Download Free Dynamic Network And Cyber Security Book in PDF and EPUB Free Download. You can read online Dynamic Network And Cyber Security and write the review.

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.
Cyber-Security Threats, Actors, and Dynamic Mitigation provides both a technical and state-of-the-art perspective as well as a systematic overview of the recent advances in different facets of cyber-security. It covers the methodologies for modeling attack strategies used by threat actors targeting devices, systems, and networks such as smart homes, critical infrastructures, and industrial IoT. With a comprehensive review of the threat landscape, the book explores both common and sophisticated threats to systems and networks. Tools and methodologies are presented for precise modeling of attack strategies, which can be used both proactively in risk management and reactively in intrusion prevention and response systems. Several contemporary techniques are offered ranging from reconnaissance and penetration testing to malware detection, analysis, and mitigation. Advanced machine learning-based approaches are also included in the area of anomaly-based detection, that are capable of detecting attacks relying on zero-day vulnerabilities and exploits. Academics, researchers, and professionals in cyber-security who want an in-depth look at the contemporary aspects of the field will find this book of interest. Those wanting a unique reference for various cyber-security threats and how they are detected, analyzed, and mitigated will reach for this book often.
Cyber-security is a matter of rapidly growing importance in industry and government. This book provides insight into a range of data science techniques for addressing these pressing concerns.The application of statistical and broader data science techniques provides an exciting growth area in the design of cyber defences. Networks of connected devices, such as enterprise computer networks or the wider so-called Internet of Things, are all vulnerable to misuse and attack, and data science methods offer the promise to detect such behaviours from the vast collections of cyber traffic data sources that can be obtained. In many cases, this is achieved through anomaly detection of unusual behaviour against understood statistical models of normality.This volume presents contributed papers from an international conference of the same name held at Imperial College. Experts from the field have provided their latest discoveries and review state of the art technologies.
Networks as sets of autonomous organisations working together to achieve individual and shared goals are becoming increasingly important across many areas of public administration. The importance of networks is well known but most analysts would agree that we do not know enough about the dynamics and effectiveness of networks in relation to their internal operations. This is a significant problem as security, intelligence, law enforcement and many other agencies are increasingly required to organise in and through networks to provide national security. In this comprehensive analysis, Chad Whelan presents a highly innovative, qualitative study of networks in the field of national security. Developing our understanding of 'organisational networks' in organisational theory, management and public administration, and 'security networks' in criminology and international relations, he presents a multi-disciplinary analysis of network forms of organisation. Whelan puts forward a methodological framework involving five levels of analysis - structural, cultural, policy, technological and relational - with which we can better analyse and understand the dynamics and effectiveness of networks. This framework is applied to public sector networks operating in the field of counter-terrorism in Australia in a way that is highly relevant to researchers and practitioners in many contexts where government departments and agencies, and the private sector, need to work together. Networks and National Security: Dynamics, Effectiveness and Organisation not only advances our knowledge of networks and national security but also assists with the essential tasks of evaluating and managing networks. Written in a clear and accessible style and featuring a wealth of first-hand accounts concerning the inside operations of networks, this book deals with the crucial subject of inter-agency coordination in the important field of national security.
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.
This book discusses and summarizes current research issues, identifies challenges, and outlines future directions for proactive and dynamic network defense. This book also presents the latest fundamental research results toward understanding proactive and dynamic network defense by top researchers in related areas. It includes research results that offer formal frameworks to define proactive and dynamic network defense, and develop novel models to analyze and evaluate proactive designs and strategies in computer systems, network systems, cyber-physical systems and wireless networks. A wide variety of scientific techniques have been highlighted to study these problems in the fundamental domain. As the convergence of our physical and digital worlds grows fast pace, protecting information systems from being tampered or unauthorized access is becoming one of the most importance issues. The traditional mechanisms of network defense are built upon a static, passive, and reactive nature, which has insufficient to defend against today's attackers that attempt to persistently analyze, probe, circumvent or fool such mechanisms. It has not yet been fully investigated to address the early stage of “cyber kill chain” when adversaries carry out sophisticated reconnaissance to plan attacks against a defense system. Recently, proactive and dynamic network defense has been proposed as an important alternative towards comprehensive network defense. Two representative types of such defense are moving target defense (MTD) and deception-based techniques. These emerging approaches show great promise to proactively disrupt the cyber-attack kill chain and are increasingly gaining interest within both academia and industry. However, these approaches are still in their preliminary design stage. Despite the promising potential, there are research issues yet to be solved regarding the effectiveness, efficiency, costs and usability of such approaches. In addition, it is also necessary to identify future research directions and challenges, which is an essential step towards fully embracing proactive and dynamic network defense. This book will serve as a great introduction for advanced-level computer science and engineering students who would like to start R&D efforts in the field of proactive and dynamic network defense. Researchers and professionals who work in this related field will also find this book useful as a reference.
