation filter, which requires a large memory and many calculations, inevitably leading to increased cost.
Accordingly, increased complexity in the technology for passing the authentication test using the fifth example of the authentication-use image leads to increased cost. Thus, in order to make a nuisance with the use of a “bot”, hardware of higher performance is required, or the frequency of nuisances per unit time needs to be decreased. Therefore, it will become more impractical to make a nuisance.
(Sixth Example of Authentication-Use Image)
With reference to
The image shown in
The image shown in
In the example shown in
The images corresponding to the characters and/or symbols are expressed by a combination of plural characters and/or symbols that are arbitrarily selected. The selected characters and/or symbols can be different for each of the sessions (each of the operations shown in
A human being can read the image shown in
In addition to the reasons described in the third example of the authentication-use image, it is difficult to detect the edges between the images corresponding to the characters and/or symbols and the background, based on the difference in the average density between the images corresponding to the characters and/or symbols and the background.
Thus, in order for a “bot” to recognize the characters and/or symbols, it is necessary to perform, as the preprocess of regular OCR, a convolution operation for a secondary derivation filter, which requires a large memory and many calculations, inevitably leading to increased cost.
Accordingly, increased complexity in the technology for passing the authentication test using the sixth example of the authentication-use image leads to increased cost. Thus, in order to make a nuisance with the use of a “bot”, hardware of higher performance is required, or the frequency of nuisances per unit time needs to be decreased. Therefore, it will become more impractical to make a nuisance.
(Seventh Example of Authentication-Use Image)
With reference to
The image shown in
The image shown in
In the example shown in
The images corresponding to the characters and/or symbols are expressed by a combination of plural characters and/or symbols that are arbitrarily selected. The selected characters and/or symbols can be different for each of the sessions (each of the operations shown in
A human being can read the image shown in
However, due to the reasons described in the third example of the authentication-use image, in order for a “bot” to recognize the characters and/or symbols, it is necessary to perform, as the preprocess of regular OCR, a convolution operation for a secondary derivation filter, which requires a large memory and many calculations, inevitably leading to increased cost.
Accordingly, increased complexity in the technology for passing the authentication test using the seventh example of the authentication-use image leads to increased cost. Thus, in order to make a nuisance with the use of a “bot”, hardware of higher performance is required, or the frequency of nuisances per unit time needs to be decreased. Therefore, it will become more impractical to make a nuisance.
(Eighth Example of Authentication-Use Image)
With reference to
The image shown in
The image shown in
In the example shown in
In the example shown in
The images corresponding to the characters and/or symbols are expressed by a combination of plural characters and/or symbols that are arbitrarily selected. The selected characters and/or symbols can be different for each of the sessions (each of the operations shown in
A human being can read the image shown in
However, due to the reasons described in the third example of the authentication-use image, in order for a “bot” to recognize the characters and/or symbols, it is necessary to perform, as the preprocess of regular OCR, a convolution operation for a secondary derivation filter, which requires a large memory and many calculations, inevitably leading to increased cost.
Accordingly, increased complexity in the technology for passing the authentication test using the eighth example of the authentication-use image leads to increased cost. Thus, in order to make a nuisance with the use of a “bot”, hardware of higher performance is required, or the frequency of nuisances per unit time needs to be decreased. Therefore, it will become more impractical to make a nuisance.
(Ninth Example of Authentication-Use Image)
With reference to
The image shown in
The image shown in
The images corresponding to the dummy characters and/or dummy symbols are expressed by a combination of plural characters and/or symbols that are arbitrarily selected. The selected characters and/or symbols can be different for each of the sessions (each of the operations shown in
A human being can read the image shown in
However, due to the reasons described in the third example of the authentication-use image, in order for a “bot” to recognize the characters and/or symbols, it is necessary to perform, as the preprocess of regular OCR, a convolution operation for a secondary derivation filter, which requires a large memory and many calculations, inevitably leading to increased cost.
Accordingly, increased complexity in the technology for passing the authentication test using the ninth example of the authentication-use image leads to increased cost. Thus, in order to make a nuisance with the use of a “bot”, hardware of higher performance is required, or the frequency of nuisances per unit time needs to be decreased. Therefore, it will become more impractical to make a nuisance.
Even if a “bot” attempted to recognize this image with OCR, the “bot” would detect not only authentication-use information without an explicit outline with respect to the background, but also the dummy characters and/or symbols whose outlines can be detected relatively easily with respect to the background. Accordingly, the “bot” would give a clearly erroneous answer (in the example shown in
For example, the server device 200 can register, in an access prohibition list, the client device 100 which sends a clearly erroneous answer at step S3 of
(Tenth Example of Authentication-Use Image)
With reference to
The image shown in
In the text information shown in
The text information corresponding to the characters and/or symbols are expressed by a combination of plural characters and/or symbols that are arbitrarily selected. The selected characters and/or symbols can be different for each of the sessions (each of the operations shown in
A human being can read the text information shown in
When a human being observes such text information presented in this manner, a perceptual mechanism called grouping is used to simultaneously recognize each character/symbol element as well as each group of characters/symbols made by these elements, i.e., “ABCD” in this example.
However, it is considerably difficult for a “bot” to analyze text information presented in such a manner. The “bot” would first need to rasterize the text, and then to perform, as the preprocess of regular OCR, a convolution operation for a secondary derivation filter, which requires a large memory and many calculations, inevitably leading to increased cost.
