Timing-based anomaly detection in embedded systems

Recent research has demonstrated that many systems are vulnerable to numerous types of malicious activity. As the pervasiveness of embedded systems with network connectivity continues to increase, embedded systems security has become a critical challenge. However, most existing techniques for detecting malware utilize software-based methods that incur significant performance overheads that are often not feasible in embedded systems. In this paper, we present an overview of a novel method for non-intrusively detecting malware in embedded system. The proposed technique utilizes timing requirements to improve detection performance and provide increased resilience to mimicry attacks.