INCIDENT TRIAGE ENGINE

• US 20140223567A1
• Filed: 04/08/2014
• Published: 08/07/2014
• Est. Priority Date: 10/07/2011
• Status: Active Grant

• Current Assignee: Accenture Global Services Limited (Accenture PLC)
• Original Assignee: Accenture Global Services Limited (Accenture PLC)
• Inventors: HOWES, Joshua Z., NEGM, Walid, SOLDERITSCH, James J., JOTWANI, Ashish, CARVER, Matthew
• Granted Patent: US 9,369,481 B2
• Time in Patent Office: Days
• US Class Current: 726/25
• CPC Class Codes: G06F 21/554 involving event detection and direct action
• CPC Class Codes: G06F 21/577 Assessing vulnerabilities and evaluating computer system security
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: H04L 63/1416 Event detection, e.g. attack signature detection
• CPC Class Codes: H04L 63/1433 Vulnerability analysis

Abstract

An incident triage engine performs incident triage in a system by prioritizing responses to incidents within the system. One prioritization method may include receiving attributes of incidents and assets in the system, generating cumulative loss forecasts for the incidents, and prioritizing the responses to the incidents based on the cumulative loss forecasts for the incidents. Another prioritization method may include determining different arrangements of incidents within a response queue, calculating cumulative queue loss forecasts for the different arrangements of incidents within the response queue, and arranging the incidents in the response queue based on the arrangement of incidents that minimizes the total loss to the system over the resolution of all of the incidents present in the response queue.

Claims

1-5. -5. (canceled)

6. A method of prioritizing responses to a plurality of incidents within a system, the method being performed by a processor connected to a memory, the method comprising:

determining a plurality of different arrangements of the incidents within a response queue;

calculating, for each of the plurality of different arrangements of the incidents within the response queue, a cumulative queue loss forecast based on the arrangement of the incidents within the response queue; and

arranging the order of the incidents within the response queue according to the arrangement of the incidents within the response queue with the smallest cumulative queue loss forecast.

7. The method according to claim 6, wherein the plurality of different arrangements of the incidents within the response queue includes all possible arrangements of the incidents within the response queue.

8. The method according to claim 6, the method further comprising:

receiving, for each incident, a remediation time attribute based on the course of action associated with the incident, wherein;

each incident is associated with a course of action for resolving the incident;

the calculating further includes, for each of the incidents, calculating a loss forecast based on a total time to resolve the incident, the total time to resolve the incident being based on sum of the remediation time of the incident plus the remediation times of all of the incidents at an earlier position in the queue; and

the cumulative queue loss forecast is the sum of the loss forecasts calculated for each of the incidents.

9. The method according to claim 8, wherein machine learning is used to associate each incident with the course of action for resolving the incident.

10. The method according to claim 8, the method further comprising:

after arranging the order of the incidents within the response queue, executing the course of action associated with the incident arranged first in the response queue.

11. The method according to claim 8, wherein:

the receiving further includes receiving attributes of the system, attributes of assets within the system, and attributes of the incidents; and

the determining, calculating, arranging and receiving are continuously performed, and the calculating is performed based on most recently received attributes of the courses of action and most recently received attributes of the system.

12. The method according to claim 11, wherein:

the attributes of the system include an environmental factors attribute;

the attributes of the incidents include one or more of the following;

an incident morbidity attribute or an incident infectiousness attribute, where the incident morbidity attribute includes one or more of the following;

a confidentiality impact of the incident, an integrity impact of the incident, an availability impact of the incident, a progression speed of the incident, or an incubation time of the incident, and where the incident infectiousness attribute includes one or more of the following;

a potency of the incident, a transmission mode of the incident, or a latency period of the incident; and

the attributes of the assets include one or more of the following;

a value attribute or an immunity attribute, where the value attribute includes one or more of the following;

a confidentiality value of the asset, an integrity value of the asset, an availability value of the asset, or a substitutability value of the asset, and where the immunity attribute includes a susceptibility value of the asset.

13. The method according to claim 6, wherein the determining, calculating and arranging are repeated after one or more of the following:

an incident being added to the queue, or an incident being removed from the queue.

14. The method according to claim 6, wherein:

the system is a computer network;

the plurality of linked assets includes one or more of the following;

a database server, an application server, a firewall, an intrusion detection system, a router, a switch, a bridge, a repeater, or an end point; and

the incidents include one or more of the following;

a denial of service attack, a virus, a worm, a trojan horse, a backdoor, or a cookie tracker.

15-19. -19. (canceled)

20. A non-transitory computer-readable storage medium storing computer program instructions for prioritizing responses to a plurality of incidents within a system according to a method, the method comprising:

determining a plurality of different arrangements of the incidents within a response queue;

calculating, for each of the plurality of different arrangements of the incidents within the response queue, a cumulative queue loss forecast based on the arrangement of the incidents within the response queue; and

arranging the order of the incidents within the response queue according to the arrangement of the incidents within the response queue with the smallest cumulative queue loss forecast.

21. The computer-readable storage medium according to claim 20, wherein the plurality of different arrangements of the incidents within the response queue includes all possible arrangements of the incidents within the response queue.

22. The computer-readable storage medium according to claim 20, the method further comprising:

receiving, for each incident, a remediation time attribute based on the course of action associated with the incident, wherein;

each incident is associated with a course of action for resolving the incident;

the calculating further includes, for each of the incidents, calculating a loss forecast based on a total time to resolve the incident, the total time to resolve the incident being based on sum of the remediation time of the incident plus the remediation times of all of the incidents at an earlier position in the queue; and

the cumulative queue loss forecast is the sum of the loss forecasts calculated for each of the incidents.

