ScholarWorks@성균관대학교

초록

IoT devices are increasingly threatened by malware however, conventional electromagnetic (EM) side-channel detection methods have short effective range with increased complexity. This paper proposes a novel EM-based malware detection technique that addresses these limitations by focusing on the periodic behavior of the device’s clock frequency signal. The proposed approach monitors the processor’s clock emission for anomalous periodic patterns caused by malicious code, rather than scanning a broad spectrum of harmonics. This simplification enables real-time malware monitoring without additional hardware or intrusive instrumentation. The proposed method detects the presence of malware as well as identifies the malware type by analyzing the unique periodic signature it imprints on the clock signal. Experiments on an Arduino-based IoT device demonstrate that the technique achieves 100% detection accuracy across multiple malware variants and remains effective at distances up to 8 cm from the device, significantly outperforming prior EM analysis approaches in both range and practicality. These results suggest a lightweight and non-intrusive solution for enhancing IoT device security through clock frequency analysis.

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