Malicious industrial internet of things node activity detection for connected plants
A method and apparatus for identifying malicious activity. At least one memory is configured to store historical communication data. At least one processor is configured to retrieve the historical communication data related to communications between a server and a plurality of clients in a system. The processor is further configured to cluster the historical communication data to group communications of the historical communication data. The processor is further configured to identify a plurality of patterns that indicate malicious activity based on the grouped communications. The processor is further configured to receive current communication data. The processor is further configured to determine whether the current communication data matches the one of the plurality of patterns. The processor is further configured to, responsive to a grouped element of the grouped communications matching the pattern, identifying a group of communications between the server and the plurality of clients as the malicious activity.
1. A method for identifying malicious activity in an IIoT ecosystem utilizing a unified architecture (UA) transport protocol comprising:
retrieving, by an intelligent security agent, historical communication data from a UA log related to communications between a UA server and a plurality of UA clients in the IIoT ecosystem;
clustering, by the intelligent security agent, the historical communication data to group communications of the historical communication data based on a combination of an unsupervised clustering algorithm and a supervised classifier algorithm;
identifying a plurality of patterns that indicate the malicious activity based on the grouped communications;
receiving current communication data;
determining whether the current communication data matches the one of the plurality of patterns; and
responsive to a grouped element of the grouped communications matching the pattern, identifying a group of communications between the UA server and the plurality of UA clients as the malicious activity.
2. The method of claim 1 , further comprising:
responsive to identifying the group of communications as the malicious activity, notifying a user of the system of the malicious activity.
3. The method of claim 1 , wherein the historical communication data is retrieved from a historian and includes log files associated with connection data and one or more UA server or plurality of UA clients.
4. The method of claim 1 , wherein the historical communication data is retrieved from a historian and includes alarm and security event data associated with the UA server.
5. The method of claim 1 , wherein the historical communication data is retrieved from one or more of the UA server or plurality of UA clients.
6. The method of claim 1 , wherein identifying the plurality of patterns for indicating the malicious activity based on the grouped communications comprises determining whether the grouped communication match any of a plurality of features.
7. The method of claim 1 , wherein the historical communication data is grouped according to a type of communication.
8. A system for identifying malicious activity in an IIoT ecosystem utilizing a unified architecture (UA) transport protocol comprising:
at least one memory configured to store historical communication data; and
at least one processor configured to:
retrieve, by an intelligent security agent, the historical communication data from a UA log related to communications between a UA server and a plurality of UA clients in the IIoT ecosystem;
cluster, by an intelligent security agent, the historical communication data to group communications of the historical communication data based on a combination of an unsupervised clustering algorithm and a supervised classifier algorithm;
identify a plurality of patterns that indicate malicious activity based on the grouped communications;
receive current communication data;
determine whether the current communication data matches the one of the plurality of patterns; and
responsive to a grouped element of the grouped communications matching the pattern, identifying a group of communications between the UA server and the plurality of UA clients as the malicious activity.
9. The system of claim 8 , responsive to identifying the group of communications as the malicious activity, notify a user of the system of the malicious activity.
10. The system of claim 8 , wherein the historical communication data is retrieved from a historian and includes log files associated with connection data and one or more UA server or plurality of UA clients.
11. The system of claim 8 , wherein the historical communication data is retrieved from a historian and includes alarm and security event data associated with the UA server.
12. The system of claim 8 , wherein the historical communication data is retrieved from one or more UA server or plurality of UA clients.
13. The system of claim 8 , wherein identifying the plurality of patterns for indicating the malicious activity based on the grouped communications comprises determining whether the grouped communication match any of a plurality of features.
14. The system of claim 8 , wherein the historical communication data is grouped according to a type of communication.
15. A non-transitory computer readable medium containing instructions that when executed cause at least one processor to identify malicious activity in an IIoT ecosystem utilizing a unified architecture (UA) transport protocol:
retrieve, by an intelligent security agent, historical communication data from a UA logs related to communications between a UA server and a plurality of UA clients in the IIoT ecosystem;
cluster, by an intelligent security agent, the historical communication data to group communications of the historical communication data based on a combination of an unsupervised clustering algorithm and a supervised classifier algorithm;
identify a plurality of patterns that indicate the malicious activity based on the grouped communications;
receive current communication data;
determine whether the current communication data matches the one of the plurality of patterns; and
responsive to a grouped element of the grouped communications matching the pattern, identifying a group of communications between the UA server and the plurality of UA clients as the malicious activity.
16. The non-transitory computer readable medium of claim 15 , responsive to identifying the group of communications as the malicious activity, notify a user of the system of the malicious activity.
17. The non-transitory computer readable medium of claim 15 , wherein the historical communication data is retrieved from a historian and includes log files associated with connection data and one or more UA server or plurality of UA clients.
18. The non-transitory computer readable medium of claim 15 , wherein the historical communication data is retrieved from a historian and includes alarm and security event data associated with the UA server.
19. The non-transitory computer readable medium of claim 15 , wherein the historical communication data is retrieved from one or more UA server or plurality of UA clients.
20. The non-transitory computer readable medium of claim 15 , wherein identifying the plurality of patterns for indicating the malicious activity based on the grouped communications comprises determining whether the grouped communication match any of a plurality of features.