23. The computer-readable storage medium according to claim 22, wherein machine learning is used to associate each incident with the course of action for resolving the incident.

24. The computer-readable storage medium according to claim 22, the method further comprising:

after arranging the order of the incidents within the response queue, executing the course of action associated with the incident arranged first in the response queue.

25. The computer-readable storage medium according to claim 22, wherein:

the receiving further includes receiving attributes of the system, attributes of assets within the system, and attributes of the incidents; and

the determining, calculating, arranging and receiving are continuously performed, and the calculating is performed based on most recently received attributes of the courses of action and most recently received attributes of the system.

26. The computer-readable storage medium according to claim 25, wherein:

the attributes of the system include an environmental factors attribute;

the attributes of the incidents include one or more of the following;

an incident morbidity attribute or an incident infectiousness attribute, where the incident morbidity attribute includes one or more of the following;

a confidentiality impact of the incident, an integrity impact of the incident, an availability impact of the incident, a progression speed of the incident, or an incubation time of the incident, and where the incident infectiousness attribute includes one or more of the following;

a potency of the incident, a transmission mode of the incident, or a latency period of the incident; and

the attributes of the assets include one or more of the following;

a value attribute or an immunity attribute, where the value attribute includes one or more of the following;

a confidentiality value of the asset, an integrity value of the asset, an availability value of the asset, or a substitutability value of the asset, and where the immunity attribute includes a susceptibility value of the asset.

27. The computer-readable storage medium according to claim 20, wherein the determining, calculating and arranging are repeated after one or more of the following:

an incident being added to the queue, or an incident being removed from the queue.

28. The computer-readable storage medium according to claim 20, wherein:

the system is a computer network;

the plurality of linked assets includes one or more of the following;

a database server, an application server, a firewall, an intrusion detection system, a router, a switch, a bridge, a repeater, or an end point; and

the incidents include one or more of the following;

a denial of service attack, a virus, a worm, a trojan horse, a backdoor, or a cookie tracker.

29-33. -33. (canceled)

34. A system including a processor and a memory, the memory storing instructions operable with the processor for prioritizing responses to a plurality of incidents within an environment, the instructions associated with a plurality of devices, the devices comprising:

a determining device that determines a plurality of different arrangements of the incidents within a response queue;

a calculating device that calculates, for each of the plurality of different arrangements of the incidents within the response queue, a cumulative queue loss forecast based on the arrangement of the incidents within the response queue; and

an arranging device that arranges the order of the incidents within the response queue according to the arrangement of the incidents within the response queue with the smallest cumulative queue loss forecast.

35. The system according to claim 34, wherein the plurality of different arrangements of the incidents within the response queue determined by the determining device includes all possible arrangements of the incidents within the response queue.

36. The system according to claim 34 further comprising:

a receiving device that receives, for each incident, a remediation time attribute based on the course of action associated with the incident; and

an associating device that associates each incident with a course of action for resolving the incident;

wherein;

the calculating further includes, for each of the incidents, calculating a loss forecast based on a total time to resolve the incident, the total time to resolve the incident being based on sum of the remediation time of the incident plus the remediation times of all of the incidents at an earlier position in the queue; and

the cumulative queue loss forecast is the sum of the loss forecasts calculated for each of the incidents.

37. The system according to claim 36, wherein machine learning is used to associate each incident with the course of action for resolving the incident.

38. The system according to claim 36 further comprising:

an executing device that, after arranging the order of the incidents within the response queue, executes the course of action associated with the incident arranged first in the response queue.

39. The system according to claim 36, wherein:

the receiving further includes receiving attributes of the environment, attributes of assets within the environment, and attributes of the incidents; and

the determining by the determining device, the calculating by the calculating device, the arranging by the arranging device and the receiving by the receiving device are continuously performed, and the calculating is performed based on most recently received attributes of the courses of action and most recently received attributes of the environment.

40. The system according to claim 39, wherein:

the attributes of the environment include an environmental factors attribute;

the attributes of the incidents include one or more of the following;

an incident morbidity attribute or an incident infectiousness attribute, where the incident morbidity attribute includes one or more of the following;

a confidentiality impact of the incident, an integrity impact of the incident, an availability impact of the incident, a progression speed of the incident, or an incubation time of the incident, and where the incident infectiousness attribute includes one or more of the following;

a potency of the incident, a transmission mode of the incident, or a latency period of the incident; and

the attributes of the assets include one or more of the following;

a value attribute or an immunity attribute, where the value attribute includes one or more of the following;

a confidentiality value of the asset, an integrity value of the asset, an availability value of the asset, or a substitutability value of the asset, and where the immunity attribute includes a susceptibility value of the asset.

41. The system according to claim 34, wherein determining by the determining device, the calculating by the calculating device, and the arranging by the arranging device are repeated after one or more of the following:

an incident being added to the queue, or an incident being removed from the queue.

42. The system according to claim 34, wherein:

the environment is a computer network;

the plurality of linked assets includes one or more of the following;

a database server, an application server, a firewall, an intrusion detection system, a router, a switch, a bridge, a repeater, or an end point; and

the incidents include one or more of the following;

a denial of service attack, a virus, a worm, a trojan horse, a backdoor, or a cookie tracker.