JCSE, vol. 17, no. 1, pp.30-40, 2023

DOI: http://dx.doi.org/10.5626/JCSE.2023.17.1.30

A New Profiling-Based Side-Channel Attack on Graphics Processing Units

Xin Wang and Wei Zhang
Department of Electrical and Computer Engineering Virginia Commonwealth University, Richmond, VA, YSA Department of Computer Science and Engineering University of Louisville, Louisville, KY, USA

Abstract: Graphics processing units (GPUs) have been increasingly used to solve a range of compute-intensive and data-parallel scientific computing problems that can be perfectly parallelized for performance speedups. Particularly, GPUs have recently become popular to host the encryption/decryption algorithms due to its high-throughput computing capability. However, the security issues of moving the cryptographic algorithms onto GPUs have not been studied adequately. Consequently, with absence of any protection strategy, the potential vulnerabilities of GPUs to side-channel attacks (SCAs) may expose the confidential information with high risk. In this paper, we proposed a new profiling-assisted correlationbased side-channel attack (pacSCA) to demonstrate that ignoring security issues and naively moving security services onto GPUs can offer adversaries fatal vulnerabilities to thieve critical information. The results showed that the proposed SCA can rebuild the secure key of the AES-128 algorithm in less than 6 seconds, revealing the urgency of protecting GPUs against side-channel threats.

Keyword: Security; Correlation-based side-channel attack; Performance profiling; Graphics processing units (GPU)

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