密码结构感知的变分量子密码分析：一种可逆的公开诊断框架
Cipher-Structure-Aware Variational Quantum Cryptanalysis: A Reversible Public-Diagnostic Framework
- Henan University（河南大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
提出密码结构感知的变分量子框架，利用混合DDT构造和可逆电路从公开数据恢复简化分组密码密钥，在16位简化AES上正确密钥排名第一。
AI中文摘要：
我们提出了一种密码结构感知的变分框架，用于从简化分组密码的公开数据中恢复密钥。公开的S盒差分约束和候选密钥相关的逆轮残差通过可逆的计算-相位-反计算电路转换为相位分离器。主要的分离器是一种混合DDT构造，它在残差细化之前结合了成对和同步多对差分约束。该构造由公开函数指定，不需要物理电路中的密钥索引相位表。我们形式化了公开实例模型，证明了结构诊断的单侧完备性，并在明确陈述的次高斯矩条件下推导了错误密钥诊断间隙的条件下尾界。这一统计陈述涉及诊断景观，而非有限深度QAOA优化器的收敛性。在十个独立的16位简化AES随机三对实例上，18层混合DDT调度达到平均公开一致密钥概率0.529785，数值范围从0.388892到0.770937，在每次运行中都将正确密钥排在首位，且观测到的最大错误密钥概率为0.008723。该结果是简化密码机制研究，而非对完整AES的攻击。
英文摘要：
We introduce a cipher-structure-aware variational framework for key recovery from public data in reduced block ciphers. Public S-box differential constraints and candidate-key-dependent inverse-round residuals are converted into phase separators through reversible compute-phase-uncompute circuits. The principal separator is a hybrid DDT construction that combines pairwise and synchronized multi-pair differential constraints before residual refinement. The construction is specified by public functions and does not require a key-indexed phase table in the physical circuit. We formalize the public-instance model, prove one-sided completeness of the structural diagnostics, and derive a conditional lower-tail bound for false-key diagnostic gaps under an explicitly stated sub-Gaussian moment condition. This statistical statement concerns the diagnostic landscape, not convergence of a finite-depth QAOA optimizer. On ten independent random three-pair instances of 16-bit simplified AES, an 18-layer Hybrid-DDT schedule reaches a mean public-consistent-key probability of 0.529785, with values from 0.388892 to 0.770937, ranks the correct key first in every run, and has largest observed false-key probability 0.008723. The result is a reduced-cipher mechanism study, not an attack on full AES.
