EVENT CORRELATION ACROSS HETEROGENEOUS OPERATIONS

• US 20160301704A1
• Filed: 08/31/2015
• Published: 10/13/2016
• Est. Priority Date: 04/09/2015
• Status: Active Grant

• Current Assignee: Accenture Global Services Limited (Accenture PLC)
• Original Assignee: Accenture Global Services Limited (Accenture PLC)
• Inventors: Hassanzadeh, Amin, Modi, Shimon, Mulchandani, Shaan, Negm, Walid
• Granted Patent: US 9,742,788 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 21/64 Protecting data integrity, e.g. using checksums, certificates or signatures
• CPC Class Codes: H04L 63/0209 Architectural arrangements, e.g. perimeter networks or demilitarized zones
• CPC Class Codes: H04L 63/0227 Filtering policies mail message filtering H04L51/212
• CPC Class Codes: H04L 63/1408 by monitoring network traffic monitoring network traffic per se H04L43/00
• CPC Class Codes: H04L 63/1416 Event detection, e.g. attack signature detection
• CPC Class Codes: H04L 63/1433 Vulnerability analysis

Abstract

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for correlating domain activity data. First domain activity data from a first network domain and second domain activity data from a second network domain is received. The first domain activity data and the second domain activity data is filtered to remove irrelevant activity data, based on a first set of profile data for devices in the first network domain and a second set of profile data for devices in the second network domain. Unfiltered first and second domain activity data is aggregated. Aggregated unfiltered first and second domain activity data is correlated to determine an attack path for an attack that occurs across the first network domain and the second network domain, based on attack signatures and profiles associated with previously identified attacks. A visualization of the attack path is generated.

Claims

1. A computer-implemented method for correlating domain activity data, the method being executed by one or more processors and comprising:

receiving first domain activity data from a first network domain and second domain activity data from a second network domain, the first domain activity data and the second domain activity data including events, alerts, or both from the respective first and second network domains;

filtering the first domain activity data and the second domain activity data to remove irrelevant activity data, based on a first set of profile data for devices in the first network domain and a second set of profile data for devices in the second network domain;

aggregating unfiltered first domain activity data and unfiltered second domain activity data;

correlating aggregated unfiltered first domain activity data and unfiltered second domain activity data to determine an attack path for an attack that occurs across the first network domain and the second network domain, based on attack signatures and profiles associated with previously identified attacks; and

generating a visualization of the attack path.

2. The method of claim 1, wherein the first domain activity data, the second domain activity data, or both, includes log data provided by one or more security sensors.

3. The method of claim 1, wherein the first network domain is an information technology network domain and the second network domain is an operational technology network domain.

4. The method of claim 1, wherein the filtering comprises:

determining, for each event or alert, a corresponding attack and a corresponding target;

determining, based on profile data for the corresponding target, that the attack on the target is rendered unsuccessful; and

filtering the corresponding event or alert.

5. The method of claim 4, wherein the filtering comprises:

for each unfiltered event or alert, dynamically retrieving current status information about the corresponding target;

determining, based the current status information about the corresponding target, that the attack on the target is rendered unsuccessful; and

filtering the corresponding event or alert.

6. The method of claim 1, wherein the aggregating comprises determining that two or more alerts were generated in response to detecting a same packet, and combining the alerts into a meta-alert.

7. The method of claim 6, wherein the aggregating comprises determining that two or more alerts, meta-alerts, or both, are associated with a same attack or have similar characteristics, and combining the alerts, meta-alerts, or both.

8. The method of claim 7, wherein the aggregating is performed when the two or more alerts, meta-alerts, or both have timestamps within a threshold similarity value and include the same destination address, the same source address, or both.

9. The method of claim 1, wherein the correlating comprises:

labeling the aggregated unfiltered first domain activity data and unfiltered second domain activity data to identify two or more alerts, meta-alerts, or both that are associated with a particular attacker;

linking the activity data that is labeled as being associated with the particular attacker to identify a chain of two or more alerts, meta-alerts, or both; and

determining the attack path that occurs across the first network domain and the second network domain, including determining a series of communications between one or more devices in the first network domain and one or more devices in the second network domain.

