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Author

R. Turkson

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Preprint Oct 2026

Augmentation-Guided Adversarial Training via Local Stability-Based Sample Selection

Adversarial training remains one of the most effective defenses against adversarial attacks, but its standard PGD-based training is computationally expensive because adversarial examples are generated for every training sample. Selective adversarial training reduces this cost by perturbing only a subset of samples. How...

Daniel Agyei Asante, M. Tetteh, Deborah Asamoah et al. · 0 citations
Preprint Aug 2026

A Commitment-Based Hybrid Post-Quantum Cryptographic Model for Multi-File Cloud Storage

Cloud storage clients increasingly require authentication that remains secure against future quantum-capable adversaries, motivating hybrid constructions that combine classical primitives with standardized post-quantum alternatives. Extended naively to multi-file upload, such constructions incur a per-file lattice sign...

Lemdi Frank Prikutse, R. Turkson, A. Yussiff et al. · 0 citations

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