arXiv:2605.24542v1 Announce Type: cross Abstract: 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.
The increasing sophistication of AI models and their integration into offensive cybersecurity capabilities makes the emergence of AI-driven adaptive adversaries an imminent threat to existing security paradigms.
This development challenges the foundational assumption of cryptographic security (algorithm resilience) by shifting the attack vector to implementation-level vulnerabilities, forcing a re-evaluation of current security models.
The focus of cybersecurity shifts from purely theoretical cryptographic robustness to practical implementation security, requiring adaptive defenses against AI-powered, real-time adversarial learning.
- · AI-powered cybersecurity firms
- · Security auditing and adaptive defense specialists
- · Hardware security module (HSM) manufacturers
- · Organizations relying solely on standard cryptographic primitives
- · Traditional static security solutions
- · Cloud providers with vulnerable infrastructure
Public Key Cryptography (PKC) systems face immediate, enhanced threats from AI-driven adaptive adversaries exploiting implementation flaws.
Increased investment in real-time, AI-backed defensive security measures and more rigorous implementation-level security audits becomes critical for all digital infrastructure.
The long-term erosion of trust in digital communications and transactions could necessitate a complete overhaul of internet security protocols or a shift to post-quantum cryptography sooner than anticipated.
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Read at arXiv cs.LG