Test generation using reinforcement learning for delay-based side-channel analysis
Test generation using reinforcement learning for delay-based side-channel analysis
复制标题
使用强化学习进行基于延迟的侧信道分析的测试生成
DOI：
10.1145/3400302.3415710
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Mishra, Prabhat
中科院分区：
文献类型：
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作者：
Pan, Zhixin;Sheldon, Jennifer;Mishra, Prabhat
可靠性和可信度是设计用于各种应用的片上系统（SoC）的主导因素。恶意植入，如硬件木马，可能会导致意外的信息泄漏或系统故障。为了确保可信计算，开发高效的木马检测技术至关重要。虽然现有的基于延迟的侧信道分析是有前途的，但由于两个基本限制，它不是有效的：（i）与环境噪声和工艺变化相比，黄金设计和特洛伊插入设计之间的路径延迟的差异可以忽略不计。(ii)现有的方法依赖于手工制作的测试生成规则，并需要大量的模拟，使其不切实际的工业设计。在本文中，我们提出了一种新的测试生成方法，使用强化学习的延迟为基础的木马检测。本文做出了三个重要贡献：1）与现有的依赖于几个门的延迟差异的方法不同，我们提出的方法利用关键路径分析来生成测试向量，可以最大限度地提高侧通道灵敏度。2）据我们所知，我们的方法是第一次尝试应用强化学习来有效地生成测试，以检测特洛伊木马使用基于延迟的分析。3)我们的实验结果表明，与最先进的测试生成技术相比，我们的方法可以显着提高侧通道灵敏度（平均59%）和测试生成时间（平均17倍）。
Reliability and trustworthiness are dominant factors in designing System-on-Chips (SoCs) for a variety of applications. Malicious implants, such as hardware Trojans, can lead to undesired information leakage or system malfunction. To ensure trustworthy computing, it is critical to develop efficient Trojan detection techniques. While existing delay-based side-channel analysis is promising, it is not effective due to two fundamental limitations: (i) The difference in path delay between the golden design and Trojan inserted design is negligible compared with environmental noise and process variations. (ii) Existing approaches rely on manually crafted rules for test generation, and require a large number of simulations, making it impractical for industrial designs. In this paper, we propose a novel test generation method using reinforcement learning for delay-based Trojan detection. This paper makes three important contributions.1) Unlike existing methods that rely on the delay difference of a few gates, our proposed approach utilizes critical path analysis to generate test vectors that can maximize the side-channel sensitivity.2) To the best of our knowledge, our approach is the first attempt in applying reinforcement learning for efficient test generation to detect Trojans using delay-based analysis. 3) Our experimental results demonstrate that our method can significantly improve both side-channel sensitivity (59% on average) and test generation time (17x on average) compared to state-of-the-art test generation techniques.