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Titlebook: Versatile Cybersecurity; Mauro Conti,Gaurav Somani,Radha Poovendran Book 2018 Springer Nature Switzerland AG 2018 Security.Privacy.Cyber P

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发表于 2025-3-21 19:00:00 | 显示全部楼层 |阅读模式
书目名称Versatile Cybersecurity
编辑Mauro Conti,Gaurav Somani,Radha Poovendran
视频video
概述Provides focused content related to specific attacks or attack families irrespective of the attack target or victim application.Includes relevant open research directions at the end of each chapter.Ta
丛书名称Advances in Information Security
图书封面Titlebook: Versatile Cybersecurity;  Mauro Conti,Gaurav Somani,Radha Poovendran Book 2018 Springer Nature Switzerland AG 2018 Security.Privacy.Cyber P
描述.Cyber security research is one of the important areas in the computer science domain which also plays a major role in the life of almost every individual, enterprise, society and country, which this book illustrates. A large number of advanced security books focus on either cryptography or system security which covers both information and network security. However, there is hardly any books available for advanced-level students and research scholars in security research to systematically study how the major attacks are studied, modeled, planned and combated by the community. This book aims to fill this gap.. This book provides focused content related to specific attacks or attack families. These dedicated discussions in the form of individual chapters covers the application or area specific aspects, while discussing  the placement of defense solutions to combat the attacks. It includes eight high quality chaptersfrom established security research groups worldwide,  which address important attacks from theoretical (modeling) as well as practical aspects.. Each chapter brings  together comprehensive and structured information on an attack or an attack family. The authors present cri
出版日期Book 2018
关键词Security; Privacy; Cyber Physical System Security; Social Engineering; Botnets; Software Defined Networki
版次1
doihttps://doi.org/10.1007/978-3-319-97643-3
isbn_ebook978-3-319-97643-3Series ISSN 1568-2633 Series E-ISSN 2512-2193
issn_series 1568-2633
copyrightSpringer Nature Switzerland AG 2018
The information of publication is updating

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发表于 2025-3-21 21:05:06 | 显示全部楼层
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Insider Threat Detection: Machine Learning Way,ur. It concludes discussing future directions that uses combination of methods from natural language processing, behavioural analysis, sentiment analysis, and machine learning for insider threat detection.
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