Enterprise threat detection (ETD) typically collects and stores a large amount of log data from various systems associated with an enterprise computing system. The collected log data is usually analyzed using forensic-type data analysis tools to identify suspicious behavior and to allow an appropriate response. While the log data contains information such as transient Internet Protocol (IP) addresses or system information, an IP address or system information in a log entry does not specifically provide information of a geographic location where the logged event occurred. This missing geographic data is extremely useful in enterprise threat detection analysis.
Additionally, transient data, such as IP addresses, can have a lifetime shorter than a time period under ETD investigation. Using such transient data in ETD can result in incomplete or erroneous analysis results.
The present disclosure describes methods and systems, including computer-implemented methods, computer program products, and computer systems for location enrichment in enterprise threat detection (ETD).
In an implementation, subnet information and location information is received from a database by a smart data streaming engine (SDS). A particular subnet of the subnet information is associated with a particular location of the location information by a globally unique location ID value. Log event data received in the SDS is normalized as normalized log event data. The normalized log event data is enriched with subnet and location information as enriched log event data and written into a log event persistence in the database. A subnet ID value retrieved from an enriched log event of the enriched log event data is used by an enterprise threat detection (ETD) system to determine a location associated with the enriched log event using a location ID value associated with the subnet ID.
The above-described implementation is implementable using a computer-implemented method; a non-transitory, computer-readable medium storing computer-readable instructions to perform the computer-implemented method; and a computer-implemented system comprising a computer memory interoperably coupled with a hardware processor configured to perform the computer-implemented method/the instructions stored on the non-transitory, computer-readable medium.
The subject matter described in this specification can be implemented in particular implementations so as to realize one or more of the following advantages. First, the described subject matter permits the showing of log events based on a location where the events happened. Second, communications between different locations can be shown. Third, a current network configuration can be shown and a comparison made to a planned network configuration is possible. Fourth, actions associated with a user can be illustrated on a geographic map. This allows, for example, discovery of user password/data sharing and successful phishing attacks (where a user logs on from different locations with large distances in between the locations). Fifth, events, alerts, investigations, etc. can be identified based on locations. For example, how many activities are occurring in a particular location(s) can help determine possible network misconfigurations/attacks. Other advantages will be apparent to those of ordinary skill in the art.
The details of one or more implementations of the subject matter of this specification are set forth in the accompanying drawings and the description below. Other features, aspects, and advantages of the subject matter will become apparent from the description, the drawings, and the claims.
Like reference numbers and designations in the various drawings indicate like elements.
The following detailed description describes for location enrichment in enterprise threat detection (ETD) and is presented to enable any person skilled in the art to make and use the disclosed subject matter in the context of one or more particular implementations. Various modifications to the disclosed implementations will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other implementations and applications without departing from scope of the disclosure. Thus, the present disclosure is not intended to be limited to the described or illustrated implementations, but is to be accorded the widest scope consistent with the principles and features disclosed herein.
Enterprise threat detection typically collects and stores a large amount of log data from various systems associated with an enterprise computing system. The collected log data is usually analyzed using forensic-type data analysis tools to identify suspicious behavior and to allow an appropriate response. While the log data contains information such as Internet Protocol (IP) addresses or system information, an IP address or system information in a log entry does not specifically provide information of a geographic location (hereinafter “geo-location”) where the logged event occurred. This missing geographic data is extremely useful in analysis of certain enterprise threat detection use cases. For example, a user logs on to a computing system using a client with a certain IP address which is located in Europe. A few seconds later, the same user passes an access control system at a location in the United States. If the two events are correlated only with user information, a threat is not readily apparent. However, when geo-location is considered, the event should be elevated for further analysis due to various possible use cases, some of which could be malicious. For example, the user could not realistically travel from Europe to the United States in a matter of seconds, so details around the European and United States logins should be analyzed in more detail. While the distant login may be innocent (for example, a legitimate remote desktop or other remote-type login to download or access data, assist a user on the other computer, etc.), questions to explore can include, where is the user geographically located? What systems were accessed and for what purpose? Was the access to the remote computer from a computer assigned to the user or using a user ID/password of the user from a different computer? Is the user authorized to perform remote logins to other computers?
Described is the enrichment of network subnet information with IP address information. Subnets and systems known to an ETD system can also be assigned to a location which contains a geo-location object. Enrichment of networks with the described IP address, location, and geo-location information will permit log events to be analyzed on the basis of locations and calculations related to the different locations (for example, distance, time to travel, operations and actions over a distance, etc.) can be calculated and used for various ETD patterns which include, for example, one or more defined evaluations with specified methods, data types/values, time frames, and the like.
Additionally, transient data, such as IP addresses, can have a lifetime shorter than a time period under ETD investigation. Using such transient data in ETD can result in incomplete or erroneous analysis results. Instead stable and reliable information is required which allows correlation of log event data containing different IP Addresses but refers to the same subnet (and same subnet location). In a typical implementation, subnets are stored in the ETD system as master data. From an IP address with knowledge of all IP subnets, a subnet of a particular IP address in a log entry can be determined. A subnet identifier (ID) is then determined and the log event is enriched with the subnet ID. As mentioned above, subnets can be assigned with location information which carries geo-location and semantical description (for example, buildings, particular rooms, etc.) information. ETD functionality is then enhanced to allow search and browsing for log events by location attributes (for example geo-location or other attributes of the location object such as a computing center name, office building, assigned office, etc.).