Furthermore, in a case of a “bot” that can only perform processes with low precision, instead of recognizing the characters and/or symbols “ABCD” that are supposed to be identified, each of the elements “AOPQR” constituting such characters and/or symbols are recognized. Thus, it would be considerably easy for the server device 200 to identify whether the client device 100 is a “bot”.
The server device 200 can register, in an access prohibition list, the client device 100 which sends a clearly erroneous answer at step S3 of
The image shown in
The authentication-use image shown in
(Modification)
An embodiment of the present invention is described above. The above examples of authentication-use images (or authentication-use videos) have images corresponding to characters and/or symbols arranged on a background. There are no edges formed by differences in image density between the background and the images corresponding to characters and/or symbols.
Thus, even a human being may not be able to stably perceive the edges, and therefore erroneous recognitions may increase compared to the case of recognizing regular characters and/or symbols.
Accordingly, in the following modification of the embodiment of the present invention, the authentication-use image presented by the server device 200 does not include characters and/or symbols that may be confused with each other, such as the capital alphabetic letter “I”, the small alphabetic letter “1”, and the number “1”; or the small alphabetic letter “o”, the capital alphabetic letter “0”, and the number “0”; or the symbol “:” and the symbol “;”. Accordingly, erroneous recognitions by the human being can be decreased.
Furthermore, in the examples of the aforementioned authentication-use images, when an authentication operation (visual anti-robot test) is performed by the same method every time, the person attempting to make a nuisance may create a “bot” that is dedicated to the particular authentication operation, in order to pass the test. Particularly, if the website has a considerably large number of accesses per day, the cost of creating such a “bot” may be decreased to an acceptable amount.
In a modification of the first embodiment of the present invention, there is provided a procedure (step) of randomly selecting one of the examples of the authentication-use images to be presented by the server device 200 for each of the sessions (each of the operations shown in
In a modification of the first embodiment of the present invention, there is provided a procedure (step) of presenting the examples of the authentication-use images to be presented by the server device 200 in each of the sessions (each of the operations shown in
A description is given of a second embodiment of the present invention with reference to
The system configuration, functional configuration, and operations of an authentication system according to the second embodiment are the same as those of the first embodiment (see
The authentication-use image presenting unit 230 (authentication-use video presenting unit) according to the first embodiment presents authentication-use images (authentication-use videos) generated by the authentication-use image generating unit 220. In the second embodiment, in addition to the authentication-use image (authentication-use video), a selection screen page is presented, including list boxes and tick boxes for prompting the user to make a selection in accordance with the presented authentication-use image, as shown in
(First Example of Presentation Screen Page of Authentication-Use Video)
With reference to
The image shown in
The screen page display contents shown in
Examples of the authentication-use video presented in the authentication-use video section 11 are described below with reference to
Examples of the authentication-use video presented by the authentication-use video section 11 are described below.
(First Example of Authentication-Use Video)
In
The series of images are continuously presented as a video, in an order starting from the left image in the top row to the right image in the top row, and then from the left image in the bottom row to the right image in the bottom row, as viewed in
This is considered as attributable to a perception mechanism that is acquired for quickly recognizing another moving human being or another moving creature.
However, it is considerably difficult for a computer program to determine the biological motion video shown in
Accordingly, increased complexity in the technology for passing the authentication test using the above example of the authentication-use video leads to increased cost. Thus, in order to make a nuisance with the use of a “bot”, hardware of higher performance is required, or the frequency of nuisances per unit time needs to be decreased. Therefore, it will become more impractical to make a nuisance.
In this example of an authentication-use video, the human observing the dots perceives them as a walking or jumping human being by biological motion perception. Instead, the video may show other movements such as throwing an object or kicking an object, which are perceived by biological motion perception.
As described above, the authentication system according to the present embodiment determines whether the user is a human being by using a video with which the human observer can perceive a biological motion from a group of dots moving on a background.
Accordingly, it possible to make it even more difficult to make a nuisance with the use of a computer program that automatically exchanges information with a server by a service on a computer network.
(Second Example of Authentication-Use Video)
(Second Example of Presentation Screen Page of Authentication-Use Video)
A description is given of a second example of a screen page presenting an authentication-use video according to the second embodiment with reference to
The screen page display contents shown in
Examples of the authentication-use videos presented in the authentication-use video sections 4, 5, and 6 are described below with reference to
The tick boxes 7 are appended in correspondence with the videos. At the client device 100, the user ticks the tick boxes provided under all of the videos which are perceived as walking human beings. Furthermore, by pressing the send button 8, the selected test result is sent to the server device 200 by a POST method of HTTP, for example. The server device 200 performs authentication by determining whether the test result is correct upon comparing the received test result with the contents of the presented authentication-use video.
However, it is considerably difficult for a computer program to determine the type of movement by biological motion perception. Even if a computer algorithm that can make such a determination were developed and implemented as a program, it would be require considerably complex processes such as grouping and identifying the moving dots. Furthermore, such processes would require a large memory and a high-speed CPU, which inevitably leads to increased cost.
Accordingly, increased complexity in the technology for passing the authentication test using the above example of the authentication-use video leads to increased cost. Thus, in order to make a nuisance with the use of a “bot”, hardware of higher performance is required, or the frequency of nuisances per unit time needs to be decreased. Therefore, it will become more impractical to make a nuisance.
In this example of an authentication-use video, three types of videos are presented. However, the number of presented videos is not particularly limited to three videos as long as plural videos are presented. It is better to have as many videos presented as possible. However, the number of videos is in a tradeoff relationship with the time required for presentation. Therefore, the number of videos is to be determined in consideration of the importance, the degree of risk, and the operability of the authentication system.
