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Titlebook: Security, Privacy, and Anonymity in Computation, Communication, and Storage; 10th International C Guojun Wang,Mohammed Atiquzzaman,Kim-Kwan

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21#
發(fā)表于 2025-3-25 06:55:55 | 只看該作者
Privacy-Preserving Handover Authentication Protocol from Lightweight Identity-Based Signature for Wure, or lack sufficient concern for user privacy. In this paper, we propose a new design idea for handover authentication protocol by using pseudonym-based cryptography and a variant of the SIGMA (Sign-and-MAC) approach, and present a new handover authentication protocol for wireless networks from e
22#
發(fā)表于 2025-3-25 07:54:09 | 只看該作者
,Research on Internet of Vehicles’ Privacy Protection Based on Tamper-Proof with Ciphertext,phertext policy attribute-based encryption, which to some degree has reduced the risk of the leakage of the user’s information. This solution realize the encryption protection of the contents of the vehicle mobile terminals by destroying the structure extension of the ciphertext, achieves the goal of non-extensibility security.
23#
發(fā)表于 2025-3-25 13:53:49 | 只看該作者
24#
發(fā)表于 2025-3-25 15:48:23 | 只看該作者
25#
發(fā)表于 2025-3-25 23:47:30 | 只看該作者
Privacy-Preserving Handover Authentication Protocol from Lightweight Identity-Based Signature for Wuser anonymity and un-traceability, conditional privacy preservation and so on. The performance analysis shows that our proposed protocol is more efficient than previous handover authentication protocols in terms of computation and communication.
26#
發(fā)表于 2025-3-26 02:43:02 | 只看該作者
Conference proceedings 2017and Storage, SpaCCS 2017, held in Guangzhou, China, in December 2017. .The 47 papers presented in this volume were carefully reviewed and selected from 140 submissions. They deal with research findings, achievements, innovations and perspectives in information security and related fields covering to
27#
發(fā)表于 2025-3-26 04:42:04 | 只看該作者
28#
發(fā)表于 2025-3-26 10:18:56 | 只看該作者
29#
發(fā)表于 2025-3-26 14:58:44 | 只看該作者
PCSD: A Tool for Android Malware Detection,lgorithms, like Bayesian ridge, Random forests, etc. Our results show that accuracy is 99.02% and . is 99.51% in experiment. These results demonstrate the efficacy of PCSD to distinguish malicious and benign android applications.
30#
發(fā)表于 2025-3-26 19:02:55 | 只看該作者
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