In the database 102, a subnet-location persistence 110 maintains a list of subnets (for example, a network address, subnet mask, subnet ID). The subnet-location persistence 110 also maintains one or more geo-location objects storing location-associated data. In typical implementations, a geo-location object includes:
Each geo-location is associated with a location ID. The location ID is can be maintained with both subnets and system using the location ID in subnet/system database objects. Using the location ID, a particular geo-location object (and associated data) can be accessed.
Once ETD functionality is deployed (for example using a deployment unit—not illustrated) on a system, information from the subnet-location persistence 110 is read from the subnet-location persistence 110 and written into a subnet-location cache 114 of the SDS 104 using an SDS database in adapter 112. The SDS database in adaptor 112 couples the database 102 and the SDS 104. In some implementations, the SDS database in adaptor 112 can be configured for fast database retrieval/storage. Information is typically held in the subnet-location cache 114 in the form of a dictionary table and a vector so that enrichment of log event data 108 can be performed quickly and without delay. At this point, the SDS 104 is ready to enrich log event data 108 using a subnet enrichment engine 116 able to access data from the subnet-location cache 114.
The log event data 108 is typically read at regular intervals (for example, periodically) so that updates/maintenance of subnet information in the subnet-location persistence 110 is respected. In other implementations, a PUSH or PULL (or both) operation can be used so that the subnet enrichment engine 116 receives the log event data 108.
Log event data 108 entering the SDS 104 is normalized into a consistent format (for example, by the subnet enrichment engine 116 or other component (whether or not illustrated) or a combination of elements). For example, the data can be normalized into a consistent format for use by some or all components of the ETD system, such as databases, graphical user interfaces (GUIs), etc.
The subnet enrichment engine 116 then enriches the log event data 108. Enrichment typically includes looking at all subnet masks (for example, closest mask first), applying, for example, a ‘bitand’ operation (or other operation) between each IP token and subnet mask token, and a searching for a suitable network address with the help of the calculated ‘bitand’ (or other operation) result. Typically, this process continues for all the subnet masks maintained in the subnet-location persistence 110 until a suitable network address (and associated subnet ID) is identified. The result of this process (the identified subnet ID value) is stored with the event log data 108 as enriched log event data 118. As detailed below, a location ID value can be associated with the subnet ID value to permit determination of a particular location associated with the subnet ID value.
The enriched log event data 118 is written to a log event persistence 122 of the database 102 using an SDS database out adapter 120 configured for fast database storage. The SDS database out adaptor 120 couples the SDS 104 and the database 102. In some implementations, the SDS database out adapter 120 and the SDS database in adapter 112 can be the same component performing both in/out database functions.
When the enriched log event data 118 is later retrieved from the log event persistence 122, the associated subnet ID information can be used to determine a location the event occurred (for example, from which building, floor, or room the event was produced in).
At 202, locations are maintained in a database with subnet information. The data is stored in a subnet-location persistence. For example, users can access the database using a GUI application to perform the maintenance. From 202, method 200 proceeds to 204.
At 204, subnet-location data is read from the database and written into a smart data streaming engine (SDS) subnet-location cache. From 204, method 200 proceeds to 206.
At 206, log event data is received by an SDS subnet enrichment engine. The received log event data is normalized into a standard format for use by components of the ETD system. From 206, method 200 proceeds to 208.
At 208, the received log event data is enriched by the SDS subnet enrichment engine using data read from the subnet-location cache and saved as enriched log event data. From 208, method 200 proceeds to 210.
At 210, the enriched log event data is persisted in the database by writing the enriched log event data into a log event persistence in the database. From 210, method 200 proceeds to 212.
At 212, an enriched log event of the enriched log event data is retrieved from the log event persistence for ETD analysis. Using the enriched log event, a subnet ID value associated with the enriched log event (due to the enrichment) can be retrieved and used to determine a particular location that the event occurred using the location ID value associated with the subnet ID value. After 212, method 200 stops.
In typical implementations, locations can be associated to subnets and systems.
On the right side of user interface 1000, user options to distribute various selectable dimensions of the set of log data. Each displayed chart is independent and provides a distributed view of the current subset of log data based on the selected path (for example chart 1014) according to a particular dimension 1016 (here “Network, Subnet, Location”). Note that a similar action can be made to create a distribution according to a dimension related to a system (for example, “System Location, Actor”).
In some implementations, initial distributions (the number depending on, for example, display size, data types available, etc.) can be preselected based on any relevant criteria consistent with this disclosure. The user can change the initial, pre-selections to view other distributions. Changing the path will automatically change the selected distributions to reflect the updated subset of data. In some implementations, the right side of UI 1000 can be scrolled to permit addition of (using a user interface element—not illustrated) or visualization of other available distributions. In some implementations, the visualizations can be set to none to remove them from the display or removed (using a user interface element—not illustrated).
The computer 1402 can serve in a role as a client, network component, a server, a database or other persistency, or any other component (or a combination of roles) of a computer system for performing the subject matter described in the instant disclosure. The illustrated computer 1402 is communicably coupled with a network 1430. In some implementations, one or more components of the computer 1402 may be configured to operate within environments, including cloud-computing-based, local, global, or other environment (or a combination of environments).
At a high level, the computer 1402 is an electronic computing device operable to receive, transmit, process, store, or manage data and information associated with the described subject matter. According to some implementations, the computer 1402 may also include or be communicably coupled with an application server, e-mail server, web server, caching server, streaming data server, business intelligence (BI) server, or other server (or a combination of servers).
The computer 1402 can receive requests over network 1430 from a client application (for example, executing on another computer 1402) and responding to the received requests by processing the said requests in an appropriate software application. In addition, requests may also be sent to the computer 1402 from internal users (for example, from a command console or by other appropriate access method), external or third-parties, other automated applications, as well as any other appropriate entities, individuals, systems, or computers.