(Third Example of Authentication-Use Video)
In
The series of images are continuously presented as a video, in an order starting from the left image in the top row to the right image in the top row, and then from the left image in the bottom row to the right image in the bottom row, as viewed in
The images in the video can be perceived by biological motion perception. The videos divided in time series shown in
As described above, the biological motion perception functions not only for moving human beings but also for animals. As described above, the biological motion perception is considered as attributable to a perception mechanism that is acquired for quickly recognizing another moving human being or another moving creature.
In the screen page shown in
As described above, the authentication system 1 according to the second embodiment uses a video including a group of dots moving on a background, with which the human observer can perceive a biological motion, to make the user distinguish the type of perceived creature (or movement).
Accordingly, it possible to make it even more difficult to make a nuisance with the use of a computer program that automatically exchanges information with a server by a service on a computer network.
(Fourth Example of Authentication-Use Video)
In
In the screen page shown in
(Modification of Authentication-Use Video Presented by Authentication-Use Video Section)
Examples of the authentication-use video are described above with reference to
Each of the above-described authentication-use videos (or each of the authentication-use images constituting the authentication-use videos) may have only two colors, i.e., a color of the background and a color of the group of dots. With such a configuration, the videos can be compressed by a LZW compression method used in GIF animation, for example.
In the authentication-use video, the area ratio of the group of dots is considerably small with respect to the background, and therefore the compression process can be performed at high speed and with a considerably high compression ratio. This is because with the LZW compression method used in GIF animation, as the same color is continuously used, the compression ratio of the image becomes high.
The modification of the authentication-use video is characterized in that only two colors are used, i.e., the color of the background and the color of the group of dots.
Accordingly, it possible to make it even more difficult to make a nuisance with the use of a computer program that automatically exchanges information with a server by a service on a computer network, and to also reduce the amount of the data being used.
A description is given of a third embodiment of the present invention with reference to
The system configuration and the functional configuration of an authentication system according to the third embodiment are the same as those of the first embodiment (see
The above-described authentication-use image presenting unit (authentication-use video presenting unit) 230 according to the first embodiment presents authentication-use images (authentication-use videos) generated by the authentication-use image generating unit 220. In the third embodiment, in addition to the authentication-use image (authentication-use video), an answer screen page is presented, including answer boxes for prompting the user to provide answers in accordance with the presented authentication-use images, as shown in
(Example of Presentation Screen Page of Authentication-Use Image)
With reference to
The image shown in
The screen page display contents shown in
The authentication-use image presented in the authentication-use image section 101 is one photograph or image randomly selected from a group of plural known images (hereinafter, “image group 1”) associated with information corresponding to objects (e.g., a man, a vehicle, a building) or scenes with meanings (e.g., a suburban area, winter) (hereinafter, the information associated with the authentication-use image is referred to as “tag information” or simply a “tag”). Meanwhile, the authentication-use image presented in the authentication-use image section 102 is one photograph or image randomly selected from a group of plural unknown images (hereinafter, “image group 2”) associated with unknown tag information of the authentication-use image.
At the screen page shown in
(Example of Operation of Authentication System)
First, the client device 100 requests the server device 200 to perform authentication (step S21). In this example, the user sends a request from the client device 100 to the server device 200, to perform authentication. The request can be a service request for receiving a service.
In step S22, the server device 200 presents authentication-use images (or authentication-use videos) to the client device 100 (step S22). The authentication-use image generating unit 220 generates authentication-use images (or authentication-use videos) (for example, an image belonging to image group 1 and an image belonging to image group 2, which are respectively presented in the authentication-use image sections 101 and 102 shown in
In step S23, the client device 100 sends the answer information to the server device 200 (step S23). The user inputs, into the input unit 110, tag information that is considered appropriate for the authentication-use image presented at step S22. The answer information input to the input unit 110 is transmitted to the server device 200.
In step S24, the server device 200 calculates the percentage of correct answers based on the answer information received at step S23 (step S24). The authentication unit 210 calculates the percentage of correct answers based on how many tag information items in the received answer information correspond to the tag information items associated beforehand with the authentication-use images presented in the authentication-use image section 101.
In step S25, the server device 200 determines whether the percentage of correct answers calculated at step S24 is greater than or equal to a predetermined threshold (step S25). When it is determined to be greater than or equal to the predetermined threshold (Yes in step S25), the process proceeds to step S26. When it is determined to be less than the predetermined threshold (No in step S25), the process returns to step S22. The threshold may be set at, for example, 40% through 50%, as long as the precision of recognition exceeds that of the most advanced image recognition technology that is currently available (for example, 20% through 30%).
In step S26, the server device 200 presents the screen page for authentication to the client device 100 (step S26). At this step, a screen page for authentication is presented for authenticating the user, including a user name (user identification character string) input form and a password input form, and the user is prompted to input these items for user authentication.
In step S27, the client device 100 sends the user name and the password to the server device 200 (step S27). The user inputs, with the input unit 110, the user name and the password into the screen page for authentication presented at step S26. The information including the user name and the password input with the input unit 110 is transmitted to the server device 200.
In step S28, the server device 200 determines whether the user is an authorized user based on the information including the user name and the password received at step S27 (step S28). The authentication unit 210 makes the determination (authentication) by comparing the information including the user name and the password received at step S27 with user information managed in a storage unit (not shown).
When the user is determined to be an authorized user (Yes in step S28), the service providing unit 250 starts providing a service, such as displaying a content posting form, for example. When a service request had been received in step S21, the service providing unit 250 can start providing the service in accordance with the service request that had been received. When the user is determined to be an unauthorized user (No in step S28), the process returns to step S26.
