Download or read book Network Anomaly Detection written by Dhruba Kumar Bhattacharyya and published by CRC Press. This book was released on 2013-06-18 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 behavi
Download or read book Network Traffic Anomaly Detection and Prevention written by Monowar H. Bhuyan and published by Springer. This book was released on 2017-09-03 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Anomaly Detection as a Service written by Danfeng (Daphne)Yao and published by Springer Nature. This book was released on 2022-06-01 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Anomaly Detection Principles and Algorithms written by Kishan G. Mehrotra and published by Springer. This book was released on 2017-11-18 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a readable and elegant presentation of the principles of anomaly detection,providing an easy introduction for newcomers to the field. A large number of algorithms are succinctly described, along with a presentation of their strengths and weaknesses. The authors also cover algorithms that address different kinds of problems of interest with single and multiple time series data and multi-dimensional data. New ensemble anomaly detection algorithms are described, utilizing the benefits provided by diverse algorithms, each of which work well on some kinds of data. With advancements in technology and the extensive use of the internet as a medium for communications and commerce, there has been a tremendous increase in the threats faced by individuals and organizations from attackers and criminal entities. Variations in the observable behaviors of individuals (from others and from their own past behaviors) have been found to be useful in predicting potential problems of various kinds. Hence computer scientists and statisticians have been conducting research on automatically identifying anomalies in large datasets. This book will primarily target practitioners and researchers who are newcomers to the area of modern anomaly detection techniques. Advanced-level students in computer science will also find this book helpful with their studies.
Download or read book Network Anomaly Detection written by Dhruba Kumar Bhattacharyya and published by CRC Press. This book was released on 2013-06-18 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Network Anomaly Detection written by Jugal Kalita and published by . This book was released on 2013 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Handbook of Information and Communication Security written by Peter Stavroulakis and published by Springer Science & Business Media. This book was released on 2010-02-23 with total page 863 pages. Available in PDF, EPUB and Kindle. Book excerpt: At its core, information security deals with the secure and accurate transfer of information. While information security has long been important, it was, perhaps, brought more clearly into mainstream focus with the so-called “Y2K” issue. Te Y2K scare was the fear that c- puter networks and the systems that are controlled or operated by sofware would fail with the turn of the millennium, since their clocks could lose synchronization by not recognizing a number (instruction) with three zeros. A positive outcome of this scare was the creation of several Computer Emergency Response Teams (CERTs) around the world that now work - operatively to exchange expertise and information, and to coordinate in case major problems should arise in the modern IT environment. Te terrorist attacks of 11 September 2001 raised security concerns to a new level. Te - ternational community responded on at least two fronts; one front being the transfer of reliable information via secure networks and the other being the collection of information about - tential terrorists. As a sign of this new emphasis on security, since 2001, all major academic publishers have started technical journals focused on security, and every major communi- tions conference (for example, Globecom and ICC) has organized workshops and sessions on security issues. In addition, the IEEE has created a technical committee on Communication and Information Security. Te ?rst editor was intimately involved with security for the Athens Olympic Games of 2004.
Download or read book NETWORKING 2011 written by Jordi Domingo-Pascual and published by Springer Science & Business Media. This book was released on 2011-04-28 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Applications of Data Mining in Computer Security written by Daniel Barbará and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining is becoming a pervasive technology in activities as diverse as using historical data to predict the success of a marketing campaign, looking for patterns in financial transactions to discover illegal activities or analyzing genome sequences. From this perspective, it was just a matter of time for the discipline to reach the important area of computer security. Applications Of Data Mining In Computer Security presents a collection of research efforts on the use of data mining in computer security. Applications Of Data Mining In Computer Security concentrates heavily on the use of data mining in the area of intrusion detection. The reason for this is twofold. First, the volume of data dealing with both network and host activity is so large that it makes it an ideal candidate for using data mining techniques. Second, intrusion detection is an extremely critical activity. This book also addresses the application of data mining to computer forensics. This is a crucial area that seeks to address the needs of law enforcement in analyzing the digital evidence.