Each of the components of the computer 1402 can communicate using a system bus 1403. In some implementations, any or all of the components of the computer 1402, both hardware or software (or a combination of hardware and software), may interface with each other or the interface 1404 (or a combination of both) over the system bus 1403 using an application programming interface (API) 1412 or a service layer 1413 (or a combination of the API 1412 and service layer 1413). The API 1412 may include specifications for routines, data structures, and object classes. The API 1412 may be either computer-language independent or dependent and refer to a complete interface, a single function, or even a set of APIs. The service layer 1413 provides software services to the computer 1402 or other components (whether or not illustrated) that are communicably coupled to the computer 1402. The functionality of the computer 1402 may be accessible for all service consumers using this service layer. Software services, such as those provided by the service layer 1413, provide reusable, defined business functionalities through a defined interface. For example, the interface may be software written in JAVA, C++, or other suitable language providing data in extensible markup language (XML) format or other suitable format. While illustrated as an integrated component of the computer 1402, alternative implementations may illustrate the API 1412 or the service layer 1413 as stand-alone components in relation to other components of the computer 1402 or other components (whether or not illustrated) that are communicably coupled to the computer 1402. Moreover, any or all parts of the API 1412 or the service layer 1413 may be implemented as child or sub-modules of another software module, enterprise application, or hardware module without departing from the scope of this disclosure.
The computer 1402 includes an interface 1404. Although illustrated as a single interface 1404 in
The computer 1402 includes a processor 1405. Although illustrated as a single processor 1405 in
The computer 1402 also includes a database 1406 that can hold data for the computer 1402 or other components (or a combination of both) that can be connected to the network 1430 (whether illustrated or not). For example, database 1406 can be an in-memory, conventional, or other type of database storing data consistent with this disclosure. In some implementations, database 1406 can be a combination of two or more different database types (for example, a hybrid in-memory and conventional database) according to particular needs, desires, or particular implementations of the computer 1402 and the described functionality. Although illustrated as a single database 1406 in
The computer 1402 also includes a memory 1407 that can hold data for the computer 1402 or other components (or a combination of both) that can be connected to the network 1430 (whether illustrated or not). For example, memory 1407 can be random access memory (RAM), read-only memory (ROM), optical, magnetic, and the like storing data consistent with this disclosure. In some implementations, memory 1407 can be a combination of two or more different types of memory (for example, a combination of RAM and magnetic storage) according to particular needs, desires, or particular implementations of the computer 1402 and the described functionality. Although illustrated as a single memory 1407 in
The application 1408 is an algorithmic software engine providing functionality according to particular needs, desires, or particular implementations of the computer 1402, particularly with respect to functionality described in this disclosure. For example, application 1408 can serve as one or more components, modules, applications, etc. Further, although illustrated as a single application 1408, the application 1408 may be implemented as multiple applications 1407 on the computer 1402. In addition, although illustrated as integral to the computer 1402, in alternative implementations, the application 1408 can be external to the computer 1402.
There may be any number of computers 1402 associated with, or external to, a computer system containing computer 1402, each computer 1402 communicating over network 1430. Further, the term “client,” “user,” and other appropriate terminology may be used interchangeably as appropriate without departing from the scope of this disclosure. Moreover, this disclosure contemplates that many users may use one computer 1402, or that one user may use multiple computers 1402.
Described implementations of the subject matter can include one or more features, alone or in combination.
For example, in a first implementation, a computer-implemented method, comprising: receiving subnet information and location information from a database into a smart data streaming engine (SDS), wherein a particular subnet of the subnet information is associated with a particular location of the location information by a globally unique location ID value; normalizing received log event data in the SDS as normalized log event data; enriching the normalized log event data with subnet and location information as enriched log event data; writing the enriched log event data into a log event persistence in the database; and using a subnet ID value retrieved from an enriched log event of the enriched log event data by an enterprise threat detection (ETD) system to determine a location associated with the enriched log event using the location ID value associated with the subnet ID value.
The foregoing and other described implementations can each optionally include one or more of the following features:
A first feature, combinable with any of the following features, wherein the subnet information and the location information is maintained in the database.
A second feature, combinable with any of the previous or following features, wherein system information is maintained in the database, and wherein a particular system of the system information is associated with a particular location of the location information by a particular globally unique location ID value.
A third feature, combinable with any of the previous or following features, comprising: reading the subnet information and the location information from the subnet-location persistence; and writing the subnet information and the location information into a subnet-location cache of the SDS.
A fourth feature, combinable with any of the previous or following features, wherein the subnet information and the location information is read from the subnet-location persistence and written to the subnet-location cache using an SDS database in adapter coupling the database and the SDS.
A fifth feature, combinable with any of the previous or following features, wherein the enriched log event data is written to the log event persistence using an SDS database out adapter coupling the SDS and the database.
A sixth feature, combinable with any of the previous or following features, comprising enriching the normalized log event data with a determined subnet ID value.
In a second implementation, a non-transitory, computer-readable medium storing one or more instructions executable by a computer system to perform operations comprising: receiving subnet information and location information from a database into a smart data streaming engine (SDS), wherein a particular subnet of the subnet information is associated with a particular location of the location information by a globally unique location ID value; normalizing received log event data in the SDS as normalized log event data; enriching the normalized log event data with subnet and location information as enriched log event data; writing the enriched log event data into a log event persistence in the database; and using a subnet ID value retrieved from an enriched log event of the enriched log event data by an enterprise threat detection (ETD) system to determine a location associated with the enriched log event using the location ID value associated with the subnet ID value.