10. The method of claim 1, wherein two or more alerts, meta-alerts, or both are linked when the alerts or meta-alerts have timestamp values within a time threshold value.

11. The method of claim 1, further comprising:

based on filtered first domain activity data and filtered second domain activity data, determining and storing filtered data associated with unsuccessful attacks; and

based on aggregated unfiltered first domain activity data and unfiltered second domain activity data, determining and storing data associated with targets and attackers;

wherein the attack signatures and profiles are based on the filtered data associated with unsuccessful attacks and on the data associated with targets and attackers.

12. The method of claim 11, wherein the data associated with targets and attackers includes references to devices that are targets of attacks, and references to addresses of attackers.

13. The method of claim 1, further comprising:

receiving data associated with the attack path;

in response to receiving the data associated with the attack path, determining an impact of the attack on the first network domain and on the second network domain; and

providing an appropriate course of action for the first network domain and the second network domain.

14. The method of claim 1, further comprising:

correlating aggregated unfiltered first domain activity data and unfiltered second domain activity data to determine multiple attack paths;

for each of the attack paths, determining an impact of the attack on the first network domain and on the second network domain; and

ranking each of the multiple attack paths, based on the impact of the respective attack.

15. A system, comprising:

one or more processors; and

a computer-readable storage device coupled to the one or more processors and having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations for correlating domain activity data, the operations comprising;

receiving first domain activity data from a first network domain and second domain activity data from a second network domain, the first domain activity data and the second domain activity data including events, alerts, or both from the respective first and second network domains;

filtering the first domain activity data and the second domain activity data to remove irrelevant activity data, based on a first set of profile data for devices in the first network domain and a second set of profile data for devices in the second network domain;

aggregating unfiltered first domain activity data and unfiltered second domain activity data;

correlating aggregated unfiltered first domain activity data and unfiltered second domain activity data to determine an attack path for an attack that occurs across the first network domain and the second network domain, based on attack signatures and profiles associated with previously identified attacks; and

generating a visualization of the attack path.

16. The system of claim 15, wherein the correlating comprises:

labeling the aggregated unfiltered first domain activity data and unfiltered second domain activity data to identify two or more alerts, meta-alerts, or both that are associated with a particular attacker;

linking the activity data that is labeled as being associated with the particular attacker to identify a chain of two or more alerts, meta-alerts, or both; and

determining the attack path that occurs across the first network domain and the second network domain, including determining a series of communications between one or more devices in the first network domain and one or more devices in the second network domain.

17. The system of claim 15, the operations further comprising:

based on filtered first domain activity data and filtered second domain activity data, determining and storing filtered data associated with unsuccessful attacks; and

based on aggregated unfiltered first domain activity data and unfiltered second domain activity data, determining and storing data associated with targets and attackers;

wherein the attack signatures and profiles are based on the filtered data associated with unsuccessful attacks and on the data associated with targets and attackers.

18. The system of claim 15, the operations further comprising:

receiving data associated with the attack path;

in response to receiving the data associated with the attack path, determining an impact of the attack on the first network domain and on the second network domain; and

providing an appropriate course of action for the first network domain and the second network domain.

19. The system of claim 15, the operations further comprising:

correlating aggregated unfiltered first domain activity data and unfiltered second domain activity data to determine multiple attack paths;

for each of the attack paths, determining an impact of the attack on the first network domain and on the second network domain; and

ranking each of the multiple attack paths, based on the impact of the respective attack.

20. A non-transitory computer-readable storage medium coupled to one or more processors and having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations for correlating domain activity data, the operations comprising:

receiving first domain activity data from a first network domain and second domain activity data from a second network domain, the first domain activity data and the second domain activity data including events, alerts, or both from the respective first and second network domains;

filtering the first domain activity data and the second domain activity data to remove irrelevant activity data, based on a first set of profile data for devices in the first network domain and a second set of profile data for devices in the second network domain;

aggregating unfiltered first domain activity data and unfiltered second domain activity data;

correlating aggregated unfiltered first domain activity data and unfiltered second domain activity data to determine an attack path for an attack that occurs across the first network domain and the second network domain, based on attack signatures and profiles associated with previously identified attacks; and

generating a visualization of the attack path.