Research Article
Adaptive Noise Injection against Side-Channel Attacks on ARM Platform
@ARTICLE{10.4108/eai.25-1-2019.159346, author={Naiwei Liu and Wanyu Zang and Songqing Chen and Meng Yu and Ravi Sandhu}, title={Adaptive Noise Injection against Side-Channel Attacks on ARM Platform}, journal={EAI Endorsed Transactions on Security and Safety}, volume={6}, number={19}, publisher={EAI}, journal_a={SESA}, year={2019}, month={1}, keywords={system security, side-channel attacks, noise injection}, doi={10.4108/eai.25-1-2019.159346} }
- Naiwei Liu
Wanyu Zang
Songqing Chen
Meng Yu
Ravi Sandhu
Year: 2019
Adaptive Noise Injection against Side-Channel Attacks on ARM Platform
SESA
EAI
DOI: 10.4108/eai.25-1-2019.159346
Abstract
In recent years, research efforts have been made to develop safe and secure environments for ARM platform. The new ARMv8 architecture brought in security features by design. However, there are still some security problems with ARMv8. For example, on Cortex-A series, there are risks that the system is vulnerable to sidechannel attacks. One major category of side-channel attacks utilizes cache memory to obtain a victim’s secret information. In the cache based side-channel attacks, an attacker measures a sequence of cache operations to obtain a victim’s memory access information, deriving more sensitive information. The success of such attacks highly depends on accurate information about the victim’s cache accesses. In this paper, we describe an innovative approach to defend against side-channel attack on Cortex-A series chips. We also considered the side-channel attacks in the context of using TrustZone protection on ARM. Our adaptive noise injection can significantly reduce the bandwidth of side-channel while maintaining an affordable system overhead. The proposed defense mechanisms can be used on ARM Cortex-A architecture. Our experimental evaluation and theoretical analysis show the effectiveness and efficiency of our proposed defense.
Copyright © 2019 Naiwei Liu et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.