Apparatus and method for dynamic customization of cyber-security risk item rules

Abstract

This disclosure provides an apparatus and method for dynamic customization of cyber-security risk item rules. A method includes interacting with a user, by a risk manager system, to define a plurality of rules for risk items to be monitored among a plurality of connected devices. The method also includes mapping each of the rules to a corresponding one or more of the connected devices by the risk manager system. The method further includes monitoring the connected devices according to the rules by the risk manager system. In addition, the method includes displaying an output based on the rules and a status of the connected devices by the risk manager system.

Description

TECHNICAL FIELD

This disclosure relates generally to network security. More specifically, this disclosure relates to an apparatus and method for dynamic customization of cyber-security risk item rules.

BACKGROUND

Processing facilities are often managed using industrial process control and automation systems. Conventional control and automation systems routinely include a variety of networked devices, such as servers, workstations, switches, routers, firewalls, safety systems, proprietary real-time controllers, and industrial field devices. Often times, this equipment comes from a number of different vendors. In industrial environments, cyber-security is of increasing concern, and unaddressed security vulnerabilities in any of these components could be exploited by attackers to disrupt operations or cause unsafe conditions in an industrial facility.

SUMMARY

This disclosure provides an apparatus and method for dynamic customization of cyber-security risk item rules.

A method includes interacting with a user, by a risk manager system, to define a plurality of rules for risk items to be monitored among a plurality of connected devices. The method also includes mapping each of the rules to a corresponding one or more of the connected devices by the risk manager system. The method further includes monitoring the connected devices according to the rules by the risk manager system. In addition, the method includes displaying an output based on the rules and a status of the connected devices by the risk manager system.

A risk manager system includes a display and a controller. The controller is configured to interact with a user to define a plurality of rules for risk items to be monitored among a plurality of connected devices. The controller is also configured to map each of the rules to a corresponding one or more of the connected devices by the risk manager system. The controller is further configured to monitor the connected devices according to the rules by the risk manager system. In addition, the controller is configured to display an output based on the rules and a status of the connected devices by the risk manager system.

A non-transitory machine-readable medium contains instructions that when executed cause one or more processors of a risk manager system to interact with a user to define a plurality of rules for risk items to be monitored among a plurality of connected devices. The medium also contains instructions that when executed cause the one or more processors of the risk manager system to map each of the rules to a corresponding one or more of the connected devices by the risk manager system. The medium further contains instructions that when executed cause the one or more processors of the risk manager system to monitor the connected devices according to the rules by the risk manager system. In addition, the medium contains instructions that when executed cause the one or more processors of the risk manager system to display an output based on the rules and a status of the connected devices by the risk manager system.

Other technical features may be readily apparent to one skilled in the art from the following Figures, descriptions, and claims.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of this disclosure, reference is now made to the following description, taken in conjunction with the accompanying drawings, in which:

FIG. 1 illustrates an example industrial process control and automation system according to this disclosure;

FIGS. 2A through 2H illustrate example graphical user interface mechanisms supporting dynamic customization of cyber-security risk item rules according to this disclosure; and

FIGS. 3 and 4 illustrate flowcharts of processes in accordance with disclosed embodiments.

DETAILED DESCRIPTION

The figures, discussed below, and the various embodiments used to describe the principles of the present invention in this document are by way of illustration only and should not be construed in any way to limit the scope of the invention. Those skilled in the art will understand that the principles of the invention may be implemented in any type of suitably arranged device or system.

FIG. 1 illustrates an example industrial process control and automation system 100 according to this disclosure. As shown in FIG. 1, the system 100 includes various components that facilitate production or processing of at least one product or other material. For instance, the system 100 is used here to facilitate control over components in one or multiple plants 101a-101n. Each plant 101a-101n represents one or more processing facilities (or one or more portions thereof), such as one or more manufacturing facilities for producing at least one product or other material. In general, each plant 101a-101n may implement one or more processes and can individually or collectively be referred to as a process system. A process system generally represents any system or portion thereof configured to process one or more products or other materials in some manner.

In FIG. 1, the system 100 is implemented using the Purdue model of process control. In the Purdue model, “Level 0” may include one or more sensors 102a and one or more actuators 102b. The sensors 102a and actuators 102b represent components in a process system that may perform any of a wide variety of functions. For example, the sensors 102a could measure a wide variety of characteristics in the process system, such as temperature, pressure, or flow rate. Also, the actuators 102b could alter a wide variety of characteristics in the process system. The sensors 102a and actuators 102b could represent any other or additional components in any suitable process system. Each of the sensors 102a includes any suitable structure for measuring one or more characteristics in a process system. Each of the actuators 102b includes any suitable structure for operating on or affecting one or more conditions in a process system.

