Tran Minh Thanh, Vo Hoai Viet · 2026 · arXiv
DOI: 10.48550/arXiv.2610.30935 · open-access PDF
Die Sicherheit moderner öffentlich-schlüsselbasierter kryptografischer Systeme, wie RSA, Diffie-Hellman und ECC, hängt vollständig von der computergestützten Unverträglichkeit der Ganzzahlenfaktorisierung und diskreten Logarithmusproblemen ab. Damit diese asymmetrischen Algorithmen funktionieren, besteht eine Kernanforderung darin, dass das System in der Lage sein muss, die Primalität außergewöhnlich großer Zahlen zu erzeugen, zu testen und gleichzeitig zu beweisen.
Machine translation (Meta M2M100); the English original follows.
The security of modern public-key cryptographic systems, such as RSA, Diffie-Hellman, and ECC, depends entirely on the computational intractability of the integer factorization and discrete logarithm problems. For these asymmetric algorithms to operate, a core requirement is that the system must be capable of generating, testing, and simultaneously proving the primality of extraordinarily large numbers. To meet those requirements, this study proposes a comprehensive framework, bridging clas- sical number theory with modern machine learning models and optimization algorithms. Specifically, the
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