Abstract
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.
Original language | English (US) |
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Article number | 8744309 |
Pages (from-to) | 512-525 |
Number of pages | 14 |
Journal | IEEE Transactions on Information Forensics and Security |
Volume | 15 |
DOIs | |
State | Published - 2020 |
Keywords
- Hardware performance counter (HPC)
- code execution
- code integrity verification
- control flow graph (CFG)
- cyber security
- malware
ASJC Scopus subject areas
- Safety, Risk, Reliability and Quality
- Computer Networks and Communications