REPQC：针对后量子密码学硬件加速器的逆向工程与后门植入
REPQC: Reverse Engineering and Backdooring Hardware Accelerators for Post-quantum Cryptography
AI总结：
本文提出REPQC，一种自动化逆向工程算法，用于在后量子密码硬件加速器中识别Keccak哈希操作并植入隐蔽硬件木马，以Dilithium为例，仅增加0.1%布局密度即可实现后门，且不影响性能。
摘要：
大量的研究工作致力于设计抗量子计算的密码算法，其动机十分明确：一旦强大的量子计算机问世，当前的密码标准将变得脆弱不堪。因此，我们需要新的后量子密码（PQC）算法，并且由于这类算法固有的复杂性，也需要在硬件上对其进行加速。在本文中，我们展示了PQC硬件加速器可能被位于芯片供应链中的两种不同对手植入后门。我们提出了REPQC，一种精密的逆向工程算法，可用于可靠地识别PQC加速器中的哈希运算（即Keccak），其位置作为寻找待泄露秘密信息的锚点。借助REPQC，对手接着以隐蔽的硬件特洛伊木马（HTH）形式插入恶意逻辑。以Dilithium作为研究案例，我们的结果表明，将加速器布局密度增加仅0.1%的HTH可以被插入，且对电路性能没有任何影响，功耗也仅有微小的增加。一个关键方面是，REPQC中的整个逆向工程过程是自动化的，随后的HTH插入也是自动化的，这使得对手能够探索多种HTH设计并识别出最合适的一种。
英文摘要：
Significant research efforts have been dedicated to designing cryptographic algorithms that are quantum-resistant. The motivation is clear: robust quantum computers, once available, will render current cryptographic standards vulnerable. Thus, we need new Post-Quantum Cryptography (PQC) algorithms, and, due to the inherent complexity of such algorithms, there is also a demand to accelerate them in hardware. In this paper, we show that PQC hardware accelerators can be backdoored by two different adversaries located in the chip supply chain. We propose REPQC, a sophisticated reverse engineering algorithm that can be employed to confidently identify hashing operations (i.e., Keccak) within the PQC accelerator - the location of which serves as an anchor for finding secret information to be leaked. Armed with REPQC, an adversary proceeds to insert malicious logic in the form of a stealthy Hardware Trojan Horse (HTH). Using Dilithium as a study case, our results demonstrate that HTHs that increase the accelerator's layout density by as little as 0.1\% can be inserted without any impact on the performance of the circuit and with a marginal increase in power consumption. An essential aspect is that the entire reverse engineering in REPQC is automated, and so is the HTH insertion that follows it, empowering adversaries to explore multiple HTH designs and identify the most suitable one.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
