Cyber-Physical Attack Detection via Synchronized Measurement Vectors
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Solution Overview
Problem
Contemporary cyber security systems struggle to detect cyber threats effectively, particularly replay attacks, as they may not appear unusual and require excessive resources, lacking dynamic threat modeling and integration in enterprise architectures.
Innovation Solution
The development of cyber security systems that use machine-learning classifiers and deep unsupervised learning to identify malicious sensor measurements by processing real-time data from cyber-physical systems, such as power grids, without prior knowledge of physical relationships, and can detect attacks in real-time with low latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If anomaly detection methods are used to detect cyber threats, then the system can identify unusual patterns, but replay attacks may go undetected because they do not appear peculiar or abnormal
Solution Approach 1:
The system performs preliminary actions by embedding unique identifiers and timestamps in sensor measurements before transmission. This preliminary marking allows the security system to later detect replay attacks by checking whether these identifiers and timestamps are valid and not from past executions, thereby solving the problem of replay attacks going undetected by anomaly detection alone.
Solution Approach 2:
The patent introduces an intermediary security layer that sits between the sensor measurements and the anomaly detection system. This intermediary layer validates measurements using physical laws and predefined criteria before they reach the anomaly detection system, preventing replay attacks from being misclassified as normal behavior.
2Reliability
If physical law detections are used to monitor system parameters, then the system can detect threats based on physical relationships, but parameters are not always known and detection may still be missed
Solution Approach 1:
The patent creates a universal security framework that can work with or without knowledge of specific physical relationships. The system uses a combination of anomaly detection, physical law validation, and predefined criteria checking that can adapt to different types of cyber-physical systems regardless of whether the specific physical parameters are known, thereby providing reliable detection without requiring complex system-specific knowledge.
Solution Approach 2:
The system changes the approach from relying on specific physical parameters to using broader validation criteria including timestamps, unique identifiers, and statistical anomalies. This parameter transformation allows the system to detect threats without needing detailed knowledge of the underlying physical relationships, reducing complexity while maintaining reliability.
3Reliability
If contemporary cyber security systems implement anomaly detection and physical law monitoring, then they can detect some threats, but they require excessive resources and lack dynamic threat modeling
Solution Approach 1:
The patent applies partial action by implementing a layered security approach where not all measurements undergo full validation. Instead, the system uses a combination of lightweight anomaly detection for all measurements and more resource-intensive physical law validation only when anomalies are detected or for critical measurements, thereby reducing overall resource consumption while maintaining detection reliability.
Solution Approach 2:
The system performs preliminary filtering and validation actions at the sensor level before data reaches the central security system. By pre-marking measurements with identifiers and timestamps, and performing initial validity checks at the source, the system reduces the computational burden on the central system while maintaining comprehensive threat detection capability.
4Speed
If cyber security systems are designed to detect threats in real-time, then they can respond quickly to attacks, but they are difficult to integrate in enterprise architectures
Solution Approach 1:
The patent designs a universal security framework that can be integrated into various enterprise architectures through standardized interfaces and protocols. The system uses common data formats and can work with different types of sensors and systems, allowing quick deployment and real-time threat detection without requiring custom integration work for each enterprise architecture, thereby achieving both speed and adaptability.
Data Source
AI summary
A cyber-security threat detection system and method stores physical data measurements from a cyber-physical system and extracts synchronized measurement vectors synchronized to one or more timing pulses. The system and method synthesize data integrity attacks in response to the physical data measurements and applies alternating parameterized linear and non-linear operations in response to the synthesized data integrity attacks. The synthesis renders optimized model parameters used to detect multiple cyber-attacks.