A Novel Post-Quantum Secure Digital Signature Scheme Based on Neural Network
Satish Kumar, Md. Arzoo Jamal

TL;DR
This paper introduces a new post-quantum secure digital signature scheme that uses neural network architectures to enhance security against quantum attacks, combining multivariate polynomial cryptography with neural network dynamics.
Contribution
It presents a novel neural network-based multivariate polynomial digital signature scheme with dynamic randomness, offering strong security and practical efficiency in the post-quantum era.
Findings
Provides security against EUF-CMA under quantum attacks
Demonstrates infeasibility of private key recovery within polynomial time
Shows efficiency and practicality for post-quantum cryptography
Abstract
Digital signatures are fundamental cryptographic primitives that ensure the authenticity and integrity of digital documents. In the post-quantum era, classical public key-based signature schemes become vulnerable to brute-force and key-recovery attacks due to the computational power of quantum algorithms. Multivariate polynomial based signature schemes are among the one of the cryptographic constructions that offers strong security guarantees against such quantum threats. With the growing capabilities of neural networks, it is natural to explore their potential application in the design of cryptographic primitives. Neural networks inherently captures the non-linear relationships within the data, which are encoded in their synaptic weight matrices and bias vectors. In this paper, we propose a novel construction of a multivariate polynomial based digital signature scheme that leverages…
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Taxonomy
TopicsCryptography and Data Security · Chaos-based Image/Signal Encryption · Cryptography and Residue Arithmetic