Covering attack detection, malware response, algorithm and mechanism design, privacy, and risk management, this comprehensive work applies unique quantitative models derived from decision, control, and game theories to understanding diverse network security problems. It provides the reader with a system-level theoretical understanding of network security, and is essential reading for researchers interested in a quantitative approach to key incentive and resource allocation issues in the field. It also provides practitioners with an analytical foundation that is useful for formalising decision-making processes in network security.
This book is a select collection of edited papers from the International Conference on Security of Information and Networks (SIN 2007) on the main theme of Information Assurance, Security, and Public Policy. SIN 2007 was hosted by the Eastern Mediterranean University in Gazimagusa, North Cyprus and co-organized by the Istanbul Technical University, Turkey. While SIN 2007 covered all areas of information and network security, the papers included here focused on the following topics: - cryptology: design and analysis of cryptographic algorithms, hardware and software implementations of cryptographic algorithms, and steganography; - network security: authentication, authorization and access control, privacy, intrusion detection, grid security, and mobile and personal area networks; - IT governance: information security management systems, risk and threat analysis, and information security policies. They represent an interesting mix of innovative academic research and experience reports from practitioners. This is further complemented by a number of invited papers providing excellent overviews: - Elisabeth Oswald, University of Bristol, Bristol, UK: Power Analysis Attack: A Very Brief Introduction; - Marc Joye, Thomson R&D, France: On White-Box Cryptography; - Bart Preneel, Katholieke Universiteit Leuven, Leuven, Belgium: Research Challenges in Cryptology; - Mehmet Ufuk Caglayan, Bogazici University, Turkey: Secure Routing in Ad Hoc Networks and Model Checking. The papers are organized in a logical sequence covering Ciphers; Mobile Agents & Networks; Access Control and Security Assurance; Attacks, Intrusion Detection, and Security Recommendations; and, Security Software, Performance, and Experience.
There is increasing pressure to protect computer networks against unauthorized intrusion, and some work in this area is concerned with engineering systems that are robust to attack. However, no system can be made invulnerable. Data Analysis for Network Cyber-Security focuses on monitoring and analyzing network traffic data, with the intention of preventing, or quickly identifying, malicious activity.Such work involves the intersection of statistics, data mining and computer science. Fundamentally, network traffic is relational, embodying a link between devices. As such, graph analysis approaches are a natural candidate. However, such methods do not scale well to the demands of real problems, and the critical aspect of the timing of communications events is not accounted for in these approaches.This book gathers papers from leading researchers to provide both background to the problems and a description of cutting-edge methodology. The contributors are from diverse institutions and areas of expertise and were brought together at a workshop held at the University of Bristol in March 2013 to address the issues of network cyber security. The workshop was supported by the Heilbronn Institute for Mathematical Research.
The goal of this SpringerBrief is to collect and systematically present the state-of-the-art in this research field and the underlying game-theoretic and learning tools to the broader audience with general network security and engineering backgrounds. Particularly, the exposition of this book begins with a brief introduction of relevant background knowledge in Chapter 1, followed by a review of existing applications of SG in addressing various dynamic network security problems in Chapter 2. A detailed treatment of dynamic security games with information asymmetry is given in Chapters 3–5. Specifically, dynamic security games with extra information that concerns security competitions, where the defender has an informational advantage over the adversary are discussed in Chapter 3. The complementary scenarios where the defender lacks information about the adversary is examined in Chapter 4 through the lens of incomplete information SG. Chapter 5 is devoted to the exploration of how to proactively create information asymmetry for the defender’s benefit. The primary audience for this brief includes network engineers interested in security decision-making in dynamic network security problems. Researchers interested in the state-of-the-art research on stochastic game theory and its applications in network security will be interested in this SpringerBrief as well. Also graduate and undergraduate students interested in obtaining comprehensive information on stochastic game theory and applying it to address relevant research problems can use this SpringerBrief as a study guide. Lastly, concluding remarks and our perspective for future works are presented in Chapter 6.