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

Fuente: arXiv
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Autor principal: Radanliev, Petar
Formato: Preprint
Publicado: 2026
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author Radanliev, Petar
author_facet Radanliev, Petar
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2605_24542
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle AI-Driven Adaptive Adversaries and the Erosion of Cryptographic Trust in Public Key Systems
Radanliev, Petar
Cryptography and Security
Artificial Intelligence
Machine Learning
Multiagent Systems
Software Engineering
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.
title AI-Driven Adaptive Adversaries and the Erosion of Cryptographic Trust in Public Key Systems
topic Cryptography and Security
Artificial Intelligence
Machine Learning
Multiagent Systems
Software Engineering
url https://arxiv.org/abs/2605.24542