A Novel Post-Quantum Secure Digital Signature Scheme Based on Neural Network

• URL: http://arxiv.org/abs/2507.20676v1
• Date: Mon, 28 Jul 2025 09:56:09 GMT
• Title: A Novel Post-Quantum Secure Digital Signature Scheme Based on Neural Network
• Authors: Satish Kumar, Md. Arzoo Jamal,
• Abstract summary: A neural network with binary weights is employed to define the central structure of the signature scheme.<n>It is demonstrated that the proposed signature scheme provide security against adaptive Chosen Existential Unability attacks.<n>Results indicate notable efficiency and practical viability in post-quantum cryptographic applications.
• Score: 1.7495213911983414
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• 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 neural network architectures. A neural network with binary weights is employed to define the central structure of the signature scheme. The design introduces a recurrent random vector, functionally analogous to an attention mechanism, which contributes dynamic randomness based on the previous state, thereby enhancing the scheme's security. It is demonstrated that the proposed signature scheme provide security against Existential Unforgeability under adaptive Chosen-Message Attacks (EUF-CMA). Furthermore, it is proven that direct attacks aimed to recover the private keys are computationally infeasible within polynomial time, even in the presence of quantum computing abilities. The operational characteristics of the proposed scheme are also evaluated, with results indicating notable efficiency and practical viability in post-quantum cryptographic applications.

Related papers

• Keyed Chaotic Dynamics for Privacy-Preserving Neural Inference [0.0]
  This work introduces a novel encryption method for ensuring the security of neural inference.<n>By constructing key-conditioned chaotic graph dynamical systems, we enable the encryption and decryption of real-valued tensors within the neural architecture.
  arXiv  Detail & Related papers  (2025-05-29T17:05:42Z)
• Extensible Post Quantum Cryptography Based Authentication [1.7449047573672085]
  We introduce a quantum-safe single-shot protocol for machine-to-machine authentication and authorization.<n> operating entirely over insecure channels, this protocol enables the forward-secure establishment of tokens.<n>This study lays the groundwork for scalable, resilient, and future-proof identity infrastructures in a quantum-enabled world.
  arXiv  Detail & Related papers  (2025-05-22T01:34:17Z)
• Post-Quantum Cryptography: An Analysis of Code-Based and Lattice-Based Cryptosystems [55.49917140500002]
  Quantum computers will be able to break modern cryptographic systems using Shor's Algorithm.<n>We first examine the McEliece cryptosystem, a code-based scheme believed to be secure against quantum attacks.<n>We then explore NTRU, a lattice-based system grounded in the difficulty of solving the Shortest Vector Problem.
  arXiv  Detail & Related papers  (2025-05-06T03:42:38Z)
• Quantum-Safe integration of TLS in SDN networks [0.0]
  transition to quantum-safe cryptography within the next decade is critical.<n>We have selected Transport Layer Security as the foundation to hybridize classical, quantum, and post-quantum cryptography.<n>The performance of this approach has been demonstrated using a deployed production infrastructure.
  arXiv  Detail & Related papers  (2025-02-24T14:35:56Z)
• Post-Quantum Key Agreement Protocols Based on Modified Matrix-Power Functions over Singular Random Integer Matrix Semirings [0.0]
  Post-quantum cryptography is essential for securing digital communications against threats posed by quantum computers.<n>This paper introduces two novel post-quantum key agreement protocols that can be easily implemented on standard computers.
  arXiv  Detail & Related papers  (2025-01-04T14:01:09Z)
• Pseudorandom quantum authentication [0.8204952610951527]
  We introduce the pseudorandom quantum authentication scheme (PQAS)<n>It is an efficient method for quantum states that relies solely on the existence of pseudorandom unitaries (PRUs)
  arXiv  Detail & Related papers  (2025-01-01T20:46:37Z)
• Revocable Cryptography from Learning with Errors [61.470151825577034]
  We build on the no-cloning principle of quantum mechanics and design cryptographic schemes with key-revocation capabilities. We consider schemes where secret keys are represented as quantum states with the guarantee that, once the secret key is successfully revoked from a user, they no longer have the ability to perform the same functionality as before.
  arXiv  Detail & Related papers  (2023-02-28T18:58:11Z)
• Quantization-aware Interval Bound Propagation for Training Certifiably Robust Quantized Neural Networks [58.195261590442406]
  We study the problem of training and certifying adversarially robust quantized neural networks (QNNs) Recent work has shown that floating-point neural networks that have been verified to be robust can become vulnerable to adversarial attacks after quantization. We present quantization-aware interval bound propagation (QA-IBP), a novel method for training robust QNNs.
  arXiv  Detail & Related papers  (2022-11-29T13:32:38Z)
• Robust Training and Verification of Implicit Neural Networks: A Non-Euclidean Contractive Approach [64.23331120621118]
  This paper proposes a theoretical and computational framework for training and robustness verification of implicit neural networks. We introduce a related embedded network and show that the embedded network can be used to provide an $ell_infty$-norm box over-approximation of the reachable sets of the original network. We apply our algorithms to train implicit neural networks on the MNIST dataset and compare the robustness of our models with the models trained via existing approaches in the literature.
  arXiv  Detail & Related papers  (2022-08-08T03:13:24Z)
• Generation of High-Resolution Handwritten Digits with an Ion-Trap Quantum Computer [55.41644538483948]
  We implement a quantum-circuit based generative model to learn and sample the prior distribution of a Generative Adversarial Network. We train this hybrid algorithm on an ion-trap device based on $171$Yb$+$ ion qubits to generate high-quality images.
  arXiv  Detail & Related papers  (2020-12-07T18:51:28Z)
• Decentralizing Feature Extraction with Quantum Convolutional Neural Network for Automatic Speech Recognition [101.69873988328808]
  We build upon a quantum convolutional neural network (QCNN) composed of a quantum circuit encoder for feature extraction. An input speech is first up-streamed to a quantum computing server to extract Mel-spectrogram. The corresponding convolutional features are encoded using a quantum circuit algorithm with random parameters. The encoded features are then down-streamed to the local RNN model for the final recognition.
  arXiv  Detail & Related papers  (2020-10-26T03:36:01Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.