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Titlebook: Security, Privacy, and Anonymity in Computation, Communication, and Storage; SpaCCS 2020 Internat Guojun Wang,Bing Chen,Hao Han Conference

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發(fā)表于 2025-3-21 17:31:02 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Security, Privacy, and Anonymity in Computation, Communication, and Storage
副標題SpaCCS 2020 Internat
編輯Guojun Wang,Bing Chen,Hao Han
視頻videohttp://file.papertrans.cn/864/863639/863639.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Security, Privacy, and Anonymity in Computation, Communication, and Storage; SpaCCS 2020 Internat Guojun Wang,Bing Chen,Hao Han Conference
描述.This book constitutes seven refereed workshops and symposiums, SpaCCS Workshops 2020, which are held jointly with the 13th International Conference on Security, Privacy, and Anonymity in Computation, Communication, and Storage, SpaCCS 2020, in Nanjing, China, in December 2020.. The 48 papers were carefully reviewed and selected from 131 submissions and cover a broad range of topics on security, privacy and anonymity in computation communication, and storage, including the 11th International Workshop on Trust, Security and Privacy for Big Data (TrustData 2020), the 10th International Symposium on Trust, Security and Privacy for Emerging Applications (TSP 2020), the 9th International Symposium on Security and Privacy on Internet of Things (SPIoT 2020), the 6th International Symposium on Sensor-Cloud Systems (SCS 2020), the Second International Workshop on Communication, Computing, Informatics and Security? (CCIS 2020), the First International Workshop on Intelligence and Security in Next Generation Networks (ISNGN 2020), the First International Symposium on Emerging Information Security and Applications (EISA 2020)..
出版日期Conference proceedings 2021
關鍵詞artificial intelligence; authentication; communication systems; computer hardware; computer networks; com
版次1
doihttps://doi.org/10.1007/978-3-030-68884-4
isbn_softcover978-3-030-68883-7
isbn_ebook978-3-030-68884-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2021
The information of publication is updating

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The Future Prospects of Adversarial Netsound in parallel when it comes to the literature of machine learning adversaries. In this paper, we have tried to inspect the adversarial attack types and their defenses by comprehensively classifying different techniques.
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