The paper introduces the linear canonical Riesz potential (LCRP) and analyzes its convergence properties, leveraging these findings to propose a novel, secure, and efficient asymmetric cascaded LCRP m…

This paper proposes a novel Simultaneous Data Compression and Encryption (SDCE) system that combines chaotic map-based encryption with Huffman encoding to securely and efficiently transmit large video…

The paper proposes a novel symmetric stream cipher utilizing the chaotic dynamics of random cubic mappings in the complex plane to generate highly random and secure key streams.

The paper proposes a generic, standard model construction for Anamorphic Key Encapsulation Mechanisms (AKEM) that achieves strong IND-CCA security, addressing a major gap in covert communication crypt…

The paper introduces a theoretically grounded evaluation framework for watermarking generative models, proposing a novel method (SSB) that allows for systematic design across all security-robustness-f…

This paper characterizes the graph structure, including cycle and path lengths, of Chebyshev permutation polynomials over the ring $\mathbb{Z}_{2^{k_1}3^{k_2}}$, demonstrating strong regularities desp…

The paper proposes Triumvir, a multi-modal ensemble architecture that significantly improves the classification of small, raw data fragments to distinguish between encrypted and compressed data, outpe…

The paper proposes FLAME, a novel framework that detects AI-generated image forgeries by identifying intrinsic energy anomalies caused by the diffusion process, achieving state-of-the-art localization…

The paper proposes a multi-ciphertext privacy-preserving framework to efficiently compute high-resolution image gradients using Fully Homomorphic Encryption (FHE) by dividing the large image into smal…

The paper introduces the base-m length codec, a canonical and robust encoding scheme that maps byte strings to lists of residues modulo m, essential for finite-ring cryptosystems.

The paper introduces a Neural Stringology Cryptanalysis (NSC) framework that uses machine learning to detect subtle structural patterns in stream cipher keystreams, demonstrating its potential for eva…

The paper argues that current lattice-based post-quantum cryptography, which relies on injecting noise, is not unconditionally secure because advanced quantum error correction and learning techniques…

The paper systematically investigates the conditions under which linear layers in AES-like ciphers avoid related-differential structures, proving that the MDS property is necessary and identifying spe…

The paper analyzes subcodes of lambda-Gabidulin codes to construct highly efficient McEliece-like and Niederreiter-like cryptosystems, demonstrating that random subcodes of classical Gabidulin codes y…

The paper introduces a mathematical and cryptographic framework for exactly recovering a single, noisy, high-dimensional discrete path from aggregated and incomplete observable data.

This paper provides a comparative analysis and benchmarking of Secure Multi-Party Computation (SMPC) and Fully Homomorphic Encryption (FHE) for machine learning, finding that the optimal choice depend…

The paper demonstrates that standard homomorphic encryption (HE) schemes are insufficient to guarantee integrity in networked control systems (NCS) against covert attacks, proposing instead a verifiab…

This paper provides the first comprehensive cryptanalysis of the Legendre Pseudorandom Function over extension fields, demonstrating key recovery attacks under both passive and active threat models.

The paper proposes a scalable, privacy-preserving framework for iris recognition using Fully Homomorphic Encryption (FHE), achieving accuracy comparable to cleartext while identifying the computationa…