Anomaly Detection In Network Traffic

Author : Monowar H. Bhuyan,Dhruba K. Bhattacharyya,Jugal K. Kalita
Publisher : Springer
Page : 263 pages
File Size : 45,8 Mb
Release : 2017-09-03
Category : Computers
ISBN : 9783319651880

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Network Traffic Anomaly Detection and Prevention by Monowar H. Bhuyan,Dhruba K. Bhattacharyya,Jugal K. Kalita Pdf

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.

Author : Dhruba Kumar Bhattacharyya,Jugal Kumar Kalita
Publisher : CRC Press
Page : 366 pages
File Size : 48,8 Mb
Release : 2013-06-18
Category : Computers
ISBN : 9781466582095

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Network Anomaly Detection by Dhruba Kumar Bhattacharyya,Jugal Kumar Kalita Pdf

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.

Author : IEEE Staff
Publisher : Unknown
Page : 128 pages
File Size : 40,8 Mb
Release : 2020-06-10
Category : Electronic
ISBN : 1728153727

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2020 5th International Conference on Communication and Electronics Systems (ICCES) by IEEE Staff Pdf

5th International Conference on Communication and Electronics Systems (ICCES 2020) is being organized on 10 12, June 2020 ICCES will provide an outstanding international forum for sharing knowledge and results in all fields of Engineering and Technology ICCES provides quality key experts who provide an opportunity in bringing up innovative ideas Recent updates in the in the field of technology will be a platform for the upcoming researchers The conference will be Complete, Concise, Clear and Cohesive in terms of research related to Communication and Electronics systems

Author : Zahir Tari,Adil Fahad,Xun Yi,Abdulmohsen Almalawi
Publisher : Computing and Networks
Page : 291 pages
File Size : 53,7 Mb
Release : 2020-03-23
Category : Computers
ISBN : 9781785619212

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Network Classification for Traffic Management by Zahir Tari,Adil Fahad,Xun Yi,Abdulmohsen Almalawi Pdf

This authored book investigates network traffic classification solutions by proposing transport-layer methods to achieve better run and operated enterprise-scale networks.

Author : Jugal Kalita
Publisher : Unknown
Page : 366 pages
File Size : 52,6 Mb
Release : 2013
Category : Electronic
ISBN : OCLC:1137345227

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Network Anomaly Detection by Jugal Kalita Pdf

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.

Author : Jordi Domingo-Pascual,Pietro Manzoni,Sergio Palazzo,Ana Pont,Caterina Scoglio
Publisher : Springer Science & Business Media
Page : 492 pages
File Size : 46,5 Mb
Release : 2011-04-28
Category : Business & Economics
ISBN : 9783642207563

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NETWORKING 2011 by Jordi Domingo-Pascual,Pietro Manzoni,Sergio Palazzo,Ana Pont,Caterina Scoglio Pdf

The two-volume set LNCS 6640 and 6641 constitutes the refereed proceedings of the 10th International IFIP TC 6 Networking Conference held in Valencia, Spain, in May 2011. The 64 revised full papers presented were carefully reviewed and selected from a total of 294 submissions. The papers feature innovative research in the areas of applications and services, next generation Internet, wireless and sensor networks, and network science. The first volume includes 36 papers and is organized in topical sections on anomaly detection, content management, DTN and sensor networks, energy efficiency, mobility modeling, network science, network topology configuration, next generation Internet, and path diversity.

Author : Antonio Cuadra-Sánchez,Javier Aracil
Publisher : Elsevier
Page : 70 pages
File Size : 53,8 Mb
Release : 2015-10-31
Category : Technology & Engineering
ISBN : 9780081008072

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Traffic Anomaly Detection by Antonio Cuadra-Sánchez,Javier Aracil Pdf

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

Author : Wojciech Zamojski,Jacek Mazurkiewicz,Jarosław Sugier,Tomasz Walkowiak,Janusz Kacprzyk
Publisher : Springer
Page : 554 pages
File Size : 51,8 Mb
Release : 2019-05-11
Category : Technology & Engineering
ISBN : 9783030195014

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Engineering in Dependability of Computer Systems and Networks by Wojciech Zamojski,Jacek Mazurkiewicz,Jarosław Sugier,Tomasz Walkowiak,Janusz Kacprzyk Pdf

This book presents papers on various problems of dependability in computer systems and networks that were discussed at the 14th DepCoS-RELCOMEX conference, in Brunów, Poland, from 1st to 5th July 2019. Discussing new ideas, research results and developments in the design, implementation, maintenance and analysis of complex computer systems, it is of interest to researchers and practitioners who are dealing with dependability issues in such systems. Dependability analysis came as a response to new challenges in the evaluation of contemporary complex systems, which should be considered as systems of people – with their needs and behaviours –interacting with technical communication channels (such as mobile activities, iCloud, Internet of Everything) and online applications, often operating in hostile environments. The diversity of topics covered, illustrates the variety of methods used in this area, often with the help of the latest results in artificial and computational intelligence.

