Research Article
mmFingerprint: A New Application Fingerprinting Technique via mmWave Sensing and Its Use in Rowhammer Detection
@INPROCEEDINGS{10.1007/978-3-031-51630-6_3, author={Sisheng Liang and Zhengxiong Li and Chenxu Jiang and Linke Guo and Zhenkai Zhang}, title={mmFingerprint: A New Application Fingerprinting Technique via mmWave Sensing and Its Use in Rowhammer Detection}, proceedings={Security and Privacy in Cyber-Physical Systems and Smart Vehicles. First EAI International Conference, SmartSP 2023, Chicago, USA, October 12-13, 2023, Proceedings}, proceedings_a={SMARTSP}, year={2024}, month={2}, keywords={Application fingerprinting mmWave sensing physical side-channel Rowhammer detection}, doi={10.1007/978-3-031-51630-6_3} }- Sisheng Liang
Zhengxiong Li
Chenxu Jiang
Linke Guo
Zhenkai Zhang
Year: 2024
mmFingerprint: A New Application Fingerprinting Technique via mmWave Sensing and Its Use in Rowhammer Detection
SMARTSP
Springer
DOI: 10.1007/978-3-031-51630-6_3
Abstract
Application fingerprinting is a technique broadly utilized in diverse fields such as cybersecurity, network management, and software development. We discover that the mechanical vibrations of cooling fans for both the CPU and power supply unit (PSU) in a system strongly correlate with the computational activities of running applications. In this study, we measure such vibrations with the help of mmWave sensing and design a new application fingerprinting approach namedmmFingerprint. We create a prototype ofmmFingerprintand demonstrate its effectiveness in distinguishing between various applications. To showcase the use ofmmFingerprintin cybersecurity for defensive purposes, we deploy it in a real computer system to detect the execution of reputable Rowhammer attack tools like TRRespass and Blacksmith. We find that the detection can reach a very high accuracy in practical scenarios. Specifically, the accuracy is 89% when exploiting CPU fan vibrations and nearly 100% when leveraging PSU fan vibrations.