By the above-described process, the server device 200 can perform the authentication operation of determining (authenticating) whether the user of the client device 100 is an actual human being.
The procedures of steps S22 through S25 and the procedures of steps S26 through S28 can be performed in the inverse order. Furthermore, when the request from the client device 100 to the server device 200 is to acquire an account from the server device 200, only the procedures of steps S31 through S35 shown in
In the above examples of operations, one photograph or image is randomly selected, as the authentication-use image, from each of image group 1 including plural known tag information items and image group 2 including unknown tag information items, and the selected photographs/images are presented. However, an arbitrary plural number of images (more than one) can be selected from each of the image groups, and the plural selected images can be presented.
As described above, in the authentication system according to this operation example, at least two images are presented within the same screen page, and the user is prompted to provide answers corresponding to the objects included in the images or the meanings of the images, to determine whether the user is a human being. At least one photograph or image is randomly selected, as the authentication-use image, from each of image group 1 including plural known words corresponding to names of objects in images or words expressing meanings of scenes in images, and image group 2 including unknown words corresponding to names of objects in images or words expressing meanings of scenes in images, and the selected photographs/images are presented. The determination for authentication is made based on the percentage of correct answers given by the user with respect to the image group including plural known words corresponding to names of objects or scenes.
With such a feature, it possible to make it even more difficult to make a nuisance with the use of a computer program that automatically exchanges information with a server by a service on a computer network.
(Modification 1 of Operation Example of Authentication System)
When the user is determined to be an authorized user in step S48 (Yes in step S48), the process proceeds to step S49, where the server device 200 classifies the images belonging to image group 2 presented in the authentication-use image section 102, into image group 1 (step S49). This is because when the input user name and password are those of an authorized user, it can be determined that the answer information for the images presented in the authentication-use image section 102 may be somewhat credible. Accordingly, the corresponding answer information is associated with the images of image group 2 as tag information, and these images are classified into image group 1. The service providing unit 250 starts providing a service to the user.
With such a configuration, it possible to make it even more difficult to make a nuisance with the use of a computer program that automatically exchanges information with a server by a service on a computer network. Furthermore, the number of data items in the image database can be sequentially increased, and therefore the image database required in a system for recognizing contents of a photograph/image can be easily established.
As described above, in the authentication system according to this operation example, when the user is determined to be a human being, the answer information given by the user for a presented image selected from image group 2, is used as tag information of the corresponding image, and the corresponding image is classified into image group 1.
With such a feature, it possible to make it even more difficult to make a nuisance with the use of a computer program that automatically exchanges information with a server by a service on a computer network, and also to make it easy to establish the image database required in a system for recognizing contents of a photograph/image.
(Modification 2 of Operation Example of Authentication System)
While performing the procedure of step S59, the process proceeds to step S60, where the answer information for the image presented in the authentication-use image section 101 is associated with the same image by the server device 200 as tag information (step S60). When the input user name and password are those of an authorized user, it can be determined that the answer information for the image presented in the authentication-use image section 101, which had not been associated beforehand with the corresponding image as tag information, may be somewhat credible. Accordingly, the answer information is associated with the corresponding image as new tag information.
With such a configuration, the following problem can be solved. That is, even if the user does not have any malicious intent, a word provided for an image by the user observing the image may vary somewhat according to the subjective perception of the user. This may cause erroneous determinations, in which a human user is determined as not being a human being. Such erroneous determinations can be reduced with this configuration.
As described above, in the authentication system according to this operation example, when the user is determined to be a human being, among the answer information items given by the user for presented images selected from image group 1, an answer information item that had not been known before the test is added as new tag information of the corresponding image.
With such a feature, it is possible to improve the precision in determining whether the user is a human being.
(Modification 3 of Operation Example of Authentication System)
When the procedure of step S70 is finished, the process proceeds to step S71, where the server device 200 calculates the answer ratio for all tag information items appended to the images presented in the authentication-use image section 101 (step S71). The answer ratio is obtained by dividing “the number of times the corresponding tag information item has been included in the answer information for the particular image” by “the number times the particular image has been used for the test”.
In step S72, the server device 200 selects a new correct word (step S72). In this case, when the answer ratio calculated at step S71 exceeds a predetermined threshold such as 50%, the specific tag information item is determined to be the new correct word which is used for calculating the percentage of correct answers for the particular image, starting with the next test.
With such a configuration, the following problem can be solved. That is, even if the user does not have any malicious intent, a word provided for an image by the user observing the image may vary somewhat according to the subjective perception of the user. This may cause erroneous determinations, in which a human user is determined as not being a human being. However, with this configuration, the correct word can be selected based on a larger number of determinations, so that such erroneous determinations can be reduced.
As described above, the authentication system according to this operation example calculates, for each test, the answer ratio of a tag information item given for each image belonging to image group 1 by a user that has been determined to be a human being. Based on the calculated answer ratio, a new correct word is selected for calculating the percentage of correct answers for the particular image, starting with the next test.
With such a feature, it is possible to improve the precision in determining whether the user is a human being.
(Authentication System)
The data pertaining to the authentication-use image managed in the database 22 has a structure including elements such as those shown in
By the above system configuration, in the authentication system 1, when a new request for authentication is made by the user, a request is sent to the DBMS 21 for images belonging to image group 1 and images belonging to image group 2 (instruction for selecting images) with a language such as SQL used for making a request to databases.
