嵌入式硬件轻量级虚拟化环境中的后量子密码基准测试

中文摘要 AI 辅助

后量子密码（PQC）正在被部署，而嵌入式系统日益采用轻量级虚拟化来实现工作负载隔离和安全。这两种趋势都改变了性能特征，然而它们之间的相互作用尚未被充分理解。为解决这一问题，我们提出了一项在共享软件栈下、三种执行环境中对嵌入式级ARM硬件上的PQC原语进行的测量研究：原生执行、Docker容器以及运行在QEMU下的Unikraft单内核。我们对五个签名和五个密钥封装机制家族进行了基准测试，并作为比较，各测试了两个经典算法。我们使用不同的参数集对总共约70种配置进行了评估，测量了每次操作的执行时间、内存和能量。为了更好地评估对应用程序的影响，我们评估了TLS 1.3密码套件组合。我们发现，对于原语计算，容器开销可忽略不计，而单内核开销取决于算法。对于大多数PQC家族，开销可忽略不计。在BIKE、HQC和MAYO中出现了中等开销（1.28-1.53），尤其是在Falcon签名中（17.8-19.2）。在所有环境中，每次操作的能量与执行时间密切相关。对于TLS握手，容器和单内核客户端每次握手需要更多的时间和能量，而一旦昂贵的后量子算法主导握手，所有三种环境趋于一致。在这些情况下，算法选择对每次握手能量的影响高达三个数量级，远远超过环境的影响。总体而言，虚拟化成本与密码成本成反比：环境选择对于计算廉价、标准化的算法最为重要，而对于昂贵的方案，仅算法选择就主导了性能。

英文摘要

Post-Quantum Cryptography (PQC) is being deployed while embedded systems increasingly adopt lightweight virtualization for workload isolation and security. Both trends change performance characteristics, yet their interaction is not well understood. To address this, we present a measurement study of PQC primitives on embedded-class ARM hardware under three execution environments with a shared software stack: native execution, a Docker container, and a Unikraft unikernel running under QEMU. We benchmark five signature and five key encapsulation mechanism families, and, for comparison, two classical algorithms each. We evaluate them using different parameter sets for a total of around 70 configurations, measuring execution time, memory, and energy per operation. To better gauge the impact on applications, we evaluated TLS 1.3 cipher combinations. We find that container overhead is negligible for primitive computation, whereas unikernel overhead depends on the algorithm. For most PQC families the overhead is negligible. A moderate overhead (1.28-1.53) arises in BIKE, HQC, and MAYO, and, above all, in Falcon signing (17.8-19.2). Per-operation energy closely tracks execution time in all environments. For TLS handshakes, container and unikernel clients need more time and energy per handshake, while all three environments converge once expensive post-quantum algorithms dominate the handshake. In these cases algorithm choice affects per-handshake energy by up to three orders of magnitude, far outweighing the environment. Overall, virtualization cost is inversely related to cryptographic cost: environment choice matters most for computationally cheap, standardized algorithms, while for expensive schemes, algorithm choice alone dominates performance.

发表机构

• Technical University of Munich（慕尼黑工业大学）
• Fraunhofer AISEC（弗劳恩霍夫AISEC研究所）
• CarByte Engineering GmbH（CarByte工程有限公司）

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