A Theoretical Study of Hardware Performance Counters-Based Malware Detection

• Published in: IEEE transactions on information forensics and security Vol. 15; pp. 512 - 525
• Main Authors: Basu, Kanad, Krishnamurthy, Prashanth, Khorrami, Farshad, Karri, Ramesh
• Format: Journal Article
• Language: English
• Published: New York IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Anti-virus software; code execution; code integrity verification; Computer viruses; control flow graph (CFG); cyber security; Cybersecurity; Hardware; Hardware performance counter (HPC); Malware; Monitoring; Program processors; Rootkit; Sampling; Security; Software
• ISSN: 1556-6013; 1556-6021
• DOI: 10.1109/TIFS.2019.2924549

Malware can range from simple adware to stealthy kernel control-flow modifying rootkits. Although anti-virus software is popular, an ongoing cat-and-mouse cycle of anti-virus development and malware that thwarts the anti-virus has ensued. More recently, trusted hardware-based malware detection techniques are being developed on the premise that it is easier to bypass software-based defenses than hardware-based counterparts. One such approach is the use of hardware performance counters (HPCs) to detect malware for Linux and Android platforms. This paper, for the first time, presents an analytical framework to investigate the security provided by HPC-based malware detection techniques. The HPC readings are periodically monitored over the duration of the program execution for comparison with a golden HPC reading. We develop a mathematical framework to investigate the probability of malware detection, when HPCs are monitored at a pre-determined sampling interval. In other words, given a program, a set of HPCs, and a sampling rate, the framework can be employed to analyze the probability of malware detection.