Titlebook: Proceedings of the Future Technologies Conference (FTC) 2024, Volume 4; Kohei Arai Conference proceedings 2024 The Editor(s) (if applicabl

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A Framework for TrustZone Encoding/Decoding for QR Buyer-Presented and VCC Offline Generated Payments,amework for an integrated system that can provide security well beyond exciting tokenization and VCC systems and enables a peer-to-peer transactions that encourage developers’ free access with open-source implementations and remove middleman threats or controls.

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,A Novel Approach for?Continual and?Federated Network Anomaly Detection, Force and SQL Injection to further evaluate the capability of the detection module to distinguish normal and anomalous traffic. Throughout the different validation scenarios, the detection module achieved an f1-score of 93.80% for one of the targeted components and a percentage of normal flows correctly identified of 99,13%.

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Performance Evaluation of Response Based Cryptography Versus Fuzzy Extractors Based on Error Correction Codes,rtened random number to rectify more bits in the key. Consequently, RBC emerges as a highly secure approach for rectifying PUF-based keys, notably outperforming Fuzzy Extractors at significantly low noise levels with a latency superiority of an order of 10..

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,A Novel Approach to?Optimize Response-Based Cryptography for?Secure Data Transmission,keys within milliseconds. In the rare cases of failure to recover the keys, repeating the challenge-response-pair mechanism of the?PUF proves to be a faster and effective alternative than persisting in?a lengthy search.

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,Strengthening Industrial IoT Security with?Integrated PUF Token,CRYSTAL-KYBER, our protocol presents a comprehensive framework for robust IoT device security, proficiently balancing efficiency, reliability, and cryptographic strength in safeguarding sensitive data transmission.

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Manuel A. Barroyeta,Anthony J. Toapanta,Franklin M. Silva,Jessica S. Ortiz,Cesar A. Naranjo,Víctor H. Andaluzimprovement. Extensive experiments on public benchmark datasets demonstrate that our proposed module can effectively enhance the recognition performance. Our method achieves better recognition performance than prior arts on both CROHME and HME100K datasets.

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