Download or read book Handbook of Research on Machine and Deep Learning Applications for Cyber Security written by Ganapathi, Padmavathi and published by IGI Global. This book was released on 2019-07-26 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the advancement of technology continues, cyber security continues to play a significant role in todays world. With society becoming more dependent on the internet, new opportunities for virtual attacks can lead to the exposure of critical information. Machine and deep learning techniques to prevent this exposure of information are being applied to address mounting concerns in computer security. The Handbook of Research on Machine and Deep Learning Applications for Cyber Security is a pivotal reference source that provides vital research on the application of machine learning techniques for network security research. While highlighting topics such as web security, malware detection, and secure information sharing, this publication explores recent research findings in the area of electronic security as well as challenges and countermeasures in cyber security research. It is ideally designed for software engineers, IT specialists, cybersecurity analysts, industrial experts, academicians, researchers, and post-graduate students.
Download or read book Recent Advances in Intrusion Detection written by Andreas Wespi and published by Springer Science & Business Media. This book was released on 2002-10-02 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Practical Machine Learning A New Look at Anomaly Detection written by Ted Dunning and published by "O'Reilly Media, Inc.". This book was released on 2014-07-21 with total page 65 pages. Available in PDF, EPUB and Kindle. Book excerpt: Finding Data Anomalies You Didn't Know to Look For Anomaly detection is the detective work of machine learning: finding the unusual, catching the fraud, discovering strange activity in large and complex datasets. But, unlike Sherlock Holmes, you may not know what the puzzle is, much less what “suspects” you’re looking for. This O’Reilly report uses practical examples to explain how the underlying concepts of anomaly detection work. From banking security to natural sciences, medicine, and marketing, anomaly detection has many useful applications in this age of big data. And the search for anomalies will intensify once the Internet of Things spawns even more new types of data. The concepts described in this report will help you tackle anomaly detection in your own project. Use probabilistic models to predict what’s normal and contrast that to what you observe Set an adaptive threshold to determine which data falls outside of the normal range, using the t-digest algorithm Establish normal fluctuations in complex systems and signals (such as an EKG) with a more adaptive probablistic model Use historical data to discover anomalies in sporadic event streams, such as web traffic Learn how to use deviations in expected behavior to trigger fraud alerts
Download or read book Industrial Control Systems Security and Resiliency written by Craig Rieger and published by Springer Nature. This book was released on 2019-08-29 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of the key concerns as well as research challenges in designing secure and resilient Industrial Control Systems (ICS). It will discuss today's state of the art security architectures and couple it with near and long term research needs that compare to the baseline. It will also establish all discussions to generic reference architecture for ICS that reflects and protects high consequence scenarios. Significant strides have been made in making industrial control systems secure. However, increasing connectivity of ICS systems with commodity IT devices and significant human interaction of ICS systems during its operation regularly introduces newer threats to these systems resulting in ICS security defenses always playing catch-up. There is an emerging consensus that it is very important for ICS missions to survive cyber-attacks as well as failures and continue to maintain a certain level and quality of service. Such resilient ICS design requires one to be proactive in understanding and reasoning about evolving threats to ICS components, their potential effects on the ICS mission’s survivability goals, and identify ways to design secure resilient ICS systems. This book targets primarily educators and researchers working in the area of ICS and Supervisory Control And Data Acquisition (SCADA) systems security and resiliency. Practitioners responsible for security deployment, management and governance in ICS and SCADA systems would also find this book useful. Graduate students will find this book to be a good starting point for research in this area and a reference source.
Download or read book Game Theory and Machine Learning for Cyber Security written by Charles A. Kamhoua and published by John Wiley & Sons. This book was released on 2021-09-08 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: GAME THEORY AND MACHINE LEARNING FOR CYBER SECURITY Move beyond the foundations of machine learning and game theory in cyber security to the latest research in this cutting-edge field In Game Theory and Machine Learning for Cyber Security, a team of expert security researchers delivers a collection of central research contributions from both machine learning and game theory applicable to cybersecurity. The distinguished editors have included resources that address open research questions in game theory and machine learning applied to cyber security systems and examine the strengths and limitations of current game theoretic models for cyber security. Readers will explore the vulnerabilities of traditional machine learning algorithms and how they can be mitigated in an adversarial machine learning approach. The book offers a comprehensive suite of solutions to a broad range of technical issues in applying game theory and machine learning to solve cyber security challenges. Beginning with an introduction to foundational concepts in game theory, machine learning, cyber security, and cyber deception, the editors provide readers with resources that discuss the latest in hypergames, behavioral game theory, adversarial machine learning, generative adversarial networks, and multi-agent reinforcement learning. Readers will also enjoy: A thorough introduction to game theory for cyber deception, including scalable algorithms for identifying stealthy attackers in a game theoretic framework, honeypot allocation over attack graphs, and behavioral games for cyber deception An exploration of game theory for cyber security, including actionable game-theoretic adversarial intervention detection against advanced persistent threats Practical discussions of adversarial machine learning for cyber security, including adversarial machine learning in 5G security and machine learning-driven fault injection in cyber-physical systems In-depth examinations of generative models for cyber security Perfect for researchers, students, and experts in the fields of computer science and engineering, Game Theory and Machine Learning for Cyber Security is also an indispensable resource for industry professionals, military personnel, researchers, faculty, and students with an interest in cyber security.
