Phy-Ids

Yan, Wenqing; Hylamia, Sam; Voigt, Thiemo; Rohner, Christian

doi:10.1145/3396870.3400010

Cited by 6 publications

(1 citation statement)

References 7 publications

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“…Intrusion and anomaly detection approaches were proposed for IoT environments to detect attacks using an attack signature [16] or by learning a pattern of legitimate system activities [17]. These solutions are divided into three parts: acquisition, analysis and alert.…”

Section: B Mitigationmentioning

confidence: 99%

A Lightweight Intrusion Detection System against IoT Memory Corruption Attacks

Bouazzati,

Tessier,

Tanguy

et al. 2023

2023 26th International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS)

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Attacks against internet-of-things (IoT) end-devices represent a significant threat since their wireless communication capabilities provide a potential attack entry point. To address this threat, we demonstrate the use of hardware performance counters (HPCs) in a host-based intrusion detection system (HIDS). The counter-based monitors are customized to support IoT enddevices which use low data rate GHz and sub-GHz protocols. Our solution implements a hardware unit that performs data tracing for a 32-bit RISC-V based wireless connectivity unit. The unit can detect ongoing remote attacks in real time. We demonstrate the effectiveness of our system by detecting a packet injection exploit. Our FPGA implementation of HIDS has a logic overhead of about 6% and design frequency penalty of less than 1% for a RISC-V processor.

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Section: B Mitigationmentioning

confidence: 99%