The foregoing and other described implementations can each optionally include one or more of the following features:
A first feature, combinable with any of the following features, wherein the subnet information and the location information is maintained in the database.
A second feature, combinable with any of the previous or following features, wherein system information is maintained in the database, and wherein a particular system of the system information is associated with a particular location of the location information by a particular globally unique location ID value.
A third feature, combinable with any of the previous or following features, comprising one or more instructions to: read the subnet information and the location information from the subnet-location persistence; and write the subnet information and the location information into a subnet-location cache of the SDS.
A fourth feature, combinable with any of the previous or following features, wherein the subnet information and the location information is read from the subnet-location persistence and written to the subnet-location cache using an SDS database in adapter coupling the database and the SDS.
A fifth feature, combinable with any of the previous or following features, wherein the enriched log event data is written to the log event persistence using an SDS database out adapter coupling the SDS and the database.
A sixth feature, combinable with any of the previous or following features, comprising one or more instructions to enrich the normalized log event data with a determined subnet ID value.
In a third implementation, a computer-implemented system, comprising: a computer memory; and a hardware processor interoperably coupled with the computer memory and configured to perform operations comprising: receiving subnet information and location information from a database into a smart data streaming engine (SDS), wherein a particular subnet of the subnet information is associated with a particular location of the location information by a globally unique location ID value; normalizing received log event data in the SDS as normalized log event data; enriching the normalized log event data with subnet and location information as enriched log event data; writing the enriched log event data into a log event persistence in the database; and using a subnet ID value retrieved from an enriched log event of the enriched log event data by an enterprise threat detection (ETD) system to determine a location associated with the enriched log event using the location ID value associated with the subnet ID value.
The foregoing and other described implementations can each optionally include one or more of the following features:
A first feature, combinable with any of the following features, wherein the subnet information and the location information is maintained in the database.
A second feature, combinable with any of the previous or following features, wherein system information is maintained in the database, and wherein a particular system of the system information is associated with a particular location of the location information by a particular globally unique location ID value.
A third feature, combinable with any of the previous or following features, configured to: read the subnet information and the location information from the subnet-location persistence; and write the subnet information and the location information into a subnet-location cache of the SDS.
A fourth feature, combinable with any of the previous or following features, wherein the subnet information and the location information is read from the subnet-location persistence and written to the subnet-location cache using an SDS database in adapter coupling the database and the SDS.
A fifth feature, combinable with any of the previous or following features, wherein the enriched log event data is written to the log event persistence using an SDS database out adapter coupling the SDS and the database.
A sixth feature, combinable with any of the previous or following features, configured to enrich the normalized log event data with a determined subnet ID value.
Implementations of the subject matter and the functional operations described in this specification can be implemented in digital electronic circuitry, in tangibly embodied computer software or firmware, in computer hardware, including the structures disclosed in this specification and their structural equivalents, or in combinations of one or more of them. Implementations of the subject matter described in this specification can be implemented as one or more computer programs, that is, one or more modules of computer program instructions encoded on a tangible, non-transitory, computer-readable computer-storage medium for execution by, or to control the operation of, data processing apparatus. Alternatively or in addition, the program instructions can be encoded on an artificially generated propagated signal, for example, a machine-generated electrical, optical, or electromagnetic signal that is generated to encode information for transmission to suitable receiver apparatus for execution by a data processing apparatus. The computer-storage medium can be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or a combination of computer-storage mediums.
The term “real-time,” “real time,” “realtime,” “real (fast) time (RFT),” “near(ly) real-time (NRT),” “quasi real-time,” or similar terms (as understood by one of ordinary skill in the art), means that an action and a response are temporally proximate such that an individual perceives the action and the response occurring substantially simultaneously. For example, the time difference for a response to display (or for an initiation of a display) of data following the individual's action to access the data may be less than 1 ms, less than 1 sec., less than 5 secs., etc. While the requested data need not be displayed (or initiated for display) instantaneously, it is displayed (or initiated for display) without any intentional delay, taking into account processing limitations of a described computing system and time required to, for example, gather, accurately measure, analyze, process, store, and/or transmit the data.
The terms “data processing apparatus,” “computer,” or “electronic computer device” (or equivalent as understood by one of ordinary skill in the art) refer to data processing hardware and encompass all kinds of apparatus, devices, and machines for processing data, including by way of example, a programmable processor, a computer, or multiple processors or computers. The apparatus can also be or further include special purpose logic circuitry, for example, a central processing unit (CPU), an FPGA (field programmable gate array), or an ASIC (application-specific integrated circuit). In some implementations, the data processing apparatus or special purpose logic circuitry (or a combination of the data processing apparatus or special purpose logic circuitry) may be hardware- or software-based (or a combination of both hardware- and software-based). The apparatus can optionally include code that creates an execution environment for computer programs, for example, code that constitutes processor firmware, a protocol stack, a database management system, an operating system, or a combination of execution environments. The present disclosure contemplates the use of data processing apparatuses with or without conventional operating systems, for example LINUX, UNIX, WINDOWS, MAC OS, ANDROID, IOS, or any other suitable conventional operating system.