Download or read book Anomaly Detection written by and published by BoD – Books on Demand. This book was released on 2024-01-17 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book AI Enabled Threat Detection and Security Analysis for Industrial IoT written by Hadis Karimipour and published by Springer Nature. This book was released on 2021-08-03 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: This contributed volume provides the state-of-the-art development on security and privacy for cyber-physical systems (CPS) and industrial Internet of Things (IIoT). More specifically, this book discusses the security challenges in CPS and IIoT systems as well as how Artificial Intelligence (AI) and Machine Learning (ML) can be used to address these challenges. Furthermore, this book proposes various defence strategies, including intelligent cyber-attack and anomaly detection algorithms for different IIoT applications. Each chapter corresponds to an important snapshot including an overview of the opportunities and challenges of realizing the AI in IIoT environments, issues related to data security, privacy and application of blockchain technology in the IIoT environment. This book also examines more advanced and specific topics in AI-based solutions developed for efficient anomaly detection in IIoT environments. Different AI/ML techniques including deep representation learning, Snapshot Ensemble Deep Neural Network (SEDNN), federated learning and multi-stage learning are discussed and analysed as well. Researchers and professionals working in computer security with an emphasis on the scientific foundations and engineering techniques for securing IIoT systems and their underlying computing and communicating systems will find this book useful as a reference. The content of this book will be particularly useful for advanced-level students studying computer science, computer technology, cyber security, and information systems. It also applies to advanced-level students studying electrical engineering and system engineering, who would benefit from the case studies.
Download or read book Dynamic Networks and Cyber Security written by Niall Adams and published by World Scientific. This book was released on 2016-03-22 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: As an under-studied area of academic research, the analysis of computer network traffic data is still in its infancy. However, the challenge of detecting and mitigating malicious or unauthorised behaviour through the lens of such data is becoming an increasingly prominent issue. This collection of papers by leading researchers and practitioners synthesises cutting-edge work in the analysis of dynamic networks and statistical aspects of cyber security. The book is structured in such a way as to keep security application at the forefront of discussions. It offers readers easy access into the area of data analysis for complex cyber-security applications, with a particular focus on temporal and network aspects. Chapters can be read as standalone sections and provide rich reviews of the latest research within the field of cyber-security. Academic readers will benefit from state-of-the-art descriptions of new methodologies and their extension to real practical problems while industry professionals will appreciate access to more advanced methodology than ever before. Contents:Network Attacks and the Data They Affect (M Morgan, J Sexton, J Neil, A Ricciardi & J Theimer)Cyber-Security Data Sources for Dynamic Network Research (A D Kent)Modelling User Behaviour in a Network Using Computer Event Logs (M J M Turcotte, N A Heard & A D Kent)Network Services as Risk Factors: A Genetic Epidemiology Approach to Cyber-Security (S Gil)Community Detection and Role Identification in Directed Networks: Understanding the Twitter Network of the Care.Data Debate (B Amor, S Vuik, R Callahan, A Darzi, S N Yaliraki & M Barahona)Anomaly Detection for Cyber Security Applications (P Rubin-Delanchy, D J Lawson & N A Heard)Exponential Random Graph Modelling of Static and Dynamic Social Networks (A Caimo)Hierarchical Dynamic Walks (A V Mantzaris, P Grindrod & D J Higham)Temporal Reachability in Dynamic Networks (A Hagberg, N Lemons & S Misra) Readership: Researchers and practitioners in dynamic network analysis and cyber-security. Key Features:Detailed descriptions of the behaviour of attackersDiscussions of new public domain data sources, including data quality issuesA collection of papers introducing novel methodology for cyber-data analysis