At least one network 104 is coupled to the sensors 102a and actuators 102b. The network 104 facilitates interaction with the sensors 102a and actuators 102b. For example, the network 104 could transport measurement data from the sensors 102a and provide control signals to the actuators 102b. The network 104 could represent any suitable network or combination of networks. As particular examples, the network 104 could represent an Ethernet network, an electrical signal network (such as a HART or FOUNDATION FIELDBUS network), a pneumatic control signal network, or any other or additional type(s) of network(s).

In the Purdue model, “Level 1” may include one or more controllers 106, which are coupled to the network 104. Among other things, each controller 106 may use the measurements from one or more sensors 102a to control the operation of one or more actuators 102b. For example, a controller 106 could receive measurement data from one or more sensors 102a and use the measurement data to generate control signals for one or more actuators 102b. Each controller 106 includes any suitable structure for interacting with one or more sensors 102a and controlling one or more actuators 102b. Each controller 106 could, for example, represent a proportional-integral-derivative (PID) controller or a multivariable controller, such as a Robust Multivariable Predictive Control Technology (RMPCT) controller or other type of controller implementing model predictive control (MPC) or other advanced predictive control (APC). As a particular example, each controller 106 could represent a computing device running a real-time operating system.

Two networks 108 are coupled to the controllers 106. The networks 108 facilitate interaction with the controllers 106, such as by transporting data to and from the controllers 106. The networks 108 could represent any suitable networks or combination of networks. As a particular example, the networks 108 could represent a redundant pair of Ethernet networks, such as a FAULT TOLERANT ETHERNET (FTE) network from HONEYWELL INTERNATIONAL INC.

At least one switch/firewall 110 couples the networks 108 to two networks 112. The switch/firewall 110 may transport traffic from one network to another. The switch/firewall 110 may also block traffic on one network from reaching another network. The switch/firewall 110 includes any suitable structure for providing communication between networks, such as a HONEYWELL CONTROL FIREWALL (CF9) device. The networks 112 could represent any suitable networks, such as an FTE network.

In the Purdue model, “Level 2” may include one or more machine-level controllers 114 coupled to the networks 112. The machine-level controllers 114 perform various functions to support the operation and control of the controllers 106, sensors 102a, and actuators 102b, which could be associated with a particular piece of industrial equipment (such as a boiler or other machine). For example, the machine-level controllers 114 could log information collected or generated by the controllers 106, such as measurement data from the sensors 102a or control signals for the actuators 102b. The machine-level controllers 114 could also execute applications that control the operation of the controllers 106, thereby controlling the operation of the actuators 102b. In addition, the machine-level controllers 114 could provide secure access to the controllers 106. Each of the machine-level controllers 114 includes any suitable structure for providing access to, control of, or operations related to a machine or other individual piece of equipment. Each of the machine-level controllers 114 could, for example, represent a server computing device running a MICROSOFT WINDOWS operating system. Although not shown, different machine-level controllers 114 could be used to control different pieces of equipment in a process system (where each piece of equipment is associated with one or more controllers 106, sensors 102a, and actuators 102b).

One or more operator stations 116 are coupled to the networks 112. The operator stations 116 represent computing or communication devices providing user access to the machine-level controllers 114, which could then provide user access to the controllers 106 (and possibly the sensors 102a and actuators 102b). As particular examples, the operator stations 116 could allow users to review the operational history of the sensors 102a and actuators 102b using information collected by the controllers 106 and/or the machine-level controllers 114. The operator stations 116 could also allow the users to adjust the operation of the sensors 102a, actuators 102b, controllers 106, or machine-level controllers 114. In addition, the operator stations 116 could receive and display warnings, alerts, or other messages or displays generated by the controllers 106 or the machine-level controllers 114. Each of the operator stations 116 includes any suitable structure for supporting user access and control of one or more components in the system 100. Each of the operator stations 116 could, for example, represent a computing device running a MICROSOFT WINDOWS operating system.

At least one router/firewall 118 couples the networks 112 to two networks 120. The router/firewall 118 includes any suitable structure for providing communication between networks, such as a secure router or combination router/firewall. The networks 120 could represent any suitable networks, such as an FTE network.

