Traffic Anomaly Detection
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Network Traffic Anomaly Detection And Prevention
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Author : Monowar H. Bhuyan
language : en
Publisher: Springer
Release Date : 2017-09-03
Network Traffic Anomaly Detection And Prevention written by Monowar H. Bhuyan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-03 with Computers categories.
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 network traffic monitoring and analysis tools, together with a survey of existing tools; discusses various evaluation criteria and metrics, covering issues of accuracy, performance, completeness, timeliness, reliability, and quality; reviews open issues and challenges in network traffic anomaly detection and prevention. This informative work is ideal for graduate and advanced undergraduate students interested in network security and privacy, intrusion detection systems, and data mining in security. Researchers and practitioners specializing in network security will also find the book to be a useful reference.
Traffic Anomaly Detection
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Author : Antonio Cuadra-Sánchez
language : en
Publisher: Elsevier
Release Date : 2015-10-31
Traffic Anomaly Detection written by Antonio Cuadra-Sánchez and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-31 with Technology & Engineering categories.
This book presents an overview of traffic anomaly detection analysis, allowing you to monitor security aspects of multimedia services. The author's approach is based on the analysis of time aggregation adjacent periods of the traffic. As traffic varies throughout the day, it is essential to consider the concrete traffic period in which the anomaly occurs. This book presents the algorithms proposed specifically for this analysis and an empirical comparative analysis of those methods and settle a new information theory based technique, named "typical day analysis". A new information-theory based technique for traffic anomaly detection (typical day analysis) Introductory chapters to anomaly detection methods including control charts, tests of goodness-of-fit Mutual Information Contains comparative analysis of traffic anomaly detection methods
Traffic Anomaly Detection And Cause Identification Using Flow Level Measurements
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Author : Gerhard Münz
language : en
Publisher:
Release Date : 2010
Traffic Anomaly Detection And Cause Identification Using Flow Level Measurements written by Gerhard Münz and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.
Network Traffic Anomaly Detection And Evaluation
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Author : Daniela Brauckhoff
language : en
Publisher:
Release Date : 2010
Network Traffic Anomaly Detection And Evaluation written by Daniela Brauckhoff and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.
Network Classification For Traffic Management
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Author : Zahir Tari
language : en
Publisher: Computing and Networks
Release Date : 2020-03-23
Network Classification For Traffic Management written by Zahir Tari and has been published by Computing and Networks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-23 with Computers categories.
This authored book investigates network traffic classification solutions by proposing transport-layer methods to achieve better run and operated enterprise-scale networks.
Data Traffic Monitoring And Analysis
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Author : Ernst Biersack
language : en
Publisher: Springer
Release Date : 2013-03-02
Data Traffic Monitoring And Analysis written by Ernst Biersack and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-02 with Computers categories.
This book was prepared as the Final Publication of COST Action IC0703 "Data Traffic Monitoring and Analysis: theory, techniques, tools and applications for the future networks". It contains 14 chapters which demonstrate the results, quality,and the impact of European research in the field of TMA in line with the scientific objective of the Action. The book is structured into three parts: network and topology measurement and modelling, traffic classification and anomaly detection, quality of experience.
Network Anomaly Detection
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Author : Dhruba Kumar Bhattacharyya
language : en
Publisher: CRC Press
Release Date : 2013-06-18
Network Anomaly Detection written by Dhruba Kumar Bhattacharyya and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-18 with Computers categories.
With the rapid rise in the ubiquity and sophistication of Internet technology and the accompanying growth in the number of network attacks, network intrusion detection has become increasingly important. Anomaly-based network intrusion detection refers to finding exceptional or nonconforming patterns in network traffic data compared to normal behavior. Finding these anomalies has extensive applications in areas such as cyber security, credit card and insurance fraud detection, and military surveillance for enemy activities. Network Anomaly Detection: A Machine Learning Perspective presents machine learning techniques in depth to help you more effectively detect and counter network intrusion. In this book, you’ll learn about: Network anomalies and vulnerabilities at various layers The pros and cons of various machine learning techniques and algorithms A taxonomy of attacks based on their characteristics and behavior Feature selection algorithms How to assess the accuracy, performance, completeness, timeliness, stability, interoperability, reliability, and other dynamic aspects of a network anomaly detection system Practical tools for launching attacks, capturing packet or flow traffic, extracting features, detecting attacks, and evaluating detection performance Important unresolved issues and research challenges that need to be overcome to provide better protection for networks Examining numerous attacks in detail, the authors look at the tools that intruders use and show how to use this knowledge to protect networks. The book also provides material for hands-on development, so that you can code on a testbed to implement detection methods toward the development of your own intrusion detection system. It offers a thorough introduction to the state of the art in network anomaly detection using machine learning approaches and systems.
