Towards Quantum Resilience: Data-Driven Migration Strategy Design
Nahid Aliyev, Ozan Cetin, Emil Huseynov
TL;DR
The paper tackles the quantum threat to classical cryptography by proposing a data-driven PQC migration framework (QTSRF) that maps system characteristics to mitigation strategies. It builds a synthetic, domain-informed dataset and trains both Decision Tree and Random Forest classifiers to predict suitable migration actions, achieving 96% accuracy with the RF model. A formal risk function R(s,t) = V(m,k) · S(d) · P(t) underpins the analytical framework, linking cryptographic strength, data sensitivity, and projected quantum capability to decision making. The work offers actionable, transparent guidance for cryptographic modernization, emphasizing interpretability, robustness, and scalability, with clear indications of feature importance and practical deployment considerations.
Abstract
The advancements in quantum computing are a threat to classical cryptographic systems. The traditional cryptographic methods that utilize factorization-based or discrete-logarithm-based algorithms, such as RSA and ECC, are some of these. This paper thoroughly investigates the vulnerabilities of traditional cryptographic methods against quantum attacks and provides a decision-support framework to help organizations in recommending mitigation plans and determining appropriate transition strategies to post-quantum cryptography. A semi-synthetic dataset, consisting of key features such as key size, network complexity, and sensitivity levels, is crafted, with each configuration labeled according to its recommended mitigation plan. Using decision tree and random forest models, a classifier is trained to recommend appropriate mitigation/transition plans such as continuous monitoring, scheduled transitions, and immediate hybrid implementation. The proposed approach introduces a data-driven and dynamic solution for organizations to assess the scale of the migration, specifying a structured roadmap toward quantum resilience. The results highlight important features that influence strategy decisions and support actionable recommendations for cryptographic modernization based on system context.