In the Purdue model, “Level 3” may include one or more unit-level controllers 122 coupled to the networks 120. Each unit-level controller 122 is typically associated with a unit in a process system, which represents a collection of different machines operating together to implement at least part of a process. The unit-level controllers 122 perform various functions to support the operation and control of components in the lower levels. For example, the unit-level controllers 122 could log information collected or generated by the components in the lower levels, execute applications that control the components in the lower levels, and provide secure access to the components in the lower levels. Each of the unit-level controllers 122 includes any suitable structure for providing access to, control of, or operations related to one or more machines or other pieces of equipment in a process unit. Each of the unit-level controllers 122 could, for example, represent a server computing device running a MICROSOFT WINDOWS operating system. Although not shown, different unit-level controllers 122 could be used to control different units in a process system (where each unit is associated with one or more machine-level controllers 114, controllers 106, sensors 102a, and actuators 102b).

Access to the unit-level controllers 122 may be provided by one or more operator stations 124. Each of the operator stations 124 includes any suitable structure for supporting user access and control of one or more components in the system 100. Each of the operator stations 124 could, for example, represent a computing device running a MICROSOFT WINDOWS operating system.

At least one router/firewall 126 couples the networks 120 to two networks 128. The router/firewall 126 includes any suitable structure for providing communication between networks, such as a secure router or combination router/firewall. The networks 128 could represent any suitable networks, such as an FTE network.

In the Purdue model, “Level 4” may include one or more plant-level controllers 130 coupled to the networks 128. Each plant-level controller 130 is typically associated with one of the plants 101a-101n, which may include one or more process units that implement the same, similar, or different processes. The plant-level controllers 130 perform various functions to support the operation and control of components in the lower levels. As particular examples, the plant-level controller 130 could execute one or more manufacturing execution system (MES) applications, scheduling applications, or other or additional plant or process control applications. Each of the plant-level controllers 130 includes any suitable structure for providing access to, control of, or operations related to one or more process units in a process plant. Each of the plant-level controllers 130 could, for example, represent a server computing device running a MICROSOFT WINDOWS operating system.

Access to the plant-level controllers 130 may be provided by one or more operator stations 132. Each of the operator stations 132 includes any suitable structure for supporting user access and control of one or more components in the system 100. Each of the operator stations 132 could, for example, represent a computing device running a MICROSOFT WINDOWS operating system.

At least one router/firewall 134 couples the networks 128 to one or more networks 136. The router/firewall 134 includes any suitable structure for providing communication between networks, such as a secure router or combination router/firewall. The network 136 could represent any suitable network, such as an enterprise-wide Ethernet or other network or all or a portion of a larger network (such as the Internet).

In the Purdue model, “Level 5” may include one or more enterprise-level controllers 138 coupled to the network 136. Each enterprise-level controller 138 is typically able to perform planning operations for multiple plants 101a-101n and to control various aspects of the plants 101a-101n. The enterprise-level controllers 138 can also perform various functions to support the operation and control of components in the plants 101a-101n. As particular examples, the enterprise-level controller 138 could execute one or more order processing applications, enterprise resource planning (ERP) applications, advanced planning and scheduling (APS) applications, or any other or additional enterprise control applications. Each of the enterprise-level controllers 138 includes any suitable structure for providing access to, control of, or operations related to the control of one or more plants. Each of the enterprise-level controllers 138 could, for example, represent a server computing device running a MICROSOFT WINDOWS operating system. In this document, the term “enterprise” refers to an organization having one or more plants or other processing facilities to be managed. Note that if a single plant 101a is to be managed, the functionality of the enterprise-level controller 138 could be incorporated into the plant-level controller 130.

Access to the enterprise-level controllers 138 may be provided by one or more operator stations 140. Each of the operator stations 140 includes any suitable structure for supporting user access and control of one or more components in the system 100. Each of the operator stations 140 could, for example, represent a computing device running a MICROSOFT WINDOWS operating system.

Various levels of the Purdue model can include other components, such as one or more databases. The database(s) associated with each level could store any suitable information associated with that level or one or more other levels of the system 100. For example, a historian 141 can be coupled to the network 136. The historian 141 could represent a component that stores various information about the system 100. The historian 141 could, for instance, store information used during production scheduling and optimization. The historian 141 represents any suitable structure for storing and facilitating retrieval of information. Although shown as a single centralized component coupled to the network 136, the historian 141 could be located elsewhere in the system 100, or multiple historians could be distributed in different locations in the system 100.

In particular embodiments, the various controllers and operator stations in FIG. 1 may represent computing devices. For example, each of the controllers 106, 114, 122, 130, 138 could include one or more processing devices 142 and one or more memories 144 for storing instructions and data used, generated, or collected by the processing device(s) 142. Each of the controllers 106, 114, 122, 130, 138 could also include at least one network interface 146, such as one or more Ethernet interfaces or wireless transceivers. Also, each of the operator stations 116, 124, 132, 140 could include one or more processing devices 148 and one or more memories 150 for storing instructions and data used, generated, or collected by the processing device(s) 148. Each of the operator stations 116, 124, 132, 140 could also include at least one network interface 152, such as one or more Ethernet interfaces or wireless transceivers.

