AI-Driven Adaptive Adversaries and the Erosion of Cryptographic Trust in Public Key Systems
Fuente:
arXiv
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| Autor principal: | |
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| Formato: | Preprint |
| Publicado: |
2026
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| Acceso en línea: | |
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| _version_ | 1866913159241007104 |
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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 |