TPE-Det: A Tamper-Proof External Detector via Hardware Traces Analysis Against IoT Malware

With the widespread use of Internet of Things (IoT) devices, malware detection has become a hot spot for both academic and industrial communities. A series of solutions based on system calls, system logs, or hardware performance counters achieve promising results. However, such internal monitors are easily tampered with, especially against adaptive adversaries. In addition, existing system log records typically exhibit substantial volume, resulting in data explosion problems. In this article, we present TPE-Det, a side-channel-based external monitor to cope with these issues. Specifically, TPE-Det leverages the serial peripheral interface bus to extract the on-chip traces and designs a recovery pipeline for operating logs. The advantages of this external monitor are adversary-unperceived and tamper-proof. The restored logs mainly include file operation commands, which are lightweight compared to complete records. Meanwhile, we deploy a series of machine learning models with respect to statistical, sequence, and graph features to identify malware. Empirical evaluation shows that our proposal has tamper-proof capability, high-detection accuracy, and low-time/space overhead compared to state-of-the-art methods.

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Publication Details

Journal
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Published
2024-11-01
DOI
https://doi.org/10.1109/tcad.2024.3444712
Citations
2
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
0.70

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article

TPE-Det: A Tamper-Proof External Detector via Hardware Traces Analysis Against IoT Malware

Zhaoxuan Li, Tingting Li, Fan Zhang, Ziming Zhao
2 citations
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Advanced Malware Detection Techniques
0.70
article

TPE-Det: A Tamper-Proof External Detector via Hardware Traces Analysis Against IoT Malware

Zhaoxuan Li, Tingting Li, Fan Zhang, Ziming Zhao
article en
2 citations

Abstract

With the widespread use of Internet of Things (IoT) devices, malware detection has become a hot spot for both academic and industrial communities. A series of solutions based on system calls, system logs, or hardware performance counters achieve promising results. However, such internal monitors are easily tampered with, especially against adaptive adversaries. In addition, existing system log records typically exhibit substantial volume, resulting in data explosion problems. In this article, we present TPE-Det, a side-channel-based external monitor to cope with these issues. Specifically, TPE-Det leverages the serial peripheral interface bus to extract the on-chip traces and designs a recovery pipeline for operating logs. The advantages of this external monitor are adversary-unperceived and tamper-proof. The restored logs mainly include file operation commands, which are lightweight compared to complete records. Meanwhile, we deploy a series of machine learning models with respect to statistical, sequence, and graph features to identify malware. Empirical evaluation shows that our proposal has tamper-proof capability, high-detection accuracy, and low-time/space overhead compared to state-of-the-art methods.

IEEE Transactions on Computer-Aided Design of Integrated Circuits and SystemsVol. 43(11)
Zhejiang University of Science and Technology (CN), Chinese Academy of Sciences (CN), Institute of Information Engineering (CN), University of Chinese Academy of Sciences (CN)
National Natural Science Foundation of China, Natural Science Foundation of Jiangsu Province
Openalex Percentile: Top 30%
Advanced Malware Detection Techniques
0.70
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TPE-Det: A Tamper-Proof External Detector via Hardware Traces Analysis Against IoT Malware — Zhaoxuan Li, Tingting Li, et al. · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2024) | TGRS Research Map | TGRS