As noted above, cyber-security is of increasing concern with respect to industrial process control and automation systems. Unaddressed security vulnerabilities in any of the components in the system 100 could be exploited by attackers to disrupt operations or cause unsafe conditions in an industrial facility. However, in many instances, operators do not have a complete understanding or inventory of all equipment running at a particular industrial site. As a result, it is often difficult to quickly determine potential sources of risk to a control and automation system. Exposing the appropriate level of customization can be difficult. Many products offer customization options that are either too simplistic (not allowing sufficient flexibility) or too complex (requiring additional training or hiring external contractors to customize the solution).

Disclosed embodiments understand potential vulnerabilities in various systems, prioritize the vulnerabilities based on risk to an overall system, and guide a user to mitigate the vulnerabilities. Moreover, to be of value to a variety of users across different industries, disclosed embodiments are customizable since, for instance, a risk to a system that might be of little concern to one user might be critical to another user.

Disclosed embodiments provide parameterized rules, which helps to avoid the overly-complicated scenario where a user needs to write his or her own rule logic or use a complex logic building utility. The rules can be carefully matched to the risk items they represent to provide the appropriate level of flexibility.

Disclosed embodiments also provide an effective and intuitive interface for configuring these rules and their parameters. If presented in a traditional configuration screen, the configuration process can quickly become overwhelming. There is also often a need for supplemental documentation to explain the meaning of each parameter and how the parameters relate to one another. According to disclosed embodiments, configuration parameters are exposed in the context of a plain text explanation of what the rule will do. The configurable parameters can appear similar to hyperlinks within the text. A user can click on the values and modify them directly in place. This is a much simpler configuration experience and helps to avoid the need for supplemental documentation.

In various embodiments, this is accomplished (among other ways) using a risk manager 154 (also referred to as the risk manager system). Among other things, the risk manager 154 supports this technique for dynamic customization of cyber-security risk item rules. The risk manager 154 includes any suitable structure that supports automatic handling of cyber-security risk events. Here, the risk manager 154 includes one or more processing devices 156; one or more memories 158 for storing instructions and data used, generated, or collected by the processing device(s) 156; and at least one network interface 160. Each processing device 156 could represent a microprocessor, microcontroller, digital signal process, field programmable gate array, application specific integrated circuit, or discrete logic. Each memory 158 could represent a volatile or non-volatile storage and retrieval device, such as a random access memory or Flash memory. Each network interface 160 could represent an Ethernet interface, wireless transceiver, or other device facilitating external communication. The functionality of the risk manager 154 could be implemented using any suitable hardware or a combination of hardware and software/firmware instructions.

Although FIG. 1 illustrates one example of an industrial process control and automation system 100, various changes may be made to FIG. 1. For example, a control and automation system could include any number of sensors, actuators, controllers, servers, operator stations, networks, risk managers, and other components. Also, the makeup and arrangement of the system 100 in FIG. 1 is for illustration only. Components could be added, omitted, combined, or placed in any other suitable configuration according to particular needs. Further, particular functions have been described as being performed by particular components of the system 100. This is for illustration only. In general, control and automation systems are highly configurable and can be configured in any suitable manner according to particular needs. In addition, FIG. 1 illustrates an example environment in which the functions of the risk manager 154 can be used. This functionality can be used in any other suitable device or system.

FIGS. 2A through 2H illustrate example graphical user interface mechanisms supporting dynamic customization of cyber-security risk item rules according to this disclosure. In some embodiments, dynamic customization of cyber-security risk item rules involves the following steps. First, appropriate rules are defined for parameters/risk items to be monitored. These rules are mapped to individual risk items to be monitored. Second, a configuration text template can be defined. This could be done generically for a rule type. It could also be customized further for each individual risk item.

FIGS. 2A-2H show various example configurations that could be used to dynamically customize cyber-security risk item rules.

FIG. 2A illustrates a cyber security dashboard 201 in accordance with disclosed embodiments used, in this example, to illustrate risk item weights 202. The individual risk items 203, in this example, include various security types, with weighting parameter values for the system and various zones and elements, as depicted. Each risk item can have weighting parameters for device impact, zone impact, frequency impact, and event decay. In this example, note that risk item 203 for “AV-Present” is expanded to show sub-elements System and Zones 1-3, each having its own weighting parameters. The system can automatically generate the risk item rules using the user's input from the cyber security dashboard 201.