Network Anomaly Detection
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Author : Dhruba Kumar Bhattacharyya
language : en
Publisher: CRC Press
Release Date : 2013-06-18
Network Anomaly Detection written by Dhruba Kumar Bhattacharyya and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-18 with Computers categories.
With the rapid rise in the ubiquity and sophistication of Internet technology and the accompanying growth in the number of network attacks, network intrusion detection has become increasingly important. Anomaly-based network intrusion detection refers to finding exceptional or nonconforming patterns in network traffic data compared to normal behavior. Finding these anomalies has extensive applications in areas such as cyber security, credit card and insurance fraud detection, and military surveillance for enemy activities. Network Anomaly Detection: A Machine Learning Perspective presents machine learning techniques in depth to help you more effectively detect and counter network intrusion. In this book, you’ll learn about: Network anomalies and vulnerabilities at various layers The pros and cons of various machine learning techniques and algorithms A taxonomy of attacks based on their characteristics and behavior Feature selection algorithms How to assess the accuracy, performance, completeness, timeliness, stability, interoperability, reliability, and other dynamic aspects of a network anomaly detection system Practical tools for launching attacks, capturing packet or flow traffic, extracting features, detecting attacks, and evaluating detection performance Important unresolved issues and research challenges that need to be overcome to provide better protection for networks Examining numerous attacks in detail, the authors look at the tools that intruders use and show how to use this knowledge to protect networks. The book also provides material for hands-on development, so that you can code on a testbed to implement detection methods toward the development of your own intrusion detection system. It offers a thorough introduction to the state of the art in network anomaly detection using machine learning approaches and systems.
Network Centric Traffic Analysis
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Author : Jieyan Fan
language : en
Publisher:
Release Date : 2008
Network Centric Traffic Analysis written by Jieyan Fan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Computers categories.
To provide more reliable and secure Internet service, Internet service providers have more and more interests in network centric traffic analysis. This book considers this issue from two perspectives, which are of ISP's most interest: 1) network centric anomaly detection and 2) network centric traffic classification. In our study on network centric anomaly detection, we designed an edge router based framework to detect anomaly in the first place they enter network; we proposed the so-called two-way matching features, which are effective indicators of network anomalies; and we creatively considered spatial and temporal correlation among edge routers at the same time. To tap the potential profits made by multimedia services, ISPs are of much interest to detect voice and video traffic. Yet, to our best knowledge no existing approaches are available to separate between voice and video. To solve the problem, we creatively applied spectral analysis techniques to extract regularities in multimedia traffic and used minimum distance to subspace as classification metric. Results demonstrate the effectiveness and robustness of our approach.
Multi Fractal Traffic And Anomaly Detection In Computer Communications
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Author : Ming Li
language : en
Publisher: CRC Press
Release Date : 2023-01-09
Multi Fractal Traffic And Anomaly Detection In Computer Communications written by Ming Li and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-09 with Computers categories.
This book provides a comprehensive theory of mono- and multi-fractal traffic, including the basics of long-range dependent time series and 1/f noise, ergodicity and predictability of traffic, traffic modeling and simulation, stationarity tests of traffic, traffic measurement and the anomaly detection of traffic in communications networks. Proving that mono-fractal LRD time series is ergodic, the book exhibits that LRD traffic is stationary. The author shows that the stationarity of multi-fractal traffic relies on observation time scales, and proposes multi-fractional generalized Cauchy processes and modified multi-fractional Gaussian noise. The book also establishes a set of guidelines for determining the record length of traffic in measurement. Moreover, it presents an approach of traffic simulation, as well as the anomaly detection of traffic under distributed-denial-of service attacks. Scholars and graduates studying network traffic in computer science will find the book beneficial.