The DBMS 21 that received the instruction for selecting images randomly selects one image ID from among the image IDs belonging to image group 1 and randomly selects one image ID from among the image IDs belonging to image group 2, with the use of image classification-use data shown in
When the user is determined to be a human being, and the user name and password corresponds to those of an authorized user, the authentication system 1 determines that the answer information given for images presented in the authentication-use image section 102 is somewhat credible. Therefore, the authentication system 1 sends, to the DBMS 21, a request for moving the corresponding image to image group 1, and a request for registering the answer information as tag information in association with the image. Then, the DBMS 21 overwrites the image classification-use data (delete the image from image group 2 and add the image to image group 1), adds the tag information given as an answer for the image to the image data of the image, sets “1” as the number of times that this image has been used for authentication, sets “1” as the number of times that the tag information has been given as the answer, and sets “100%” as the answer ratio (see modification 1 of operation example).
Furthermore, among the answer information items for the images presented in the authentication-use image section 101, the answer information item that had not been associated beforehand with the image can be determined as being somewhat credible. Therefore, the authentication system 1 sends a request to the DBMS 21 for registering all of the tag information items given as answers for the image in association with the image. Then, the DBMS 21 adds “1” to the number of times that the image has been used. Furthermore, among the answer information items given for the image in the authentication operation, the DBMS 21 adds “1” to the number of times that each tag information item known before the test has been given as the answer, adds the tag information not known before the test as new tag information to the image data of the image, and sets “1” as the number of times that each of the new tag information items has been given as the answer. Then, the answer ratio is calculated once again for all of the tags that are registered at this time point, and the obtained answer ratios are saved in the image data (see modification 2 and 3 of the operation example).
The communications between the user and a WEB service 31 are performed with HTTP or HTTPS. The user first accesses the authentication starting page to make a request to a WEB server 44 for authentication by the GET method. Then, in the WEB application 41, the authentication system 42 makes a request to the DBMS 21 for images belonging to image group 1 and images belonging to image group 2, with a language such as SQL used for making requests to the database 22. With the use of image classification-use data, the DBMS 21 randomly selects one image ID from the image IDs belonging to image group 1, and randomly selects one image ID from the image IDs belonging to image group 2. Then, the DBMS 21 searches the image data in the database 22 for the images corresponding to all of the selected IDs, extracts the images found as a result of the search, and returns the search results to the authentication system 42 together with tag information.
Then, the WEB application 41 displays a screen page presenting authentication-use images on the WEB browser of the user, as shown in
When the user is determined to be a human being, the authentication system 1 displays a screen page as shown in
With such a configuration, in the image database 23 and the WEB service 31 using the image database 23, tag information can be automatically appended to images that do not have tag information appended while the operation is being performed. Moreover, tag information that is given by a large number of users is selected as the appropriate tag information. Therefore, without the need for a large amount of image data with tag information appended, it can be determined as to whether a user is a human being with high precision, and searching operations can be performed with improved precision.
In this manner, the image database system 23 and the WEB service 31 that uses the image database system 23 can be provided, with which it is determined whether a user is a human being, and only a user who has been determined as a human is allowed to add images or edit data.
With such a feature, in the image database and the service using the image database, it can be determined as to whether a user is a human being with high precision, and searching operations can be performed with improved precision, without the need for a large amount of image data appended with tag information.
Furthermore, the image database system 23 and the WEB service 31 that uses the image database system 23 can be provided, with which the displaying order of the search results are changed according to the answer ratio, when tag information associated with an image is used as the search term to search for the image.
With such a feature, in the image database and the image sharing service, it can be determined as to whether a user is a human being with high precision, and searching operations can be performed with improved precision, without the need for a large amount of data.
A supplemental description is given of the advantages of the authentication system according to the third embodiment, in comparison with the conventional technology.
In a system using the conventional photograph/image content recognition technology, as the frequency of using the same photograph increases, it becomes easier to estimate the relationship between the image and the word appended to the image. Accordingly, the frequency of each image appearing in a test needs to be reduced. For this reason, it is necessary to have a large number of images having words appended expressing objects in the images or meanings of scenes in the images. It is considerably difficult to establish such an image database. Thus, it is becoming considerably difficult to actually implement a visual anti-robot test system using photographs/images.
However, the authentication system according to the third embodiment makes it easy to establish an image database required for such a system.
Furthermore, in recent years and continuing, image sharing services or stock photograph services on websites are gaining popularity, in which a user posts an image, which is shared among other users, so that other users are allowed to use the image in their blogs or documents at a charge or at no charge. In such a service, a word naming an object in the image or giving the meaning of a scene in the image is appended to the image beforehand as tag information by the poster of the image (person who posted the image). Therefore, the image can be searched for with the use of the tag information. However, in such a WEB service, the tag that is appended to the image beforehand depends on the subjective perception of the person who appended the tag. Therefore, it is considerably difficult to search for the desired photograph from a large number of images.
However, the authentication system according to the third embodiment makes it possible to improve the quality of such tag information and improve the precision in performing the searching operations.
The CPU 10 is an arithmetic unit for controlling operations of the entire device. The RAM 20 is a volatile storage medium for writing/reading information at high-speed, which is used as a work area when the CPU 10 processes information. The ROM 30 is a read-only non-volatile recording medium, storing programs such as firmware. The HDD 40 is a non-volatile storage medium for writing/reading information at high-speed, which stores an OS (Operating System) and various control programs and application programs.
The I/F 50 is for connecting various hardware components and networks to the bus 80, and controlling the connection. The LCD 60 is a visual user interface used by the user to confirm the state of the PC. The operations unit 70 is a user interface such as a keyboard and a mouse, used by the user to input information to the device.
