Program Behavior Modeling for Real-Time Anomaly Detection
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Solution Overview
Problem
Conventional approaches to software security often detect breaches after they occur, failing to prevent unanticipated or malicious program behavior due to a lack of real-time anomaly detection during normal operation.
Innovation Solution
A system that generates an acceptable behavior model by monitoring a program in a controlled environment, comparing operational sequences against this model to detect deviations and halt or flag unanticipated behavior, using instrumentation and a supervisor to enforce normal operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional approaches monitor for big picture anomalies such as unusual network traffic or CPU usage, then security breaches can be detected after they occur, but the detection is too late to prevent the security breach from happening
Solution Approach 1:
The system performs preliminary action by establishing an acceptable behavior model through static analysis before the program executes in the operational environment. This pre-established model enables real-time comparison during execution, allowing the system to detect deviations immediately rather than relying on post-breach log analysis. The supervisor component is also prepared in advance to enforce the model during runtime.
Solution Approach 2:
The patent introduces an intermediary mechanism (the supervisor and acceptable behavior model) that mediates between the program execution and security monitoring. Instead of directly monitoring big picture anomalies, the supervisor compares operational sequences against the pre-established acceptable behavior model, enabling timely detection of deviations that indicate security breaches.
2Reliability
If static analysis tools scan code to identify known vulnerability types, then known attacks such as SQL injections can be detected, but unanticipated or novel attacks cannot be detected
Solution Approach 1:
The system performs preliminary static analysis to establish an acceptable behavior model that captures the program's normal operational sequences. This model is not limited to known attack patterns but represents the program's expected behavior under various normal conditions. During runtime, any deviation from this model is detected, enabling the system to identify novel or unanticipated attacks that static analysis alone would miss.
Solution Approach 2:
The patent transitions from static vulnerability scanning to dynamic behavior monitoring. The acceptable behavior model captures the program's dynamic operational sequences, and the supervisor continuously compares runtime behavior against this model. This dynamic approach enables detection of both known and unknown attacks by focusing on behavioral deviations rather than pattern matching.
3Reliability
If the system compares operational sequences against the acceptable behavior model in real-time, then unanticipated malicious behavior can be detected and prevented, but the device complexity increases due to the supervisor and model comparison mechanisms
Solution Approach 1:
The patent extracts the security monitoring function into a separate supervisor component that operates independently from the program being monitored. The supervisor receives operational sequences from the program, compares them against the acceptable behavior model, and enforces security decisions. This separation reduces the complexity burden on the monitored program while maintaining high detection accuracy through dedicated monitoring infrastructure.
Data Source
AI summary
A program is executed in a first mode of operation in a controlled environment in accordance with normal operations without malicious behavior. An acceptable behavior model is generated based on a plurality of sequences of events that occur during the normal operation of the program. The acceptable behavior model is indicative of normal behavior of the program that occurs during the normal operation. Then the program is executed in a second mode of operation in an operational environment. An operational sequence of events (determined during the second mode of operation) is compared with the acceptable behavior model. When there is a match between the operational sequence of events and the acceptable behavior model, execution in the second mode of operation continues. When there is not a match between the operational sequence of events and the acceptable behavior model, execution in the second mode of operation is halted.