FIG. 2B illustrates another example of cyber security dashboard 201 in accordance with disclosed embodiments used, in this example, to illustrate risk item weights 202. The individual risk items 203, in this example, include various security types, with weighting parameter values for the system and various zones and elements, as depicted. Each risk item can have weighting parameters for device impact, zone impact, frequency impact, and event decay. In this example, note that risk item 203 for “AV-Present” is collapsed and shows with the weighting parameters of (now hidden) sub-elements System and Zones 1-3. The system can automatically generate the risk item rules using the user's input from the cyber security dashboard 201.

FIG. 2C illustrates a risk items rules user interface 205 in accordance with disclosed embodiments. In this example, a parameter-entry area is shown for string comparison 206, which has entries for a default value and a system value. This example also shows a simple selector for a frequency increase model 207, with selector buttons for a desired frequency increase curve. This example also shows a simple selector for an event decay model 208, with selector buttons for a desired event decay curve. This example also shows a data scaling entry area 209, which allows the user to define risk ranges and associated values for the risk item rules. The system can automatically generate the risk item rules using the user's input from the risk items rules user interface 205.

FIG. 2D illustrates a “reset to defaults” button 210 that can reset all custom settings to default. Similar reset buttons can be used for individual parameter items. Resets can be applied to just the current interface screen, can be applied only at the system level, or can be applied to all zones as well. Examples of such reset buttons are reset system settings, reset system and zone settings, reset all visible settings, and others.

FIG. 2E illustrates other user interfaces in accordance with disclosed embodiments, used to customize risk item rules as disclosed herein. This example shows a time window interface 220 for customizing risk item triggers by time, indicating that an alert should be triggered based on how many times an event happens in a given time period. This example also shows a frequency impact interface 221 that allows users to adjust to “impact” of a risk item based on the frequency it occurs. This example also shows a risk-aging interface 222 that allows a user to customize an alert based on an aging parameter, such as the age of an antivirus definition file. As an example, risk-aging interface 222 describes a rule in simple text, rather than requiring complicated tables or groups of configuration boxes. Each underlined part of this rule represents a configurable parameter of the rule. Clicking on the parameter could change it into an editable field (similar to the boxes shown in time window interface 220 and frequency impact interface 221).

FIG. 2F illustrates another example of cyber security dashboard 201 in accordance with disclosed embodiments used, in this example, to illustrate zone configuration 230. This interface is used to assign zones to specific sensors or devices. The system or user can start with default zone called “Unassigned,” as Zone 0. All devices not assigned to a zone automatically go into this zone. When a zone is created, it goes into the last available numerical slot (e.g., if Zones 1-3 exist, the new zone will be Zone 4). A user can take action on existing zones, such as renaming the zone, moving the zone up or down in the zone numbering, and deleting a zone. If a zone is deleted, all devices in that zone move into the “Unassigned” zone. Existing zone numbers after the deleted zone are shifted up one number as needed to ensure there are no “gaps” in the zone numbering.

FIG. 2G illustrates another example of cyber security dashboard 201 in accordance with disclosed embodiments used, in this example, to illustrate device configuration 231. This user interface allows the user to assign, for each device 232, a zone, a device type, and an IP address (or other network address).

FIG. 2H illustrates patch reports in accordance with disclosed embodiments used, in this example, to illustrate whether particular devices 241 (in rows) have been updated or patched on each of the corresponding systems 242 (in columns). In this example, a check mark is used to indicate that a device 241 has been fully updated or patched on the corresponding system. This user interface allows the user to assign, for each device 232, a zone, a device type, and an IP address (or other network address). This Figure also illustrates that highlighting can be used to indicate differences or “disagreement” in patches of a device on different systems or of different devices on a single system.

For example, if 75% of the nodes (devices on a system or systems for a device) agree on a patch, the system can highlight the 25% that “disagree” or are not updated in red (or in other appropriate color or means). Thus, checkboxes 243 and 244 could be highlighted to show that they “disagree” with the other 3 boxes for their respective devices.

As another example, if the “disagreement” is between 25% and 75%, then system can highlight the entire row in yellow (or in other appropriate color or means). Thus, all the checkboxes for device 245 can be highlighted.

Although FIGS. 2A through 2H illustrate examples of graphical user interface mechanisms supporting dynamic customization of cyber-security risk item rules, various changes may be made to FIGS. 2A through 2H. For example, FIGS. 2A through 2H illustrate the use of various input/output mechanisms (such as checkboxes, text boxes, hyperlinks, etc.). These are for illustration only, and other data input and/or data output mechanisms could be used. Also, the content and arrangement of each graphical user interface mechanism are for illustration only.

FIG. 3 illustrates a flowchart of a method 300 in accordance with disclosed embodiments, as can be performed, for example, by risk manager 154 or other device or controller (referred to as the “system” below).

