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首页> 外文期刊>IEEE transactions on dependable and secure computing >Detecting Fault Injection Attacks Based on Compressed Sensing and Integer Linear Programming
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Detecting Fault Injection Attacks Based on Compressed Sensing and Integer Linear Programming

机译：基于压缩感知和整数线性规划的故障注入攻击检测

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摘要

Cryptographic ICs have been widely applied to numerous security-critical environments nowadays. Fault injection has become a serious attack on cryptographic IC, especially soft-errors or single event upsets (SEUs) by fine-resolution fault injection attacks. Detection and tamper evidence of these attacks become important. Traditional SEU diagnose methods usually require special sensors embedded into the circuits. However, these methods require non-trivial design and test effort, and usually just yield statistic results. In this paper, we formulate the detection fault injection attacks as a compressed sensing problem, due to sparsity of soft errors. Besides, due to the binary characteristic of the coefficient matrix and the variables, integer linear programming is adopted to reconstruct the soft error signals. Simulation results on a cryptographic IC demonstrate that the proposed method is capable to accurately detect the locations of soft-errors caused by fault injection attacks with negligible hardware overhead. The abnormal test output of scan-chains can be tamper evidence of the fault injection attacks.
机译：如今，加密IC已广泛应用于众多对安全性要求很高的环境。故障注入已成为对密码IC的严重攻击，尤其是通过精细分辨率的故障注入攻击对软错误或单事件扰动（SEU）的攻击。检测和篡改这些攻击的证据变得很重要。传统的SEU诊断方法通常需要在电路中嵌入特殊的传感器。但是，这些方法需要不平凡的设计和测试工作，并且通常只产生统计结果。在本文中，由于软错误的稀疏性，我们将检测故障注入攻击表述为压缩感知问题。此外，由于系数矩阵和变量的二进制特性，采用整数线性规划来重建软误差信号。加密IC上的仿真结果表明，该方法能够以可忽略的硬件开销准确地检测到由故障注入攻击引起的软错误的位置。扫描链的异常测试输出可能是故障注入攻击的篡改证据。

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