A computer program, which may also be referred to or described as a program, software, a software application, a module, a software module, a script, or code can be written in any form of programming language, including compiled or interpreted languages, or declarative or procedural languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment. A computer program may, but need not, correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs or data, for example, one or more scripts stored in a markup language document, in a single file dedicated to the program in question, or in multiple coordinated files, for example, files that store one or more modules, sub-programs, or portions of code. A computer program can be deployed to be executed on one computer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communication network. While portions of the programs illustrated in the various figures are shown as individual modules that implement the various features and functionality through various objects, methods, or other processes, the programs may instead include a number of sub-modules, third-party services, components, libraries, and such, as appropriate. Conversely, the features and functionality of various components can be combined into single components as appropriate.
The processes and logic flows described in this specification can be performed by one or more programmable computers executing one or more computer programs to perform functions by operating on input data and generating output. The processes and logic flows can also be performed by, and apparatus can also be implemented as, special purpose logic circuitry, for example, a CPU, an FPGA, or an ASIC.
Computers suitable for the execution of a computer program can be based on general or special purpose microprocessors, both, or any other kind of CPU. Generally, a CPU will receive instructions and data from a read-only memory (ROM) or a random access memory (RAM), or both. The essential elements of a computer are a CPU, for performing or executing instructions, and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to, receive data from or transfer data to, or both, one or more mass storage devices for storing data, for example, magnetic, magneto-optical disks, or optical disks. However, a computer need not have such devices. Moreover, a computer can be embedded in another device, for example, a mobile telephone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a global positioning system (GPS) receiver, or a portable storage device, for example, a universal serial bus (USB) flash drive, to name just a few.
Computer-readable media (transitory or non-transitory, as appropriate) suitable for storing computer program instructions and data include all forms of non-volatile memory, media and memory devices, including by way of example semiconductor memory devices, for example, erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), and flash memory devices; magnetic disks, for example, internal hard disks or removable disks; magneto-optical disks; and CD-ROM, DVD+/−R, DVD-RAM, and DVD-ROM disks. The memory may store various objects or data, including caches, classes, frameworks, applications, backup data, jobs, web pages, web page templates, database tables, repositories storing dynamic information, and any other appropriate information including any parameters, variables, algorithms, instructions, rules, constraints, or references thereto. Additionally, the memory may include any other appropriate data, such as logs, policies, security or access data, reporting files, as well as others. The processor and the memory can be supplemented by, or incorporated in, special purpose logic circuitry.
To provide for interaction with a user, implementations of the subject matter described in this specification can be implemented on a computer having a display device, for example, a CRT (cathode ray tube), LCD (liquid crystal display), LED (Light Emitting Diode), or plasma monitor, for displaying information to the user and a keyboard and a pointing device, for example, a mouse, trackball, or trackpad by which the user can provide input to the computer. Input may also be provided to the computer using a touchscreen, such as a tablet computer surface with pressure sensitivity, a multi-touch screen using capacitive or electric sensing, or other type of touchscreen. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback, for example, visual feedback, auditory feedback, or tactile feedback; and input from the user can be received in any form, including acoustic, speech, or tactile input. In addition, a computer can interact with a user by sending documents to and receiving documents from a device that is used by the user; for example, by sending web pages to a web browser on a user's client device in response to requests received from the web browser.
The term “graphical user interface,” or “GUI,” may be used in the singular or the plural to describe one or more graphical user interfaces and each of the displays of a particular graphical user interface. Therefore, a GUI may represent any graphical user interface, including but not limited to, a web browser, a touch screen, or a command line interface (CLI) that processes information and efficiently presents the information results to the user. In general, a GUI may include a plurality of user interface (UI) elements, some or all associated with a web browser, such as interactive fields, pull-down lists, and buttons operable by the business suite user. These and other UI elements may be related to or represent the functions of the web browser.
Implementations of the subject matter described in this specification can be implemented in a computing system that includes a back-end component, for example, as a data server, or that includes a middleware component, for example, an application server, or that includes a front-end component, for example, a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the subject matter described in this specification, or any combination of one or more such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of wireline or wireless digital data communication (or a combination of data communication), for example, a communication network. Examples of communication networks include a local area network (LAN), a radio access network (RAN), a metropolitan area network (MAN), a wide area network (WAN), Worldwide Interoperability for Microwave Access (WIMAX), a wireless local area network (WLAN) using, for example, 802.11 a/b/g/n or 802.20 (or a combination of 802.11x and 802.20 or other protocols consistent with this disclosure), all or a portion of the Internet, or any other communication system or systems at one or more locations (or a combination of communication networks). The network may communicate with, for example, Internet Protocol (IP) packets, Frame Relay frames, Asynchronous Transfer Mode (ATM) cells, voice, video, data, or other suitable information (or a combination of communication types) between network addresses.
The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
In some implementations, any or all of the components of the computing system, both hardware or software (or a combination of hardware and software), may interface with each other or the interface using an application programming interface (API) or a service layer (or a combination of API and service layer). The API may include specifications for routines, data structures, and object classes. The API may be either computer language independent or dependent and refer to a complete interface, a single function, or even a set of APIs. The service layer provides software services to the computing system. The functionality of the various components of the computing system may be accessible for all service consumers using this service layer. Software services provide reusable, defined business functionalities through a defined interface. For example, the interface may be software written in JAVA, C++, or other suitable language providing data in extensible markup language (XML) format or other suitable format. The API or service layer (or a combination of the API and the service layer) may be an integral or a stand-alone component in relation to other components of the computing system. Moreover, any or all parts of the service layer may be implemented as child or sub-modules of another software module, enterprise application, or hardware module without departing from the scope of this disclosure.