The system identifies a plurality of connected devices that are vulnerable to cyber-security risks (305). These could be any of the devices or components as illustrated in FIG. 1, or others.

The system interacts with a user to define a plurality of rules for risk items to be monitored among the connected devices (310). Each rule can have one or more parameters. The rules can be displayed as a plain-text sentence in the context of a plain text explanation of what the rule will do. The configurable parameters can appear similar to hyperlinks within the text. A user can click on the values and modify them directly in place.

Non-limiting examples of rules include a String-Comparison rule that compares the collected value with a predefined string or set of strings. In such as case, parameters can include an output risk weight. The rule can be displayed to the user as “Alert with a value of $Risk if the condition is detected.”

Another example is a rule for date-scaling that compares the collected value (which is a formatted string containing a date) with the current date and returns a range of risk values depending on the difference between those dates. The parameters can include a minimum age value ($Age-Min), a maximum age value ($Age-Max), a minimum risk value ($Risk-Min), and a maximum risk value ($Risk-Max). The rule can be displayed to the user as “Alert if the age is greater than $Age-Min days. Start at $Risk-Min and increase to a maximum of $Risk-Max after $Age-Max days. Can convert $Age-Min and $Age-Max from milliseconds to days.”

Another example is a rule for string-comparison-scaling that compares the collected value (which is a string value) with the predefined values. As the value continues to match the predefined value, the risk value begins to increase. When the parameter begins to match the comparison value, the risk is 0 until it has been in that state for “Minimum age value.” Then the risk goes up to “Minimum risk value,” and scales up to “Maximum risk value” when it has been in that state for “Maximum age value.” It remains at “Maximum risk value” until the collected value changes. If the collected values change at any time, the timer is reset.

Another example is a rule for value-scaling that compares the collected value (which is a numeric value) with the defined value range. If it is less than the minimum value, the result is zero. If it is between the minimum and maximum values, the result is calculated based on its position and configured weights. If it is greater than the maximum value, the result is the maximum risk weight.

Another example is a rule for event-decay that compares the date/time the event occurred with the current date/time. Immediately after an event occurs it will have the maximum risk value. As the events ages without reoccurring, its risk weight will gradually decay until reaching 0 by the end of the event lifespan. If the event reoccurs sooner, the value will immediately go to the maximum risk weight.

The system maps each of the rules to a corresponding one or more of the connected devices (315).

The system monitors the connected devices according to the rules (320).

The system displays an output based on the rules and a status of the connected devices (325).

The system can also define and store a configuration text template corresponding to one or more of the rules (330). The configuration text template can be customized to each risk item.

FIG. 4 illustrates a flowchart of a method 400 in accordance with disclosed embodiments, as can be performed, for example, by risk manager 154 or other device or controller (referred to as the “system” below).

The system obtains information defining a rule, the rule identifying a cyber-security risk to a computing device in an industrial process control and automation system (405). These could be any of the devices or components as illustrated in FIG. 1, or others.

The system displays a textual description describing the rule to a user (410), the textual description including a selectable configuration parameter associated with the rule. The selectable configuration parameter can be displayed as a hyperlink within the textual description. The textual description can describe what the rule will do. Each rule can be associated with at least one physical device.

The system receives the user's selection of the configuration parameter (415).

In response to receiving the user's selection of the configuration parameter, the system receives a value associated with the configuration parameter from the user (420). The value associated with the configuration parameter can be received through an input box that is displayed proximate to the configuration parameter.

The system can displays an output based on the configuration parameter and the received value (425).

The system can also define and store a rule corresponding to the configuration parameter and received value (430). In this way, the system has enabled the user to intuitively “complete” the rule for the risk manager by entering the values for the configuration parameters to be used in applying the rule.

Note that the risk manager 154 and/or the graphical user interface mechanism for dynamically customizing cyber-security risk item rules could use or operate in conjunction with any combination or all of various features described in the following previously-filed and concurrently-filed patent applications (all of which are hereby incorporated by reference):

