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I. Cherkaoui

Publications and source records attributed to I. Cherkaoui.

3 recordsLinked to original sources

Deterministic Johnson--Lindenstrauss Projections from Pisot $β$-Transformations for Zero-Knowledge Private Routing

Zero-knowledge (ZK) proofs certify that a message belongs to an allowed semantic class without revealing the message, but the certificate compares a high-dimensional embedding against class centroids, so its cost grows with the embedding dimension $d$. A Johnson--Lindenstrauss (JL) projection lowers $d$ to $m\ll d$ while preserving pairwise distances, yet a random JL matrix must be committed and its sampling proved inside the circuit, which is costly and a leakage risk. We construct a public deterministic projection from the standardized orbit of a Pisot $β$-transformation, analyzed through the spectral gap of the $β$-map, the geometric decay of its correlations, rather than equidistribution. We prove that the induced squared-norm estimator is unbiased up to a term decaying geometrically with a sampling gap, and that its variance is $V_0/m$ with a constant $V_0$ that is dimension-free in experiment and, under one stated concentration hypothesis, in theory. A single public seed preserving all pairwise centroid distances therefore exists and is found by search. Against six standard projections, including the chaotic-sequence matrix of Yu \emph{et al.}, the construction matches statistical quality to within measurement noise, and it is the only one simultaneously free of in-circuit randomness and exactly reproducible in a fixed finite field at a per-step cost $\log_2β$ rather than $2^{k}$.

cs.IT

Categorical Framework for Quantum-Resistant Zero-Trust AI Security

The rapid deployment of AI models necessitates robust, quantum-resistant security, particularly against adversarial threats. Here, we present a novel integration of post-quantum cryptography (PQC) and zero trust architecture (ZTA), formally grounded in category theory, to secure AI model access. Our framework uniquely models cryptographic workflows as morphisms and trust policies as functors, enabling fine-grained, adaptive trust and micro-segmentation for lattice-based PQC primitives. This approach offers enhanced protection against adversarial AI threats. We demonstrate its efficacy through a concrete ESP32-based implementation, validating a crypto-agile transition with quantifiable performance and security improvements, underpinned by categorical proofs for AI security. The implementation achieves significant memory efficiency on ESP32, with the agent utilizing 91.86% and the broker 97.88% of free heap after cryptographic operations, and successfully rejects 100% of unauthorized access attempts with sub-millisecond average latency.

cs.CR

Quasi-cyclic Linear Error-Block Code-based Post-quantum Signature

Shor algorithm led to the discovery of multiple vulnerabilities in a number of cryptosystems. As a result, post-quantum cryptography attempts to provide cryptographic solutions that can face these attacks, ensuring the security of sensitive data in a future where quantum computers are assumed to exist. Error correcting codes are a source for efficiency when it comes to signatures, especially random ones described in this paper, being quantum-resistant and reaching the Gilbert-Varshamov bound, thus offering a good trade-off between rate and distance. In the light of this discussion, we introduce a signature based on a family of linear error-block codes (LEB), with strong algebraic properties: it is the family of quasi-cyclic LEB codes that we do define algebraically during this work.

quant-ph