ThermalAttackNet: Are CNNs Making It Easy to Perform Temperature Side-Channel Attack in Mobile Edge Devices?
Open Access
- 31 May 2021
- journal article
- research article
- Published by MDPI AG in Future Internet
- Vol. 13 (6), 146
- https://doi.org/10.3390/fi13060146
Abstract
Side-channel attacks remain a challenge to information flow control and security in mobile edge devices till this date. One such important security flaw could be exploited through temperature side-channel attacks, where heat dissipation and propagation from the processing cores are observed over time in order to deduce security flaws. In this paper, we study how computer vision-based convolutional neural networks (CNNs) could be used to exploit temperature (thermal) side-channel attack on different Linux governors in mobile edge device utilizing multi-processor system-on-chip (MPSoC). We also designed a power- and memory-efficient CNN model that is capable of performing thermal side-channel attack on the MPSoC and can be used by industry practitioners and academics as a benchmark to design methodologies to secure against such an attack in MPSoC.Keywords
Funding Information
- UK Engineering and Physical Sciences Research Council (EP/P017487/1, EP/R02572X/1, nosh/agri-tech-000001)
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