• • U.S. patent application Ser. No. 14/482,888 entitled “DYNAMIC QUANTIFICATION OF CYBER-SECURITY RISKS IN A CONTROL SYSTEM”;
  • U.S. Provisional Patent Application No. 62/036,920 entitled “ANALYZING CYBER-SECURITY RISKS IN AN INDUSTRIAL CONTROL ENVIRONMENT”;
  • U.S. Provisional Patent Application No. 62/113,075 entitled “RULES ENGINE FOR CONVERTING SYSTEM-RELATED CHARACTERISTICS AND EVENTS INTO CYBER-SECURITY RISK ASSESSMENT VALUES” and corresponding non-provisional U.S. patent application Ser. No. 14/871,695 of like title;
  • U.S. Provisional Patent Application No. 62/113,221 entitled “NOTIFICATION SUBSYSTEM FOR GENERATING CONSOLIDATED, FILTERED, AND RELEVANT SECURITY RISK-BASED NOTIFICATIONS” and corresponding non-provisional U.S. patent application Ser. No. 14/871,521 of like title;
  • U.S. Provisional Patent Application No. 62/113,100 entitled “TECHNIQUE FOR USING INFRASTRUCTURE MONITORING SOFTWARE TO COLLECT CYBER-SECURITY RISK DATA” and corresponding non-provisional U.S. patent application Ser. No. 14/871,855 of like title;
  • U.S. Provisional Patent Application No. 62/113,186 entitled “INFRASTRUCTURE MONITORING TOOL FOR COLLECTING INDUSTRIAL PROCESS CONTROL AND AUTOMATION SYSTEM RISK DATA” and corresponding non-provisional U.S. patent application Ser. No. 14/871,732 of like title;
  • U.S. Provisional Patent Application No. 62/113,165 entitled “PATCH MONITORING AND ANALYSIS” and corresponding non-provisional U.S. patent application Ser. No. 14/871,921 of like title;
  • U.S. Provisional Patent Application No. 62/113,152 entitled “APPARATUS AND METHOD FOR AUTOMATIC HANDLING OF CYBER-SECURITY RISK EVENTS” and corresponding non-provisional U.S. patent application Ser. No. 14/871,503 of like title;
  • U.S. Provisional Patent Application No. 62/114,865 entitled “APPARATUS AND METHOD FOR PROVIDING POSSIBLE CAUSES, RECOMMENDED ACTIONS, AND POTENTIAL IMPACTS RELATED TO IDENTIFIED CYBER-SECURITY RISK ITEMS” and corresponding non-provisional U.S. patent application Ser. No. 14/871,814 of like title;
  • U.S. Provisional Patent Application No. 62/114,937 entitled “APPARATUS AND METHOD FOR TYING CYBER-SECURITY RISK ANALYSIS TO COMMON RISK METHODOLOGIES AND RISK LEVELS” and corresponding non-provisional U.S. patent application Ser. No. 14/871,136 of like title; and
  • U.S. Provisional Patent Application No. 62/116,245 entitled “RISK MANAGEMENT IN AN AIR-GAPPED ENVIRONMENT” and corresponding non-provisional U.S. patent application Ser. No. 14/871,547 of like title.

In some embodiments, various functions described in this patent document are implemented or supported by a computer program that is formed from computer readable program code and that is embodied in a computer readable medium. The phrase “computer readable program code” includes any type of computer code, including source code, object code, and executable code. The phrase “computer readable medium” includes any type of medium capable of being accessed by a computer, such as read only memory (ROM), random access memory (RAM), a hard disk drive, a compact disc (CD), a digital video disc (DVD), or any other type of memory. A “non-transitory” computer readable medium excludes wired, wireless, optical, or other communication links that transport transitory electrical or other signals. A non-transitory computer readable medium includes media where data can be permanently stored and media where data can be stored and later overwritten, such as a rewritable optical disc or an erasable memory device.

It may be advantageous to set forth definitions of certain words and phrases used throughout this patent document. The terms “application” and “program” refer to one or more computer programs, software components, sets of instructions, procedures, functions, objects, classes, instances, related data, or a portion thereof adapted for implementation in a suitable computer code (including source code, object code, or executable code). The term “communicate,” as well as derivatives thereof, encompasses both direct and indirect communication. The terms “include” and “comprise,” as well as derivatives thereof, mean inclusion without limitation. The term “or” is inclusive, meaning and/or. The phrase “associated with,” as well as derivatives thereof, may mean to include, be included within, interconnect with, contain, be contained within, connect to or with, couple to or with, be communicable with, cooperate with, interleave, juxtapose, be proximate to, be bound to or with, have, have a property of, have a relationship to or with, or the like. The phrase “at least one of,” when used with a list of items, means that different combinations of one or more of the listed items may be used, and only one item in the list may be needed. For example, “at least one of: A, B, and C” includes any of the following combinations: A, B, C, A and B, A and C, B and C, and A and B and C.

While this disclosure has described certain embodiments and generally associated methods, alterations and permutations of these embodiments and methods will be apparent to those skilled in the art. Accordingly, the above description of example embodiments 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, as defined by the following claims.

