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Titlebook: Cyber Security Cryptography and Machine Learning; Fourth International Shlomi Dolev,Vladimir Kolesnikov,Gera Weiss Conference proceedings 2

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发表于 2025-3-21 17:48:10 | 显示全部楼层 |阅读模式
书目名称Cyber Security Cryptography and Machine Learning
副标题Fourth International
编辑Shlomi Dolev,Vladimir Kolesnikov,Gera Weiss
视频videohttp://file.papertrans.cn/242/241744/241744.mp4
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Cyber Security Cryptography and Machine Learning; Fourth International Shlomi Dolev,Vladimir Kolesnikov,Gera Weiss Conference proceedings 2
描述This book constitutes the refereed proceedings of the Fourth International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2020, held in Be‘er Sheva, Israel, in July 2020..The 12 full and 4 short papers presented in this volume were carefully reviewed and selected from 38 submissions. They deal with the theory, design, analysis, implementation, or application of cyber security, cryptography and machine learning systems and networks, and conceptually innovative topics in these research areas..
出版日期Conference proceedings 2020
关键词artificial intelligence; authentication; computer networks; computer security; computer systems; cryptogr
版次1
doihttps://doi.org/10.1007/978-3-030-49785-9
isbn_softcover978-3-030-49784-2
isbn_ebook978-3-030-49785-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2020
The information of publication is updating

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https://doi.org/10.1007/978-1-349-07449-5th device-specific features and domain-related features are taken into account. We applied the proposed model on several IoT devices in the context of an enterprise network environment, demonstrating its feasibility in analyzing security-related considerations in smart environments.
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Religious Commitment and Marriage Breakdownture set dimensional space in half (from nine to four features), we still improve the performance of the classifier (an increase in the model’s F1-score from 92.92% to 95.81%). The fact that our models are robust to malicious perturbations but are also useful for clean data demonstrates the effectiv
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https://doi.org/10.1007/978-94-017-5976-2s safe on the platform. In this work, we detect malicious nodes by using supervised machine learning based anomaly detection in the transactional behavior of the accounts. Depending on the two prevalent account types – Externally Owned Account (EOA) and smart contract accounts, we apply two distinct
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Zel’manov’s Exceptional Methods on the ., resulting in increased power consumption and lower throughput. Volder proposed the CORDIC algorithm for trigonometric functions, expressed in terms of basic rotations. In this work, we present a correctly-rounded and efficient implementation of the CORDIC algorithm for the dataflow archit
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Bill Packer MA, FCA,Elaine Bakeread to the complete corruption of the ledger and even to the destruction of ledger copies the nodes hold. We will suggest a solution for the reconstruction of the blockchain in the event of such an attack. Our solution will include a mandatory publication of additional information by the private use
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Foreign Nationals Working in the UK, manner. We formulate the recommender system as a multi objective multi constraints optimization problem along with a simpler single objective multi constraint optimization problem. We solve this optimization using TOPSIS based on experimental analysis performed on three prominent FHE libraries HEli
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Zero-Knowledge to the Rescue: Consistent Redundant Backup of Keys Generated for Critical Financial ent where, as we said, not all recovery agents are available at all times, yet where transfers of encrypted information is semi-synchronous and globally available to parties that become on-line. In this architecture, it turned out, that the usually considered theoretical and costly transferable Zero
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Security Ranking of IoT Devices Using an AHP Model,th device-specific features and domain-related features are taken into account. We applied the proposed model on several IoT devices in the context of an enterprise network environment, demonstrating its feasibility in analyzing security-related considerations in smart environments.
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