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Titlebook: Network Traffic Anomaly Detection and Prevention; Concepts, Techniques Monowar H. Bhuyan,Dhruba K. Bhattacharyya,Jugal K. Textbook 2017 Spr

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發(fā)表于 2025-3-21 18:50:31 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Network Traffic Anomaly Detection and Prevention
副標(biāo)題Concepts, Techniques
編輯Monowar H. Bhuyan,Dhruba K. Bhattacharyya,Jugal K.
視頻videohttp://file.papertrans.cn/663/662862/662862.mp4
概述Provides a thorough introduction to network attacks, describes the pros and cons of various data mining approaches, and discusses important issues and challenges to be addressed.Presents a systematic,
叢書名稱Computer Communications and Networks
圖書封面Titlebook: Network Traffic Anomaly Detection and Prevention; Concepts, Techniques Monowar H. Bhuyan,Dhruba K. Bhattacharyya,Jugal K. Textbook 2017 Spr
描述This indispensable text/reference presents a comprehensive overview on the detection and prevention of anomalies in computer network traffic, from coverage of the fundamental theoretical concepts to in-depth analysis of systems and methods. Readers will benefit from invaluable practical guidance on how to design an intrusion detection technique and incorporate it into a system, as well as on how to analyze and correlate alerts without prior information..Topics and features: introduces the essentials of traffic management in high speed networks, detailing types of anomalies, network vulnerabilities, and a taxonomy of network attacks; describes a systematic approach to generating large network intrusion datasets, and reviews existing synthetic, benchmark, and real-life datasets; provides a detailed study of network anomaly detection techniques and systems under six different categories: statistical, classification, knowledge-base, cluster and outlier detection, soft computing, and combination learners; examines alert management and anomaly prevention techniques, including alert preprocessing, alert correlation, and alert post-processing; presents a hands-on approach to developing net
出版日期Textbook 2017
關(guān)鍵詞Anomaly Detection; Data Mining; Denial of Service; Distributed Denial of Service; Intrusion Prevention; N
版次1
doihttps://doi.org/10.1007/978-3-319-65188-0
isbn_softcover978-3-319-87968-0
isbn_ebook978-3-319-65188-0Series ISSN 1617-7975 Series E-ISSN 2197-8433
issn_series 1617-7975
copyrightSpringer International Publishing AG 2017
The information of publication is updating

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A Systematic Hands-On Approach to Generate Real-Life Intrusion Datasets,a systematic hands-on approach to generate real-life intrusion dataset. It is organized in three major sections. Section?3.1 provides the basic concepts. Section?3.2 introduces several benchmark and real-life datasets. Finally, Sect.?3.3 provides a systematic approach toward generation of an unbiase
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Network Traffic Anomaly Detection Techniques and Systems, chapter starts with a discussion of the basic properties of network-wide traffic with an example. This chapter is organized into six major sections to describe different network anomaly detection techniques and systems. They are statistical techniques and systems, classification-based techniques an
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Alert Management and Anomaly Prevention Techniques, messages (i.e., alerts) that indicate attack or suspicious or legitimate events. Due to widespread deployment of IDSs, they may generate an overwhelming number of alerts with true alerts mixed with false alerts. So, management of such alerts is indeed necessary to get to the origin of an attack, so
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Open Issues, Challenges, and Conclusion,detecting such threats. Any antivirusor defense software can only detect the threats if and only if the defender software understands how attackers get entry into a system and what tools they use to compromise a network or system. This chapter is focused on the open issuesand challengesfaced by theA
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