Capability-Adaptive Cryptanalysis with Reduced-Space Quantum Verification
2026-08-12 • Emerging Technologies
Emerging Technologies
AI summaryⓘ
The authors developed a method that combines classical cryptanalysis techniques with quantum verification to more efficiently find likely secret keys. They first use classical filters to shrink the large list of possible keys from thousands down to just a few dozen. Then, they apply a quantum search method called amplitude amplification to quickly verify the smaller group of key candidates. Their approach greatly reduces the quantum effort needed while still maintaining accuracy. This framework could help make hybrid quantum-classical cryptanalysis more practical.
cryptanalysislinear cryptanalysisdifferential cryptanalysisside-channel leakagequantum verificationamplitude amplificationGrover's algorithmcandidate-key spaceHamiltonian formulationhybrid cryptanalysis
Authors
Nivedita Dey, Mrityunjay Ghosh, Pranav Kaushal, Abhinab Khare, Amlan Chakrabarti
Abstract
Efficient integration of cryptanalytic evidence with quantum verification remains a fundamental challenge in hybrid classical-quantum cryptanalysis. This work presents a capability-adaptive cryptanalytic framework that unifies linear cryptanalysis, differential cryptanalysis, and side-channel leakage analysis within a common candidate-space reduction architecture, followed by reduced-space quantum verification through amplitude amplification. A formal mathematical model is developed for candidate-space construction, adaptive filtering, verification-space reduction, and complexity characterization, supported by the oretical results establishing the relationship between candidate-space contraction and quantum verification effort. A Hamiltonian formulation is further introduced to provide a physically realizable interpretation of the reduced-space verification process. Evaluation using statistically generated cryptanalytic observations demonstrates that the proposed framework reduces an initial candidate-key hypothesis space of 4096 candidates to an effective candidate space of 13 hypotheses, corresponding to an overall reduction of approximately 99.683%. Consequently, the Grover verification requirement decreases from 50 iterations to only 2 iterations, yielding an approximately 25-fold reduction in verification effort, while reduced-space amplitude amplification achieves a target-state success probability of approximately 94.53%. These results demonstrate that adaptive cryptanalytic filtering can substantially reduce quantum verification complexity while preserving cryptanalytic admissibility, providing a practical foundation for capability-aware hybrid cryptanalysis and reduced-space quantum search.