Dynamically Enabled Cyber Defense
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| Author | : Lin Yang |
| Publisher | : World Scientific |
| Total Pages | : 389 |
| Release | : 2021-06-08 |
| Genre | : Computers |
| ISBN | : 9811234353 |
The book puts forward dynamically enabled cyber defense technology as a solution to the system homogenization problem. Based on the hierarchy of the protected information system entity, the book elaborates on current mainstream dynamic defense technologies from four aspects: the internal hardware platform, software service, information data and external network communication. It also ascertains their possible evolution routes, clarifies their relationship with existing security products, and makes macro analyses and discussions on security gain and overall system efficiency of these technologies.This book can be used as both a textbook for graduate courses related to electronic information as well as a reference for scientific researchers engaged in relevant research. It helps graduate students majoring in electronics and information sciences to gain an understanding in dynamically-enabled cyber defense. Scientists and engineers specialising in network security research should also find this book to be a useful guide on recent developments in network security.
| Author | : Nicholas Kolokotronis |
| Publisher | : CRC Press |
| Total Pages | : 392 |
| Release | : 2021-04-04 |
| Genre | : Computers |
| ISBN | : 100036660X |
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.
| Author | : Niall M Adams |
| Publisher | : World Scientific |
| Total Pages | : 222 |
| Release | : 2016-03-22 |
| Genre | : Computers |
| ISBN | : 1786340763 |
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.
| Author | : Andrew A. Bochman |
| Publisher | : CRC Press |
| Total Pages | : 232 |
| Release | : 2021-01-20 |
| Genre | : Political Science |
| ISBN | : 1000292975 |
Countering Cyber Sabotage: Introducing Consequence-Driven, Cyber-Informed Engineering (CCE) introduces a new methodology to help critical infrastructure owners, operators and their security practitioners make demonstrable improvements in securing their most important functions and processes. Current best practice approaches to cyber defense struggle to stop targeted attackers from creating potentially catastrophic results. From a national security perspective, it is not just the damage to the military, the economy, or essential critical infrastructure companies that is a concern. It is the cumulative, downstream effects from potential regional blackouts, military mission kills, transportation stoppages, water delivery or treatment issues, and so on. CCE is a validation that engineering first principles can be applied to the most important cybersecurity challenges and in so doing, protect organizations in ways current approaches do not. The most pressing threat is cyber-enabled sabotage, and CCE begins with the assumption that well-resourced, adaptive adversaries are already in and have been for some time, undetected and perhaps undetectable. Chapter 1 recaps the current and near-future states of digital technologies in critical infrastructure and the implications of our near-total dependence on them. Chapters 2 and 3 describe the origins of the methodology and set the stage for the more in-depth examination that follows. Chapter 4 describes how to prepare for an engagement, and chapters 5-8 address each of the four phases. The CCE phase chapters take the reader on a more granular walkthrough of the methodology with examples from the field, phase objectives, and the steps to take in each phase. Concluding chapter 9 covers training options and looks towards a future where these concepts are scaled more broadly.
| Author | : Prabhakar, G. |
| Publisher | : IGI Global |
| Total Pages | : 513 |
| Release | : 2024-08-01 |
| Genre | : Computers |
| ISBN | : |
In the digital age, smart grids stand as the backbone of modern energy systems, facilitating efficient energy distribution and management. However, this sophistication comes at the cost of heightened vulnerability to cyber threats. Standing on the precipice of a hyper-connected future, the inadequacies of current cybersecurity measures loom large, demanding urgent attention from academic scholars and industry experts. 5G and Fiber Optics Security Technologies for Smart Grid Cyber Defense addresses the challenges of securing smart grid systems through communication technologies. The book navigates through 5G wireless and fiber optics, offering a nuanced understanding of their application in the context of grid security. The book begins by exploring the inherent vulnerabilities in smart grid architecture and the imperative role of cybersecurity in modern energy systems. Subsequently, it delves into the specifics of 5G network architectures, dissecting the technologies and standards underpinning the new radio (NR) while emphasizing the significance of network slicing and security isolation. Concurrently, the book unveils the intricacies of fiber optic communication in smart grids, elucidating network design, security measures, and integrating fiber optic sensors for grid monitoring and intrusion detection.
| Author | : Xiaofeng Chen |
| Publisher | : Springer Nature |
| Total Pages | : 411 |
| Release | : 2019-09-11 |
| Genre | : Computers |
| ISBN | : 3030306194 |
This book constitutes the proceedings of the Second International Conference on Machine Learning for Cyber Security, ML4CS 2019, held in Xi’an, China in September 2019. The 23 revised full papers and 3 short papers presented were carefully reviewed and selected from 70 submissions. The papers detail all aspects of machine learning in network infrastructure security, in network security detections and in application software security.
| Author | : National Academies of Sciences, Engineering, and Medicine |
| Publisher | : National Academies Press |
| Total Pages | : 99 |
| Release | : 2020-01-27 |
| Genre | : Computers |
| ISBN | : 0309494508 |
In recent years, interest and progress in the area of artificial intelligence (AI) and machine learning (ML) have boomed, with new applications vigorously pursued across many sectors. At the same time, the computing and communications technologies on which we have come to rely present serious security concerns: cyberattacks have escalated in number, frequency, and impact, drawing increased attention to the vulnerabilities of cyber systems and the need to increase their security. In the face of this changing landscape, there is significant concern and interest among policymakers, security practitioners, technologists, researchers, and the public about the potential implications of AI and ML for cybersecurity. The National Academies of Sciences, Engineering, and Medicine convened a workshop on March 12-13, 2019 to discuss and explore these concerns. This publication summarizes the presentations and discussions from the workshop.
| Author | : Jhanjhi, Noor Zaman |
| Publisher | : IGI Global |
| Total Pages | : 546 |
| Release | : 2024-09-12 |
| Genre | : Computers |
| ISBN | : |
As cyber threats become increasingly sophisticated, the need for innovative defense strategies becomes urgent. Generative artificial intelligence (AI) offers a revolutionary approach to enhance cybersecurity. By utilizing advanced algorithms, data analysis, and machine learning, generative AI can simulate complex attack scenarios, identify vulnerabilities, and develop proactive defense mechanisms while adapting to modern-day cyber-attacks. AI strengthens current organizational security while offering quick, effective responses to emerging threats. Decisive strategies are needed to integrate generative AI into businesses defense strategies and protect organizations from attacks, secure digital data, and ensure safe business processes. Utilizing Generative AI for Cyber Defense Strategies explores the utilization of generative AI tools in organizational cyber security and defense. Strategies for effective threat detection and mitigation are presented, with an emphasis on deep learning, artificial intelligence, and Internet of Things (IoT) technology. This book covers topics such as cyber security, threat intelligence, and behavior analysis, and is a useful resource for computer engineers, security professionals, business owners, government officials, data analysts, academicians, scientists, and researchers.
| Author | : Charles A. Kamhoua |
| Publisher | : John Wiley & Sons |
| Total Pages | : 546 |
| Release | : 2021-09-08 |
| Genre | : Technology & Engineering |
| ISBN | : 1119723949 |
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.
| Author | : Takako Izumi |
| Publisher | : Springer Nature |
| Total Pages | : 283 |
| Release | : |
| Genre | : |
| ISBN | : 9819718600 |