While this specification contains many specific implementation details, these should not be construed as limitations on the scope of any invention or on the scope of what may be claimed, but rather as descriptions of features that may be specific to particular implementations of particular inventions. Certain features that are described in this specification in the context of separate implementations can also be implemented, in combination, in a single implementation. Conversely, various features that are described in the context of a single implementation can also be implemented in multiple implementations, separately, or in any suitable sub-combination. Moreover, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can, in some cases, be excised from the combination, and the claimed combination may be directed to a sub-combination or variation of a sub-combination.
Particular implementations of the subject matter have been described. Other implementations, alterations, and permutations of the described implementations are within the scope of the following claims as will be apparent to those skilled in the art. While operations are depicted in the drawings or claims in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed (some operations may be considered optional), to achieve desirable results. In certain circumstances, multitasking or parallel processing (or a combination of multitasking and parallel processing) may be advantageous and performed as deemed appropriate.
Moreover, the separation or integration of various system modules and components in the implementations described above should not be understood as requiring such separation or integration in all implementations, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.
Accordingly, the above description of example implementations does not define or constrain this disclosure. Other changes, substitutions, and alterations are also possible without departing from the spirit and scope of this disclosure.
Furthermore, any claimed implementation below is considered to be applicable to at least a computer-implemented method; a non-transitory, computer-readable medium storing computer-readable instructions to perform the computer-implemented method; and a computer system comprising a computer memory interoperably coupled with a hardware processor configured to perform the computer-implemented method or the instructions stored on the non-transitory, computer-readable medium.
Number | Name | Date | Kind |
---|---|---|---|
5440726 | Fuchs | Aug 1995 | A |
5960170 | Chen | Sep 1999 | A |
6173418 | Fujino et al. | Jan 2001 | B1 |
6629106 | Narayanaswamy | Sep 2003 | B1 |
6779001 | Kanai et al. | Aug 2004 | B1 |
7376969 | Njemanze | May 2008 | B1 |
7380205 | Bezrukov et al. | May 2008 | B2 |
7441197 | Tschiegg et al. | Oct 2008 | B2 |
7457792 | Weigt et al. | Nov 2008 | B2 |
7457793 | Weigt et al. | Nov 2008 | B2 |
7457794 | Weigt et al. | Nov 2008 | B2 |
7545969 | Bennett | Jun 2009 | B2 |
7624092 | Lieske et al. | Nov 2009 | B2 |
7627544 | Chkodrov | Dec 2009 | B2 |
7756808 | Weigt et al. | Jul 2010 | B2 |
7756809 | Weigt et al. | Jul 2010 | B2 |
7761396 | Weigt et al. | Jul 2010 | B2 |
7783723 | Peng et al. | Aug 2010 | B2 |
7788718 | Fei | Aug 2010 | B1 |
7872982 | Atkins | Jan 2011 | B2 |
7908660 | Bahl | Mar 2011 | B2 |
7934257 | Kienzle | Apr 2011 | B1 |
7961633 | Shankar | Jun 2011 | B2 |
7971209 | Eberlein et al. | Jun 2011 | B2 |
8051034 | Mehta et al. | Nov 2011 | B2 |
8091117 | Williams | Jan 2012 | B2 |
8474047 | Adelstein | Jun 2013 | B2 |
8484726 | Sutton | Jul 2013 | B1 |
8554907 | Chen et al. | Oct 2013 | B1 |
8661103 | Mehta et al. | Feb 2014 | B2 |
8775671 | Rodeck et al. | Jul 2014 | B2 |
8892454 | Rabetge et al. | Nov 2014 | B2 |
8954602 | Seifert et al. | Feb 2015 | B2 |
8973147 | Pearcy | Mar 2015 | B2 |
9037678 | Mehta et al. | May 2015 | B2 |
9075633 | Nos | Jul 2015 | B2 |
9106697 | Capalik et al. | Aug 2015 | B2 |
9116906 | Nos et al. | Aug 2015 | B2 |
9148488 | Rabetge et al. | Sep 2015 | B2 |
9170951 | He | Oct 2015 | B1 |
9251011 | Meier et al. | Feb 2016 | B2 |
9262519 | Saurabh | Feb 2016 | B1 |
9304978 | Bezrukov et al. | Apr 2016 | B2 |
9313421 | Deshpande | Apr 2016 | B2 |
9336385 | Spencer | May 2016 | B1 |