In such a hardware configuration, a program stored in the ROM 30, the HDD 40, or a storage medium such as an optical disk (not shown) is read out into the RAM 20. The program is operated according to control by the CPU 10, thereby configuring a software control unit. With the combination of such a software control unit and the hardware, there are provided functional blocks for implementing functions of the client device 100 and the server device 200 according to the fourth embodiment. As for the server device 200, user interfaces such as the LCD 60 and the operations unit 70 can be omitted.
(Functional Configuration)
First, a description is given of the function units included in the client device 100. The input unit 110 receives various instructions input by the user of the client device 100. The input unit 110 is realized by the operations unit 70 shown in
The display unit 120 is for displaying the operational status of the client device 100, and is realized by the I/F 50 and the LCD 60 shown in
Next, a description is given of the respective function units of the server device 200. The authentication unit 210 performs authentication based on information received from the client device 100. For example, the authentication unit 210 determines (authenticates) whether the user of the client device 100 is an actual human being or an automated computer program. Furthermore, the authentication unit 210 performs user authentication of the client device 100 based on a user name or a password received from the client device 100. These operations are described below with reference to
The authentication-use image generating unit 220 generates an authentication-use image according to an embodiment of the present invention. Examples of the authentication-use image are described below. The authentication-use image generating unit 220, implemented as a program loaded in the RAM 20 shown in
The communications unit 240 is an interface for performing communications with the client device 100. The communications unit 240 is realized by the I/F 50 shown in
(Operational Examples of Authentication System)
First, the client device 100 requests the server device 200 to perform authentication (S81). In this example, the user sends a request from the client device 100 to the server device 200, to perform authentication. The request can be a service request for receiving a service.
In step S82, the server device 200 presents an authentication-use image to the client device 100 for the visual anti-robot test (step S82). The authentication-use image generating unit 220 generates an authentication-use image. Next, the authentication-use image presenting unit 230 presents the authentication-use image generated by the authentication-use image generating unit 220 to the client device 100. Next, the display unit 120 of the client device 100 displays the authentication-use image.
In step S83, the client device 100 sends the test result (answers) to the server device 200 (step S83). The user reads the contents in the authentication-use image presented at step S82, and inputs, with the input unit 110, test result information, i.e., the read contents. The test result information input with the input unit 110 is transmitted to the server device 200.
In step S84, the server device 200 determines whether the test result information received at step S83 is correct (step S84). The authentication unit 210 makes the determination (authentication) by determining whether the test result information received at step S83 is the correct answer for the authentication-use image presented at step S82. When it is determined that the information is correct (Yes in step S84), the process proceeds to step S85. When it is determined that the information is incorrect (No in step S84), the process returns to step S82.
In step S85, the server device 200 displays the screen page for authentication at the client device 100 (step S85). For example, the server device 200 presents a known screen page for authenticating the user, which includes a user name (user identification character string) input form and a password input form, and prompts the user to input this information for user authentication.
In step S86, the client device 100 sends the user name and the password to the server device 200 (step S86). The user inputs, with the input unit 110, the user name and the password into the screen page for authentication presented at step S85. The information including the user name and the password input with the input unit 110 is transmitted to the server device 200.
In step S87, the server device 200 determines whether the user is an authorized user based on the information including the user name and the password received at step S86 (step S87). The authentication unit 210 makes the determination (authentication) by comparing the information including the user name and the password received at step S86 with user information managed in the HDD 40.
When the user is determined to be an authorized user (Yes in step S87), the service providing unit 250 starts providing a service of the actual purpose, such as displaying a content posting form, for example. When the user is determined to be an unauthorized user (No in step S87), the process returns to step S85. By the above-described process, the server device 200 can perform the authentication operation of determining (authenticating) whether the user of the client device 100 is an actual human being.
The procedures of steps S82 through S84, corresponding to the visual anti-robot test process, and the procedures of steps S85 through S87, corresponding to the user authentication process, can be performed in the inverse order, as shown in
In the following, a description is given of several specific examples of screen pages for authentication and pairs of authentication-use images (group of images) used in the fourth embodiment according to the present invention, which solve the problems of the conventional technology.
(First Example of Authentication-Use Image and Screen Page Presenting Authentication-Use Image)
With reference to
The contents of the displayed screen page shown in
In
In the examples shown in
As evident from
Accordingly, increased complexity in the technology for passing the authentication test (visual anti-robot test) using the first example of the authentication-use image leads to increased cost. Thus, in order to make a nuisance with the use of a “bot”, hardware of higher performance is required, or the frequency of nuisances per unit time needs to be decreased. Therefore, it will become more impractical to make a nuisance. Incidentally, the original image used in the visual anti-robot test is preferably different for each session, and similarly, the order in which the original image and the degraded image are presented is preferably different for each session.
In the present embodiment, noise is used as the factor for degrading the image quality. Other factors may also be used, such as blurring the image or reversing the colors. Another method is to add irregularly-arranged polkadots to the image. Yet another method is to have the user select the processed image with degraded image quality as the answer, instead of the original image.
(Second Example of Screen Page Presenting Authentication-Use Image)
Next, with reference to
In
As described above, in the fourth embodiment, the user (client) inputs the ID of the original image as the answer (in this case, (A)), or clicks the check box 57 corresponding to the original image out of the two check boxes 57 appended to the images, to answer which image is not the degraded one. Alternatively, the user (client) may input the ID of the degraded image as the answer (in this case, (B)), or click the check box 57 corresponding to the degraded image. In either case, when the answer is correct, the server determines that the client is a human being.
