Domain-Informed Representation for Evolutionary Sieving in Integral and Module Lattices

Computer Science > Cryptography and Security [Submitted on 27 May 2026] Domain-Informed Representation for Evolutionary Sieving in Integral and Module Lattices Ahmad Tashfeen, Qi Cheng Traditional cryptography, rooted in problems, e.g., integer factorisation or discrete log, is inevitably vulnerable to a fully operational quantum computer. Although it remains an engineering frontier, the looming threat extends to encrypted data stored today, which could be decrypted in the future with quantum capabilities. To safeguard against this eventuality, the backbone of the modern quantum-safe cryptography is the Shortest Vector Problem (SVP). We enhance Laarhoven's treatment of Ajtai et al.'s sieving as a genetic algorithm (GA) for the SVP by incorporating domain-informed SVP representation and crossover while naturally extending application to the module lattices. Comments: Published (16 pages) in the proceedings of EvoApplications 2026. You may find the proceedings version here this https URL Subjects: Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI) Cite as: arXiv:2605.29169 [cs.CR]   (or arXiv:2605.29169v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2605.29169 Focus to learn more Journal reference: Lecture Notes in Computer Science 16524 (2026) 133-148 Related DOI: https://doi.org/10.1007/978-3-032-23604-3_9 Focus to learn more Submission history From: Ahmad Tashfeen [view email] [v1] Wed, 27 May 2026 23:09:10 UTC (10,725 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-05 Change to browse by: cs cs.AI References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)