9348665 | Storz et al. | May 2016 | B2 |
9383934 | Likacs | Jul 2016 | B1 |
9419989 | Harris | Aug 2016 | B2 |
9524389 | Roth | Dec 2016 | B1 |
9619984 | Donovan | Apr 2017 | B2 |
9690931 | Anantharaju et al. | Jun 2017 | B1 |
9779147 | Sherman et al. | Oct 2017 | B1 |
9843596 | Avelbuch | Dec 2017 | B1 |
9979741 | Fehrman | May 2018 | B2 |
10001389 | Das et al. | Jun 2018 | B1 |
10079842 | Brandwine et al. | Sep 2018 | B1 |
10102379 | Seifert et al. | Oct 2018 | B1 |
10140447 | Rahaman et al. | Nov 2018 | B2 |
10148675 | Brandwine et al. | Dec 2018 | B1 |
20020070953 | Barg | Jun 2002 | A1 |
20030074471 | Anderson | Apr 2003 | A1 |
20030115484 | Mariconi et al. | Jun 2003 | A1 |
20030217137 | Roese | Nov 2003 | A1 |
20040044912 | Connary | Mar 2004 | A1 |
20040078490 | Anderson | Apr 2004 | A1 |
20040093513 | Cantrell | May 2004 | A1 |
20060037075 | Frattura | Feb 2006 | A1 |
20060059115 | Gulfleisch et al. | Mar 2006 | A1 |
20060161816 | Gula et al. | Jul 2006 | A1 |
20060253907 | McConnell | Nov 2006 | A1 |
20070067438 | Goranson et al. | Mar 2007 | A1 |
20070073519 | Long | Mar 2007 | A1 |
20070100905 | Masters et al. | May 2007 | A1 |
20070115998 | McElligott | May 2007 | A1 |
20070136437 | Shankar et al. | Jun 2007 | A1 |
20070150596 | Miller et al. | Jun 2007 | A1 |
20070183389 | Clee | Aug 2007 | A1 |
20070186284 | McConnell | Aug 2007 | A1 |
20070266387 | Henmi | Nov 2007 | A1 |
20070283192 | Shevchenko | Dec 2007 | A1 |
20070300296 | Kudla | Dec 2007 | A1 |
20080033966 | Wahl | Feb 2008 | A1 |
20080034425 | Overcash et al. | Feb 2008 | A1 |
20080080384 | Atkins | Apr 2008 | A1 |
20080091681 | Dwivedi | Apr 2008 | A1 |
20080295173 | Tsvetanov | Nov 2008 | A1 |
20080320552 | Kumar | Dec 2008 | A1 |
20090044277 | Aaron et al. | Feb 2009 | A1 |
20090049518 | Roman | Feb 2009 | A1 |
20090288164 | Adelstein | Nov 2009 | A1 |
20090293046 | Cheriton | Nov 2009 | A1 |
20090300045 | Chaudhry et al. | Dec 2009 | A1 |
20090312026 | Parameswar | Dec 2009 | A1 |
20100011031 | Huang | Jan 2010 | A1 |
20100114832 | Lillibridge | May 2010 | A1 |
20100180325 | Golobay | Jul 2010 | A1 |
20110213741 | Shama | Sep 2011 | A1 |
20110277034 | Hanson | Nov 2011 | A1 |
20110320816 | Yao | Dec 2011 | A1 |
20120005542 | Petersen | Jan 2012 | A1 |
20120158653 | Shaffer et al. | Jun 2012 | A1 |
20120167161 | Kim et al. | Jun 2012 | A1 |
20120191660 | Hoog | Jul 2012 | A1 |
20120210434 | Curtis et al. | Aug 2012 | A1 |
20120271790 | Lappas et al. | Oct 2012 | A1 |
20120317078 | Zhou et al. | Dec 2012 | A1 |
20130086023 | Tsukamoto et al. | Apr 2013 | A1 |
20130106830 | de Loera | May 2013 | A1 |
20130198840 | Drissi et al. | Aug 2013 | A1 |
20130212709 | Tucker | Aug 2013 | A1 |
20130262311 | Buhrmann | Oct 2013 | A1 |
20130298243 | Kumar et al. | Nov 2013 | A1 |
20130304665 | Rodeck et al. | Nov 2013 | A1 |
20130304666 | Rodeck et al. | Nov 2013 | A1 |
20130305369 | Karta | Nov 2013 | A1 |
20130326079 | Seifert et al. | Dec 2013 | A1 |
20130347111 | Karta | Dec 2013 | A1 |
20140047413 | Sheive et al. | Feb 2014 | A1 |
20140201836 | Amsler | Jul 2014 | A1 |
20140223283 | Hancock | Aug 2014 | A1 |
20140244623 | King | Aug 2014 | A1 |
20140317681 | Shende | Oct 2014 | A1 |
20150007325 | Eliseev | Jan 2015 | A1 |
20150067880 | Ward | Mar 2015 | A1 |
20150106867 | Liang | Apr 2015 | A1 |
20150143521 | Eliseev | May 2015 | A1 |
20150154524 | Borodow | Jun 2015 | A1 |
20150180891 | Seward | Jun 2015 | A1 |
20150215329 | Singla | Jul 2015 | A1 |
20150237065 | Roytman | Aug 2015 | A1 |
20150264011 | Liang | Sep 2015 | A1 |
20150278371 | Anand | Oct 2015 | A1 |
20150281278 | Gooding | Oct 2015 | A1 |
20150319185 | Kirti | Nov 2015 | A1 |
20150341389 | Kurakami | Nov 2015 | A1 |
20150347751 | Card et al. | Dec 2015 | A1 |
20150355957 | Steiner | Dec 2015 | A1 |
20150358344 | Mumcuoglu | Dec 2015 | A1 |
20150381646 | Lin | Dec 2015 | A1 |
20160057166 | Chesla | Feb 2016 | A1 |
20160057167 | Bach et al. | Feb 2016 | A1 |
20160065594 | Srivastava et al. | Mar 2016 | A1 |
20160092535 | Kuchibhotla et al. | Mar 2016 | A1 |
20160127391 | Kobres | May 2016 | A1 |
20160164891 | Satish | Jun 2016 | A1 |
20160202893 | Mustonen et al. | Jul 2016 | A1 |
20160226905 | Baikalov et al. | Aug 2016 | A1 |
20160248798 | Cabrera et al. | Aug 2016 | A1 |
20160291982 | Mizrahi | Oct 2016 | A1 |