(Third Example of Screen Page Presenting Authentication-Use Image)
Next, with reference to
(Fourth Example of Screen Page Presenting Authentication-Use Image)
Next, with reference to
A modification of the fourth example is described with reference to
(Fifth Example of Screen Page Presenting Authentication-Use Image)
With reference to
(Sixth Example of Screen Page Presenting Authentication-Use Image)
With reference to
Furthermore, in the examples of the aforementioned authentication-use images, when an authentication operation (visual anti-robot test) is performed by the same method every time, the person attempting to make a nuisance may create a “bot” that is dedicated to the particular authentication operation, in order to pass the test. Particularly, if the website has a considerably large number of accesses per day, the cost of creating such a “bot” may be decreased to an acceptable amount.
In a modification of the fourth embodiment of the present invention, there is provided a procedure (step) of randomly selecting one of the examples of the authentication-use images to be presented by the server device 200 in each of the sessions (each of the operations shown in
A description is given of a fifth embodiment of the present invention with reference to figures. The operation configuration, the hardware configuration, the functional configuration, and the overall operations of an authentication system according to the fifth embodiment are substantially the same as those of the first embodiment, and are therefore not further described. In the authentication system according to the fifth embodiment, the screen page for authentication presented at step S82 in
In step S82 of
Operations of the test program are described with reference to
The timing of displaying the button prompting the user to click the button is randomly determined when the program is sent out from the server, and the determined timing is passed to the program as a parameter. Therefore, the button is presented at random timings for each of the sessions. The user clicks the button with a mouse when this button is displayed. As shown in
The program executed at the client saves the timings at which the user clicks the button. Each time equals the time that has passed from when the test started (step S1403). When the test ends, the program encrypts the times that have been saved, and sends them to the server (step S1404). The procedure at step S1404 corresponds to step S83 in the fourth embodiment. The clicking times are encrypted with the use of a key embedded in the test program beforehand, which key is required for encrypting the times. A symmetric (private) key method or a public (asymmetric) key method is used for the encryption. When a symmetric key method is used, the same key is used for the encryption by the test program and the decryption by the server. When a public key method is used, the public key is used for the encryption by the test program, and a private key corresponding to the public key is used is used for the decryption by the server. A different key (or pair of keys) is used for each session according to the required level of encryption.
The server uses the symmetric key or the private key to decrypt the response from the client. When the time of the response is appropriate with respect to the display timing that is set beforehand (Yes in step S84), the server determines that the user is a human being. Accordingly, the server presents to the client a screen page for user authentication, including a form for inputting a character string to identify the user (user name) and a form for inputting a password (step S85). The server prompts the user to input this information for authentication, and the user inputs the user name and the password (step S86). When the input user name and password correspond to an authorized user (Yes in step S87), the server starts providing the service.
As long as the user clicks the button with a mouse any time between “display ON” and the next “display ON”, the user is determined to be a human being. When the mouse is clicked at a shifted timing as shown in
It is considerably difficult for a so-called “bot” to pass such a test according to the fifth embodiment. Even if the “bot” were to pass such a test, it would be required to perform considerably complex processes. Such processes require a large memory and a high-speed CPU, which inevitably leads to increased cost. Therefore, it will be impractical to make a nuisance with the use of “bot”. In a system such as CAPTCHA which uses images including characters that are made obscure, it may be difficult even for a human being to read such characters, which is disadvantageous in terms of usability. However, in the present system, the user is only required to perform a considerably simple task of clicking a displayed button with a mouse, thereby minimizing the decrease in usability.
In the fifth embodiment, the user clicks a mouse as a response. However, the response can be made by striking a key of a keyboard, or by touching a screen of a touch screen panel.
In the fifth embodiment, the user is prompted to respond by clicking buttons displayed as shown in
In the fifth embodiment, the user is prompted to respond by clicking a button with a mouse at mouse-clicking timings. The user may also be prompted to click plural of buttons.
The user clicks the buttons in the order of the numbers, and finally clicks the end button. The program saves the order in which the user clicked the buttons. When it is determined that the test has ended as the end button is clicked, the program encrypts the saved order, and sends it to the server. When this order is the same as an order set beforehand (Yes in step S84), the server determines that the user is a human being, and presents to the client a screen page for user authentication, including a form for inputting a character string to identify the user (user name) and a form for inputting a password (step S85).
In this system also, the user is only required to perform a considerably simple task of clicking displayed buttons with a mouse, thereby minimizing the decrease in usability. In the present embodiment, plural buttons are labeled with different numbers, thereby clearly indicating the order or making it easy to guess the order. However, the buttons can be labeled with other characters, which also make it easy to guess the order, such as alphabetical letters “a, b, c . . . ”.
The user only clicks the buttons with numbers, in the order of the numbers, and finally clicks the end button. The program saves the order in which the user clicked the buttons. When it is determined that the test has ended as the end button is clicked, the program encrypts the saved order, and sends it to the server. When this order is the same as an order set beforehand (Yes in step S84), the server determines that the user is a human being, and presents to the client a screen page for user authentication, including a form for inputting a character string to identify the user (user name) and a form for inputting a password (step S85). With such a configuration, the probability of a “bot” selecting the correct answer by chance can be reduced even further than the example described with reference to
The test program displays an image including figures with numbers as shown in
The user clicks the buttons in the order of the numbers, and finally clicks the end button. The program saves the order in which the user clicked the buttons. When it is determined that the test has ended as the end button is clicked, the program encrypts the saved order, and sends it to the server. When the clicked positions are within a region of figures set beforehand, and the order of clicking the figures is the same as an order set beforehand (Yes in step S84), the server determines that the user is a human being, and presents to the client a screen page for user authentication, including a form for inputting a character string to identify the user (user name) and a form for inputting a password (step S85).
