High-Level Synthesis for side-channel defense

S. T. C. Konigsmark, Deming Chen, Martin D. F. Wong
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引用次数: 10

Abstract

The Internet of Things (IoT) and cloud computing rely on strong confidence in security of confidential or highly privacy sensitive data. Therefore, side-channel leakage is an important threat, but countermeasures require expert-level security knowledge for efficient application, limiting adoption. This work addresses this need by presenting the first High-Level Synthesis (HLS) flow with primary focus on side-channel leakage reduction. Minimal security annotation to the high-level C-code is sufficient to perform automatic analysis of security critical operations with corresponding insertion of countermeasures. Additionally, imbalanced branches are detected and corrected. For practicality, the flow can meet both resource and information leakage constraints. The presented flow is extensively evaluated on established HLS benchmarks and a general IoT benchmark. Under identical resource constraints, leakage is reduced between 32% and 72% compared to the reference. Under leakage target, the constraints are achieved with 31% to 81% less resource overhead.
高级合成的侧通道防御
物联网(IoT)和云计算依赖于对机密或高度隐私敏感数据的安全性的强烈信心。因此,侧信道泄漏是一个重要的威胁,但应对措施需要专家级的安全知识才能有效应用,限制了采用。这项工作通过提出第一个高水平合成(HLS)流来解决这一需求,主要侧重于减少侧通道泄漏。对高级c代码的最小安全注释足以执行安全关键操作的自动分析,并插入相应的对策。此外,不平衡的分支被检测和纠正。在实用性方面,该流程可以同时满足资源和信息泄漏的约束。所提出的流程在已建立的HLS基准和一般物联网基准上进行了广泛评估。在相同的资源限制下,与参考相比,泄漏减少了32%至72%。在达到泄漏目标的情况下,减少了31%到81%的资源开销。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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