20160292061 | Marron | Oct 2016 | A1 |
20160337384 | Jansson | Nov 2016 | A1 |
20160359886 | Yadav et al. | Dec 2016 | A1 |
20160364315 | Lee | Dec 2016 | A1 |
20160364571 | Lee | Dec 2016 | A1 |
20160373476 | Dell'anno et al. | Dec 2016 | A1 |
20160378978 | Singla | Dec 2016 | A1 |
20160381049 | Lakhani | Dec 2016 | A1 |
20170004005 | Elliott | Jan 2017 | A1 |
20170026400 | Adams et al. | Jan 2017 | A1 |
20170031002 | Newton et al. | Feb 2017 | A1 |
20170034023 | Nickolov | Feb 2017 | A1 |
20170070415 | Bell et al. | Mar 2017 | A1 |
20170091008 | Cherbakov | Mar 2017 | A1 |
20170093902 | Roundy et al. | Mar 2017 | A1 |
20170148060 | Showers | May 2017 | A1 |
20170169217 | Rahaman | Jun 2017 | A1 |
20170251365 | Burchardt | Aug 2017 | A1 |
20170270006 | Kankylas | Sep 2017 | A1 |
20170279837 | Dasgupta | Sep 2017 | A1 |
20170287179 | Tibshirani et al. | Oct 2017 | A1 |
20170302685 | Ladnai et al. | Oct 2017 | A1 |
20170308602 | Raghunathan et al. | Oct 2017 | A1 |
20170310690 | Mestha | Oct 2017 | A1 |
20170316026 | Kanthak et al. | Nov 2017 | A1 |
20170322993 | Brodt et al. | Nov 2017 | A1 |
20170324766 | Gonzalez | Nov 2017 | A1 |
20180027002 | Rodeck et al. | Jan 2018 | A1 |
20180027010 | Pritzkau et al. | Jan 2018 | A1 |
20180059876 | Peng et al. | Mar 2018 | A1 |
20180091535 | Chrosziel | Mar 2018 | A1 |
20180091536 | Chrosziel et al. | Mar 2018 | A1 |
20180157835 | Nos | Jun 2018 | A1 |
20180173872 | Lam et al. | Jun 2018 | A1 |
20180173873 | Hassforther et al. | Jun 2018 | A1 |
20180176234 | Kunz et al. | Jun 2018 | A1 |
20180176235 | Lam et al. | Jun 2018 | A1 |
20180176238 | Nos et al. | Jun 2018 | A1 |
20180234447 | Mueen | Aug 2018 | A1 |
20190005423 | Pritzkau et al. | Jan 2019 | A1 |
20190007435 | Pritzkau et al. | Jan 2019 | A1 |
Entry |
---|
Office Action in related U.S. Appl. No. 15/216,201 dated Mar. 7, 2018; 14 pages. |
Office Action in related U.S. Appl. No. 15/274,569 dated Apr. 16, 2018; 11 pages. |
U.S. Office Action in related U.S. Appl. No. 15/274,569 dated Nov. 14, 2018, 11 pages. |
U.S. Office Action in related U.S. Appl. No. 15/274,693 dated Feb. 11, 2019, 13 pages. |
U.S. Office Action in related U.S. Appl. No. 15/274,693 dated Jul. 26, 2018, 14 pages. |
U.S. Office Action in related U.S. Appl. No. 15/216201 dated Jul. 20, 2018, 15 pages. |
U.S. Office Action in related U.S. Appl. No. 15/246,053 dated May 21, 2018, 14 pages. |
U.S. Office Action in related U.S. Appl. No. 15/246,053 dated Sep. 24, 2018, 14 pages. |
U.S. Office Action in related U.S. Appl. No. 15/370,084 dated Aug. 27, 2018, 14 pages. |
U.S. Office Action in related U.S. Appl. No. 15/370,084 dated Feb. 4, 2019, 9 pages. |
U.S. Office Action in related U.S. Appl. No. 15/380,450 dated Aug. 27, 2018, 19 pages. |
U.S. Office Action in related U.S. Appl. No. 15/380,450 dated Jan. 23, 2019, 21 pages. |
U.S. Office Action in related U.S. Appl. No. 15/380,450 dated Nov. 2, 2018, 19 pages. |
U.S. Office Action in related U.S. Appl. No. 15/380,379 dated Jul. 19, 2018, 9 pages. |
U.S. Office Action in related U.S. Appl. No. 15/381,567 dated Nov. 2, 2018, 17 pages. |
U.S. Office Action in related U.S. Appl. No. 15/383,771 dated Aug. 3, 2018, 12 pages. |
U.S. Office Action in related U.S. Appl. No. 15/383,771 dated Jan. 23, 2019, 14 pages. |
Schumacher, “An effective way to bring SAP Security Notes under control,” Virtual Forge GmbH, Feb. 2017, https://blog.virtualforge.com/en/an-effective-way-to-bring-sap-security-notes-under-control, 4 pages. |
Non-Final Office Action issued in U.S. Appl. No. 15/274,569 dated Mar. 22, 2019, 11 pages. |
Office Action issued in U.S. Appl. No. 15/847,478, dated Aug. 6, 2019, 36 pages. |
Office Action issued in U.S. Appl. No. 15/216,046 dated Aug. 21, 2019, 23 pages. |
Final Office Action issued in U.S. Appl. No. 15/381,567 dated May 22, 2019, 28 pages. |
Non-Final Office Action issued in U.S. Appl. No. 15/216,046 dated Apr. 29, 2019, 23 pages. |
Non-Final Office Action issued in U.S. Appl. No. 15/246,053 dated May 17, 2019, 28 pages. |
Non-Final Office Action issued in U.S. Appl. No. 15/639,863 dated Jun. 24, 2019, 37 pages. |
U.S. Office Action in related U.S. Appl. No. 15/383,771 dated Jul. 5, 2019, 16 pages. |
Number | Date | Country | |
---|---|---|---|
20180063167 A1 | Mar 2018 | US |