Simulation Based Evaluation of Bit-Interaction Side-Channel Leakage on RISC-V Processor

Tamon Asano, T. Sugawara
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Abstract

Masking is a promising countermeasure against side-channel attack, and share slic- ing is its efficient software implementation that stores all the shares in a single register to exploit the parallelism of Boolean instructions. However, the security of share slicing relies on the assumption of bit-independent leakage from those instructions. Gao et al. recently discovered a violation causing a security degradation, called the bit-interaction leakage, by experimentally evaluating ARM processors. However, its causality remained open because of the blackbox inside the target processors. In this paper, we approach this problem with simulation-based side-channel leakage evaluation using a RISC-V processor. More specifically, we use Western Digital’s open-source SweRV EH1 core as a target plat- form and measure its side-channel traces by running logic simulation and counting the number of signal transitions in the synthesized ALU netlist. We successfully replicate the bit-interaction leakage from a shifter using the simulated traces. By exploiting the flexi- bility of simulation-based analysis, we positively verify Gao et al.’s hypothesis on how the shifter causes the leakage. Moreover, we discover a new bit-interaction leakage from an arithmetic adder caused by carry propagation. Finally, we discuss hardware and software countermeasures against the bit-interaction leakage.
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基于仿真的RISC-V处理器位交互侧信道泄漏评估
屏蔽是一种很有前途的对抗侧信道攻击的方法,共享分片是一种有效的软件实现,它将所有的共享存储在一个寄存器中,以利用布尔指令的并行性。然而,共享切片的安全性依赖于这些指令的位无关泄漏的假设。Gao等人最近通过实验评估ARM处理器,发现了一种导致安全性下降的违规行为,称为位交互泄漏。然而,由于目标处理器内部的黑盒子,它的因果关系仍然是开放的。在本文中,我们使用RISC-V处理器通过基于仿真的侧信道泄漏评估来解决这个问题。更具体地说,我们使用西部数据的开源SweRV EH1核心作为目标平台,并通过运行逻辑仿真和计算合成ALU网表中的信号转换次数来测量其侧通道走线。我们利用模拟走线成功地复制了移位器的位相互作用泄漏。通过利用基于仿真分析的灵活性,我们积极地验证了Gao等人关于换档器如何导致泄漏的假设。此外,我们还发现了由进位传播引起的算术加法器位交互泄漏。最后,我们讨论了防止位交互泄漏的硬件和软件对策。
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ARCH-COMP23 Category Report: Hybrid Systems Theorem Proving ARCH-COMP23 Category Report: Continuous and Hybrid Systems with Linear Continuous Dynamics ARCH-COMP23 Category Report: Continuous and Hybrid Systems with Nonlinear Dynamics ARCH-COMP23 Repeatability Evaluation Report ARCH-COMP23 Category Report: Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants
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