Author : Daniela Brauckhoff
Publisher : Unknown
Page : 180 pages
File Size : 44,5 Mb
Release : 2010
Category : Electronic
ISBN : 3832289771

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Network Traffic Anomaly Detection and Evaluation by Daniela Brauckhoff Pdf

Author : Anonim
Publisher : BoD – Books on Demand
Page : 170 pages
File Size : 40,6 Mb
Release : 2024-01-17
Category : Electronic
ISBN : 9781837690268

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Anomaly Detection by Anonim Pdf

Author : Dongxiao Yu,Falko Dressler,Jiguo Yu
Publisher : Springer Nature
Page : 838 pages
File Size : 45,8 Mb
Release : 2020-09-09
Category : Computers
ISBN : 9783030590161

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Wireless Algorithms, Systems, and Applications by Dongxiao Yu,Falko Dressler,Jiguo Yu Pdf

The two-volume set LNCS 12385 + 12386 constitutes the proceedings of the 15th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2020, which was held during September 13-15, 2020. The conference was planned to take place in Qingdao, China; due to the COVID-19 pandemic it was held virtually. The 67 full and 14 short papers presented in these proceedings were carefully reviewed and selected from 216 submissions. These submissions cover many hot research topics, including machine-learning algorithms for wireless systems and applications, Internet of Things (IoTs) and related wireless solutions, wireless networking for cyber-physical systems (CPSs), security and privacy solutions for wireless applications, blockchain solutions for mobile applications, mobile edge computing, wireless sensor networks, distributed and localized algorithm design and analysis, wireless crowdsourcing, mobile cloud computing, vehicular networks, wireless solutions for smart cities, wireless algorithms for smart grids, mobile social networks, mobile system security, storage systems for mobile applications, etc.

Author : Ernst Biersack,Christian Callegari,Maja Matijasevic
Publisher : Springer
Page : 359 pages
File Size : 41,6 Mb
Release : 2013-03-02
Category : Computers
ISBN : 9783642367847

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Data Traffic Monitoring and Analysis by Ernst Biersack,Christian Callegari,Maja Matijasevic Pdf

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.

Author : Anup Bhange,Manmeet Kaur Marhas
Publisher : LAP Lambert Academic Publishing
Page : 92 pages
File Size : 49,8 Mb
Release : 2012
Category : Electronic
ISBN : 3659297631

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Anomaly Detection in Network Traffic by Anup Bhange,Manmeet Kaur Marhas Pdf

A worldwide Internet usage growth rate of 380% larger than the period from 2000, the year of the dot-com bubble burst, until present indicates that Internet technology has become a foundation of our daily life. In the same period, cyber-crime has seen an incredible that makes sophisticated protection device for computers and networks an absolute necessity. Firewalls as the major defense of the last decade do not give sufficient protection anymore. This fact has given rise to the expansion of intrusion detection and prevention systems. Traditional intrusion detection systems are hasty in the sense that they use a set of signatures, which raise at the same rate as new technique are discovered, to identify malicious traffic patterns. Anomaly detection systems are another branch of intrusion detection systems that act more proactively. They get a model of the normal system performance and issue alerts whenever the behavior changes; making an appropriate assumption that such changes are frequently caused by malicious or disruptive events. Anomaly detection has been a ground of exhaustive research over the last years as it poses several challenging problems.

Author : Eduardo H.M. Pena ,Luiz F. Carvalho ,Sylvio Barbon ,Joel J.P.C. Rodrigues ,Mario Lemes Proença
Publisher : Infinite Study
Page : 16 pages
File Size : 55,9 Mb
Release : 2024-05-12
Category : Electronic
ISBN : 8210379456XXX

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Anomaly detection using the correlational paraconsistent machine with digital signatures of network segment by Eduardo H.M. Pena ,Luiz F. Carvalho ,Sylvio Barbon ,Joel J.P.C. Rodrigues ,Mario Lemes Proença Pdf

This study presents the correlational paraconsistent machine (CPM), a tool for anomaly detection that incorporates unsupervised models for traffic characterization and principles of paraconsistency, to inspect irregularities at the network traffic flow level.

Author : Danfeng (Daphne)Yao,Xiaokui Shu,Long Cheng,Salvatore J.Stolfo
Publisher : Springer Nature
Page : 157 pages
File Size : 48,6 Mb
Release : 2022-06-01
Category : Computers
ISBN : 9783031023545

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Anomaly Detection as a Service by Danfeng (Daphne)Yao,Xiaokui Shu,Long Cheng,Salvatore J.Stolfo Pdf

Anomaly detection has been a long-standing security approach with versatile applications, ranging from securing server programs in critical environments, to detecting insider threats in enterprises, to anti-abuse detection for online social networks. Despite the seemingly diverse application domains, anomaly detection solutions share similar technical challenges, such as how to accurately recognize various normal patterns, how to reduce false alarms, how to adapt to concept drifts, and how to minimize performance impact. They also share similar detection approaches and evaluation methods, such as feature extraction, dimension reduction, and experimental evaluation. The main purpose of this book is to help advance the real-world adoption and deployment anomaly detection technologies, by systematizing the body of existing knowledge on anomaly detection. This book is focused on data-driven anomaly detection for software, systems, and networks against advanced exploits and attacks, but also touches on a number of applications, including fraud detection and insider threats. We explain the key technical components in anomaly detection workflows, give in-depth description of the state-of-the-art data-driven anomaly-based security solutions, and more importantly, point out promising new research directions. This book emphasizes on the need and challenges for deploying service-oriented anomaly detection in practice, where clients can outsource the detection to dedicated security providers and enjoy the protection without tending to the intricate details.