AI-Driven Adaptive Adversaries and the Erosion of Cryptographic Trust in Public Key Systems

Computer Science > Cryptography and Security [Submitted on 23 May 2026] AI-Driven Adaptive Adversaries and the Erosion of Cryptographic Trust in Public Key Systems Petar Radanliev This paper examines the erosion of Public Key Cryptography (PKC) security under adaptive adversarial optimisation driven by artificial intelligence. The problem addressed is the growing mismatch between algorithm-centric cryptographic security models and operational attack realities, where adversaries exploit implementation-level observability rather than breaking cryptographic primitives. Subjects: Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI); Machine Learning (cs.LG); Multiagent Systems (cs.MA); Software Engineering (cs.SE) Cite as: arXiv:2605.24542 [cs.CR]   (or arXiv:2605.24542v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2605.24542 Focus to learn more Journal reference: J Anal Sci Technol 17, 26 (2026) Related DOI: https://doi.org/10.1186/s40543-026-00547-y Focus to learn more Submission history From: Petar Radanliev [view email] [v1] Sat, 23 May 2026 12:14:22 UTC (2,137 KB) Access Paper: view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-05 Change to browse by: cs cs.AI cs.LG cs.MA cs.SE 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?)