Claims

1. A method comprising: identifying by a risk manager system a plurality of risk items;interacting with a user, by the risk manager system, to solicit from the user one or more parameters associated with at least some of the plurality of risk items;automatically generating, by the risk manager system, a plurality of rules for the plurality of risk items to be monitored among a plurality of connected devices based at least in part on the one or more parameters entered by the user;mapping each of the rules to one or more of the connected devices by the risk manager system;monitoring the connected devices according to the rules by the risk manager system; anddisplaying an output based on the rules and a status of the connected devices by the risk manager system.

2. The method of claim 1, wherein each rule references one or more of the parameters, and each rule is displayed as a plain text explanation of what the rule will do with one or more parameters embedded in the plain text explanation.

3. The method of claim 1, wherein the risk manager system defines and stores a configuration text template corresponding to one or more of the rules.

4. The method of claim 1, wherein: the risk manager system identifies the plurality of connected devices; andat least some of the plurality of connected devices are vulnerable to cyber-security risks.

5. The method of claim 1, wherein at least one of the one or more parameters is accessible via a selectable hyperlink within a textual description of a rule.

6. The method of claim 1, wherein each rule identifies a cyber-security risk to a computing device in an industrial process control and automation system.

7. The method of claim 1, further comprising, for each rule: obtaining information defining the rule;presenting a textual description describing an effect of the rule to the user by the risk manager system, the textual description including a selectable field associated with a parameter of the rule; andin response to receiving the user's selection of the selectable field, presenting an editable field and receiving a value associated with the parameter of the rule from the user.

8. A risk manager system comprising: a display; anda controller configured to: identify a plurality of risk items;interact with a user to solicit from the user one or more parameters associated with at least some of the plurality of risk items;automatically generate a plurality of rules for the plurality of risk items to be monitored among a plurality of connected devices based at least in part on the one or more parameters entered by the user;map each of the rules to one or more of the connected devices by the risk manager system;monitor the connected devices according to the rules by the risk manager system; anddisplay an output based on the rules and a status of the connected devices by the risk manager system.

9. The risk manager system of claim 8, wherein: the controller is configured to display each rule as a plain text explanation of what the rule will do with one or more parameters embedded in the plain text explanation.

10. The risk manager system of claim 8, wherein the controller is configured to define and store a configuration text template corresponding to one or more of the rules.

11. The risk manager system of claim 8, wherein: the controller is configured to identify the plurality of connected devices; andat least some of the plurality of connected devices are vulnerable to cyber-security risks.

12. The risk manager system of claim 8, wherein: at least one of the one or more parameters is accessible via a selectable hyperlink within a textual description of a rule.

13. The risk manager system of claim 8, wherein each rule identifies a cybersecurity risk to a computing device in an industrial process control and automation system.

14. The risk manager system of claim 8, wherein the controller is further configured, for each rule, to: obtain information defining the rule;present a textual description describing an effect of the rule to the user by the risk manager system, the textual description including a selectable field associated with a parameter of the rule; andin response to receiving the user's selection of the selectable field, presenting an editable field and receive a value associated with the parameter of the rule from the user.

15. The risk manager system of claim 8, wherein the controller comprises one or more processors.

16. A non-transitory machine-readable medium containing instructions that when executed cause one or more processors of a risk manager system to: identify a plurality of risk items;interact with a user to solicit from the user one or more parameters associated with at least some of the plurality of risk items;automatically generate a plurality of rules for the plurality of risk items to be monitored among a plurality of connected devices based at least in part on the one or more parameters entered by the user;map each of the rules to one or more of the connected devices by the risk manager system;monitor the connected devices according to the rules by the risk manager system; anddisplay an output based on the rules and a status of the connected devices by the risk manager system.

17. The non-transitory machine-readable medium of claim 16, wherein: the medium further contains instructions that when executed cause the one or more processors of the risk manager system to display each rule as a plain text explanation of what the rule will do with one or more parameters embedded in the plain text explanation.

18. The non-transitory machine-readable medium of claim 16, wherein the medium further contains instructions that when executed cause the one or more processors of the risk manager system to define and store a configuration text template corresponding to one or more of the rules.

19. The non-transitory machine-readable medium of claim 16, wherein: at least one of the one or more parameters is accessible via a selectable hyperlink within a textual description of a rule.

20. The non-transitory machine-readable medium of claim 16, wherein each rule identifies a cyber-security risk to a computing device in an industrial process control and automation system.

21. The non-transitory machine-readable medium of claim 16, wherein the medium further contains instructions that when executed cause the one or more processors of the risk manager system to: obtain information defining the rule;present a textual description describing an effect of the rule to the user by the risk manager system, the textual description including a selectable field associated with a parameter of the rule; andin response to receiving the user's selection of the selectable field, presenting an editable field and receive a value associated with the parameter of the rule from the user.