Titlebook: Security and Privacy; Second International Pantelimon St?nic?,Sihem Mesnager,Sumit Kumar Debn Conference proceedings 2021 Springer Nature S

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moribund

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AGGER

Multi-source Fault Injection Detection Using Machine Learning and Sensor Fusionease attack diversity. The framework is able to detect the presence of an attack with 92% accuracy for mixed or multiple attack sources, and further classify the type of perturbation with 78% accuracy keeping the false positive rate at 0%. Overall, this two-stage detection framework is a cost-effect

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Traceable and Verifier-Local Revocable Attribute-Based Signature with Constant Lengths traceability or revocability, but not both. In this paper, we proposed a constant-size traceable ABS scheme with verifier-local revocation (VLR) feature and it supports monotone predicate. The scheme is secure in the standard model under well-known cryptographic assumptions.

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整潔漂亮

嚴峻考驗

den continuum causes the divergence of the conventional polarization expansion and of several variants of SAPT. This development will be described in some detail in Sects.?2–4, where, in addition to a?review of published work, we shall present several original results on this subject. In an unrelate