Intrusion Detection Networks
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Intrusion Detection Networks
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Author : Carol Fung
language : en
Publisher: CRC Press
Release Date : 2013-11-19
Intrusion Detection Networks written by Carol Fung and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-19 with Computers categories.
Intrusion Detection Networks: A Key to Collaborative Security supplies a complete introduction to intrusion detection systems (IDS) and intrusion detection networks (IDN). Describing how to leverage effective and efficient collaboration between participant IDSs, it explains the benefits of building IDNs, identifies the challenges underlying their design, and outlines possible solutions. It also reviews the full-range of proposed IDN solutions-analyzing their scope, topology, strengths, weaknesses, and limitations. It also includes a case study that illustrates the application of collaborative intrusion detection to real-world malware detection scenarios.
Intrusion Detection Systems
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Author : Roberto Di Pietro
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-06-12
Intrusion Detection Systems written by Roberto Di Pietro and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-06-12 with Computers categories.
In our world of ever-increasing Internet connectivity, there is an on-going threat of intrusion, denial of service attacks, or countless other abuses of computer and network resources. In particular, these threats continue to persist due to the flaws of current commercial intrusion detection systems (IDSs). Intrusion Detection Systems is an edited volume by world class leaders in this field. This edited volume sheds new light on defense alert systems against computer and network intrusions. It also covers integrating intrusion alerts within security policy framework for intrusion response, related case studies and much more. This volume is presented in an easy-to-follow style while including a rigorous treatment of the issues, solutions, and technologies tied to the field. Intrusion Detection Systems is designed for a professional audience composed of researchers and practitioners within the computer network and information security industry. It is also suitable as a reference or secondary textbook for advanced-level students in computer science.
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 Intrusion Detection And Prevention
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Author : Ali A. Ghorbani
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-10-10
Network Intrusion Detection And Prevention written by Ali A. Ghorbani and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-10-10 with Computers categories.
Network Intrusion Detection and Prevention: Concepts and Techniques provides detailed and concise information on different types of attacks, theoretical foundation of attack detection approaches, implementation, data collection, evaluation, and intrusion response. Additionally, it provides an overview of some of the commercially/publicly available intrusion detection and response systems. On the topic of intrusion detection system it is impossible to include everything there is to say on all subjects. However, we have tried to cover the most important and common ones. Network Intrusion Detection and Prevention: Concepts and Techniques is designed for researchers and practitioners in industry. This book is suitable for advanced-level students in computer science as a reference book as well.
Network Intrusion Detection Using Deep Learning
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Author : Kwangjo Kim
language : en
Publisher: Springer
Release Date : 2018-09-25
Network Intrusion Detection Using Deep Learning written by Kwangjo Kim and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-25 with Computers categories.
This book presents recent advances in intrusion detection systems (IDSs) using state-of-the-art deep learning methods. It also provides a systematic overview of classical machine learning and the latest developments in deep learning. In particular, it discusses deep learning applications in IDSs in different classes: generative, discriminative, and adversarial networks. Moreover, it compares various deep learning-based IDSs based on benchmarking datasets. The book also proposes two novel feature learning models: deep feature extraction and selection (D-FES) and fully unsupervised IDS. Further challenges and research directions are presented at the end of the book. Offering a comprehensive overview of deep learning-based IDS, the book is a valuable reerence resource for undergraduate and graduate students, as well as researchers and practitioners interested in deep learning and intrusion detection. Further, the comparison of various deep-learning applications helps readers gain a basic understanding of machine learning, and inspires applications in IDS and other related areas in cybersecurity.
Deep Learning For Intrusion Detection
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Author : Faheem Syeed Masoodi
language : en
Publisher: John Wiley & Sons
Release Date : 2026-01-28
Deep Learning For Intrusion Detection written by Faheem Syeed Masoodi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-01-28 with Computers categories.
Comprehensive resource exploring deep learning techniques for intrusion detection in various applications such as cyber physical systems and IoT networks Deep Learning for Intrusion Detection provides a practical guide to understand the challenges of intrusion detection in various application areas and how deep learning can be applied to address those challenges. It begins by discussing the basic concepts of intrusion detection systems (IDS) and various deep learning techniques such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and deep belief networks (DBNs). Later chapters cover timely topics including network communication between vehicles and unmanned aerial vehicles. The book closes by discussing security and intrusion issues associated with lightweight IoTs, MQTT networks, and Zero-Day attacks. The book presents real-world examples and case studies to highlight practical applications, along with contributions from leading experts who bring rich experience in both theory and practice. Deep Learning for Intrusion Detection includes information on: Types of datasets commonly used in intrusion detection research including network traffic datasets, system call datasets, and simulated datasets The importance of feature extraction and selection in improving the accuracy and efficiency of intrusion detection systems Security challenges associated with cloud computing, including unauthorized access, data loss, and other malicious activities Mobile Adhoc Networks (MANETs) and their significant security concerns due to high mobility and the absence of a centralized authority Deep Learning for Intrusion Detection is an excellent reference on the subject for computer science researchers, practitioners, and students as well as engineers and professionals working in cybersecurity.
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.
Network Intrusion Detection
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Author : Stephen Northcutt
language : en
Publisher: Sams Publishing
Release Date : 2002
Network Intrusion Detection written by Stephen Northcutt and has been published by Sams Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Computers categories.
This book is a training aid and reference for intrusion detection analysts. While the authors refer to research and theory, they focus their attention on providing practical information. New to this edition is coverage of packet dissection, IP datagram fields, forensics, and snort filters.
Computer Intrusion Detection And Network Monitoring
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Author : David J. Marchette
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17
Computer Intrusion Detection And Network Monitoring written by David J. Marchette and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-17 with Mathematics categories.
In the fall of 1999, I was asked to teach a course on computer intrusion detection for the Department of Mathematical Sciences of The Johns Hopkins University. That course was the genesis of this book. I had been working in the field for several years at the Naval Surface Warfare Center, in Dahlgren, Virginia, under the auspices of the SHADOW program, with some funding by the Office of Naval Research. In designing the class, I was concerned both with giving an overview of the basic problems in computer security, and with providing information that was of interest to a department of mathematicians. Thus, the focus of the course was to be more on methods for modeling and detecting intrusions rather than one on how to secure one's computer against intrusions. The first task was to find a book from which to teach. I was familiar with several books on the subject, but they were all at either a high level, focusing more on the political and policy aspects of the problem, or were written for security analysts, with little to interest a mathematician. I wanted to cover material that would appeal to the faculty members of the department, some of whom ended up sitting in on the course, as well as providing some interesting problems for students. None of the books on the market at the time had an adequate discussion of mathematical issues related to intrusion detection.
Network Intrusion Detection
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Author : Stephen Northcutt
language : en
Publisher: New Riders Publishing
Release Date : 2001
Network Intrusion Detection written by Stephen Northcutt and has been published by New Riders Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Computers categories.
Intrusion detection is one of the hottest growing areas of network security. As the number of corporate, government, and educational networks grow and as they become more and more interconnected through the Internet, there is a correlating increase in the types and numbers of attacks to penetrate those networks. Intrusion Detection, Second Edition is a training aid and reference for intrusion detection analysts. This book is meant to be practical. The authors are literally the most recognized names in this specialized field, with unparalleled experience in defending our country s government and military computer networks. People travel from all over the world to hear them speak, and this book will be a distillation of that experience. The book's approach is to introduce and ground topics through actual traffic patterns. The authors have been through the trenches and give you access to unusual and unique data.