Workspace Orchestration Log Discrepancy Detection
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Solution Overview
Problem
Current systems lack effective methods for detecting security attacks, particularly Person-in-the-Middle attacks, in Information Handling Systems (IHSs) using workspace orchestration logs.
Innovation Solution
A workspace orchestration server maintains logs of orchestration operations and compares them with logs from client IHSs and other servers, identifying discrepancies such as missing operations or different sequences to detect security attacks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If workspace orchestration logs are maintained and compared between server and client IHS, then security attack detection capability is improved, but system complexity increases
Solution Approach 1:
The system pre-establishes expected log patterns, sequences, and formats for workspace orchestration operations. By having the correct log structure predefined on the server side, the system can efficiently compare client logs against these expectations without requiring complex real-time analysis algorithms, thus improving detection capability while limiting complexity growth.
Solution Approach 2:
The server maintains a reference copy of expected workspace orchestration logs and compares them against client-submitted logs. This copying approach allows for straightforward discrepancy identification without requiring the server to reconstruct or re-execute orchestration sequences, simplifying the detection mechanism while maintaining high reliability.
2Measurement precision
If log comparison methods are implemented to detect discrepancies, then security monitoring accuracy is improved, but processing time increases
Solution Approach 1:
The system extracts and compares only critical log elements such as orchestration operation sequences, timestamps, and key state transitions. By focusing on essential discrepancies rather than analyzing entire log files in detail, the system achieves high monitoring accuracy for security threats while minimizing processing time overhead.
Solution Approach 2:
The comparison mechanism changes parameters by focusing on specific log attributes (sequence numbers, operation types, timing intervals) rather than performing full log content analysis. This selective parameter comparison maintains high detection accuracy for security anomalies while significantly reducing computational processing time.
Data Source
AI summary
Systems and methods for detecting security attacks using workspace orchestration logs are described. In some embodiments, a workspace orchestration server may include a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, may cause the server to: maintain a first workspace orchestration log, receive a second workspace orchestration log from a client Information Handling System (IHS), and identify the security attack, at least in part, in response to a discrepancy between the first and second workspace orchestration logs.