In this system also, the user is only required to perform a considerably simple task of clicking displayed buttons with a mouse, thereby minimizing the decrease in usability. In the present embodiment, plural buttons labeled with different numbers, thereby clearly indicating the order or making it easy to guess the order. However, the buttons can be labeled with other characters which make it easy to guess the order, such as alphabetical letters “a, b, c . . . ”.
The user clicks the buttons in the order of the numbers, and finally clicks the end button. The program saves the order in which the user clicked the buttons. When it is determined that the test has ended as the end button is clicked, the program encrypts the saved order, and sends it to the server. When the clicked positions are within a region of figures set beforehand, and the order of clicking the figures is the same as an order set beforehand (Yes in step S84), the server determines that the user is a human being, and presents to the client a screen page for user authentication, including a form for inputting a character string to identify the user (user name) and a form for inputting a password (step S85).
In this system also, the user is only required to perform a considerably simple task of clicking displayed buttons with a mouse, thereby minimizing the decrease in usability. In the present embodiment, plural buttons labeled with different numbers, thereby clearly indicating the order or making it easy to guess the order. However, the buttons can be labeled with other characters which make it easy to guess the order, such as alphabetical letters “a, b, c . . . ”.
A description is given of a sixth embodiment of the present invention with reference to figures. The operation configuration, the hardware configuration, the functional configuration, and the overall operations of an authentication system according to the sixth embodiment are substantially the same as those of the first embodiment, and are therefore not further described. In the authentication system according to the sixth embodiment, the screen page for authentication presented at step S82 in
In step S82 of
In the case of a combination of images that can be easily recognized as shown in
Moreover, even when the computer program is able to restore an original image, the computer program needs to recognize the image. Thus, in order to extract the two words of “banana” and “cherry” from a “bot”, a complex image process is required as the preprocess. Such a preprocess requires a large memory and a high-speed CPU, which inevitably leads to increased cost. Accordingly, increased complexity in the technology for passing the authentication test according to the sixth embodiment leads to increased cost. Thus, in order to make a nuisance with the use of a “bot”, hardware of higher performance is required, or the frequency of nuisances per unit time needs to be decreased. Therefore, it will become more impractical to make a nuisance.
In the present invention, the images are combined in the form of thin strips. The width of the strips is not fixed. The width can be different in each of the sessions. However, depending on the image, the human being may not be able to recognize the image if the strips are too wide or too narrow. In the sixth embodiment, the strips are arranged side by side along a horizontal direction. However, the strips may be arranged side by side along a vertical direction or an oblique direction. The direction in which strips are arranged may be different for each of the sessions.
When two images are combined in the form of strips, the backgrounds of the images preferably have the same color or texture. This way it is advantageous in that the edges cannot be detected (by a “bot”) upon separating the images. When the background colors of the combined images are different as in the example shown in
The presented images may be combined in the form of a jigsaw puzzle as shown in
In the above embodiment, if the number of variations is small, the person attempting to make a nuisance may create a “bot” that is dedicated to the particular test, in order to pass the test. Particularly, if the website has a considerably large number of accesses per day, the cost of creating such a “bot” may be decreased to an acceptable amount. Thus, the combinations are preferably randomly changed, in order to increase the variations of images to be presented. Such an operation increases the difficulty and the cost for creating and executing a “bot”. Therefore, it will become more impractical to make a nuisance.
As described above, if the number of variations of images to be presented is small, the “bot” may pass the test. However, it is difficult to prepare a vast number of illustrations. Therefore, images to be presented can be created with combinations of natural images. However, it is necessary to use an image with which “only a human being can past the test and a robot cannot past the test” in the visual anti-robot test. Accordingly, the image not only needs to be difficult for a robot to recognize, but the image also needs to be easy for a human being to recognize. Incidentally, a natural image means an image such as a photograph. A normatural image means an illustration, a lineal drawing, and CG (Computer Graphics).
For example, when images of the same genre such as “an animal and an animal” are combined (
In a test for making a user answer what the combined images are, it may be possible to pass the test by combining common nouns with the use of a dictionary, without recognizing the images at all. In this case, when there are only two images used for the combination, it may be easy to pass the test. Thus, it is effective to combine a recognition question, which cannot be answered unless the user recognizes the image.
For example, the image shown in
Q1 is a combination of two common nouns in a dictionary, which may be easy for a robot to find, but Q2 cannot be answered unless the image is recognized. A human can easily recognize the image and give the correct answer to Q2, but Q2 is a difficult question for a robot.
Examples of questions that cannot be answered unless the image is recognized are “Q2: What is the shape of this clock?” The answer is “A2: A circle”. It is possible to prepare plural variations of Q2, and present them randomly for each of the sessions. Such an operation increases the difficulty and the cost for creating and executing a “bot”. Therefore, it will become more impractical to make a nuisance.
The present invention is not limited to the specifically disclosed embodiment, and variations and modifications may be made without departing from the scope of the present invention.
The present application is based on Japanese Priority Patent Application No. 2008-063170, filed on Mar. 12, 2008, and Japanese Priority Patent Application No. 2008-234029, filed on Sep. 11, 2008, the entire contents of which are hereby incorporated herein by reference.
Number | Date | Country | Kind |
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2008-063170 | Mar 2008 | JP | national |
2008-234029 | Sep 2008 | JP | national |