Machine Learning For Cyber Security
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Machine Learning For Cyber Security
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Author : Preeti Malik
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2022-12-05
Machine Learning For Cyber Security written by Preeti Malik and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-05 with Business & Economics categories.
This book shows how machine learning (ML) methods can be used to enhance cyber security operations, including detection, modeling, monitoring as well as defense against threats to sensitive data and security systems. Filling an important gap between ML and cyber security communities, it discusses topics covering a wide range of modern and practical ML techniques, frameworks and tools.
Cyber Security Meets Machine Learning
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Author : Xiaofeng Chen
language : en
Publisher: Springer Nature
Release Date : 2021-07-02
Cyber Security Meets Machine Learning written by Xiaofeng Chen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-02 with Computers categories.
Machine learning boosts the capabilities of security solutions in the modern cyber environment. However, there are also security concerns associated with machine learning models and approaches: the vulnerability of machine learning models to adversarial attacks is a fatal flaw in the artificial intelligence technologies, and the privacy of the data used in the training and testing periods is also causing increasing concern among users. This book reviews the latest research in the area, including effective applications of machine learning methods in cybersecurity solutions and the urgent security risks related to the machine learning models. The book is divided into three parts: Cyber Security Based on Machine Learning; Security in Machine Learning Methods and Systems; and Security and Privacy in Outsourced Machine Learning. Addressing hot topics in cybersecurity and written by leading researchers in the field, the book features self-contained chapters to allow readers to select topics that are relevant to their needs. It is a valuable resource for all those interested in cybersecurity and robust machine learning, including graduate students and academic and industrial researchers, wanting to gain insights into cutting-edge research topics, as well as related tools and inspiring innovations.
Explainable Artificial Intelligence For Cyber Security
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Author : Mohiuddin Ahmed
language : en
Publisher: Springer Nature
Release Date : 2022-04-18
Explainable Artificial Intelligence For Cyber Security written by Mohiuddin Ahmed and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-18 with Computers categories.
This book presents that explainable artificial intelligence (XAI) is going to replace the traditional artificial, machine learning, deep learning algorithms which work as a black box as of today. To understand the algorithms better and interpret the complex networks of these algorithms, XAI plays a vital role. In last few decades, we have embraced AI in our daily life to solve a plethora of problems, one of the notable problems is cyber security. In coming years, the traditional AI algorithms are not able to address the zero-day cyber attacks, and hence, to capitalize on the AI algorithms, it is absolutely important to focus more on XAI. Hence, this book serves as an excellent reference for those who are working in cyber security and artificial intelligence.
Game Theory And Machine Learning For Cyber Security
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Author : Charles A. Kamhoua
language : en
Publisher: John Wiley & Sons
Release Date : 2021-09-15
Game Theory And Machine Learning For Cyber Security written by Charles A. Kamhoua 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 2021-09-15 with Technology & Engineering categories.
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.
Artificial Intelligence And Machine Learning In Cyber Security
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Author : Mark Hayward
language : en
Publisher: Mark Hayward
Release Date : 2025-06-06
Artificial Intelligence And Machine Learning In Cyber Security written by Mark Hayward and has been published by Mark Hayward this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-06 with Computers categories.
Artificial Intelligence (AI) refers to the development of computer systems that can perform tasks typically requiring human intelligence. These tasks include understanding language, recognizing patterns, solving problems, and making decisions. AI systems can process vast amounts of data quickly and adapt their responses based on new information, which makes them particularly valuable in monitoring and responding to cyber threats. Machine Learning (ML), a subset of AI, focuses specifically on algorithms that enable computers to learn from data without being explicitly programmed for every specific task. In recent years, AI and ML have gained widespread attention for their potential to dramatically enhance cybersecurity defenses
Machine Learning For Cyber Agents
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Author : Stanislav Abaimov
language : en
Publisher: Springer Nature
Release Date : 2022-01-27
Machine Learning For Cyber Agents written by Stanislav Abaimov and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-27 with Computers categories.
The cyber world has been both enhanced and endangered by AI. On the one hand, the performance of many existing security services has been improved, and new tools created. On the other, it entails new cyber threats both through evolved attacking capacities and through its own imperfections and vulnerabilities. Moreover, quantum computers are further pushing the boundaries of what is possible, by making machine learning cyber agents faster and smarter. With the abundance of often-confusing information and lack of trust in the diverse applications of AI-based technologies, it is essential to have a book that can explain, from a cyber security standpoint, why and at what stage the emerging, powerful technology of machine learning can and should be mistrusted, and how to benefit from it while avoiding potentially disastrous consequences. In addition, this book sheds light on another highly sensitive area – the application of machine learning for offensive purposes, an aspect that is widely misunderstood, under-represented in the academic literature and requires immediate expert attention.
Machine Learning For Computer And Cyber Security
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Author : Brij B. Gupta
language : en
Publisher: CRC Press
Release Date : 2019-02-05
Machine Learning For Computer And Cyber Security written by Brij B. Gupta and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-05 with Computers categories.
While Computer Security is a broader term which incorporates technologies, protocols, standards and policies to ensure the security of the computing systems including the computer hardware, software and the information stored in it, Cyber Security is a specific, growing field to protect computer networks (offline and online) from unauthorized access, botnets, phishing scams, etc. Machine learning is a branch of Computer Science which enables computing machines to adopt new behaviors on the basis of observable and verifiable data and information. It can be applied to ensure the security of the computers and the information by detecting anomalies using data mining and other such techniques. This book will be an invaluable resource to understand the importance of machine learning and data mining in establishing computer and cyber security. It emphasizes important security aspects associated with computer and cyber security along with the analysis of machine learning and data mining based solutions. The book also highlights the future research domains in which these solutions can be applied. Furthermore, it caters to the needs of IT professionals, researchers, faculty members, scientists, graduate students, research scholars and software developers who seek to carry out research and develop combating solutions in the area of cyber security using machine learning based approaches. It is an extensive source of information for the readers belonging to the field of Computer Science and Engineering, and Cyber Security professionals. Key Features: This book contains examples and illustrations to demonstrate the principles, algorithms, challenges and applications of machine learning and data mining for computer and cyber security. It showcases important security aspects and current trends in the field. It provides an insight of the future research directions in the field. Contents of this book help to prepare the students for exercising better defense in terms of understanding the motivation of the attackers and how to deal with and mitigate the situation using machine learning based approaches in better manner.
Machine Learning In Cyber Trust
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Author : Jeffrey J. P. Tsai
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-04-05
Machine Learning In Cyber Trust written by Jeffrey J. P. Tsai 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 2009-04-05 with Computers categories.
Many networked computer systems are far too vulnerable to cyber attacks that can inhibit their functioning, corrupt important data, or expose private information. Not surprisingly, the field of cyber-based systems is a fertile ground where many tasks can be formulated as learning problems and approached in terms of machine learning algorithms. This book contains original materials by leading researchers in the area and covers applications of different machine learning methods in the reliability, security, performance, and privacy issues of cyber space. It enables readers to discover what types of learning methods are at their disposal, summarizing the state-of-the-practice in this significant area, and giving a classification of existing work. Those working in the field of cyber-based systems, including industrial managers, researchers, engineers, and graduate and senior undergraduate students will find this an indispensable guide in creating systems resistant to and tolerant of cyber attacks.
Adversary Aware Learning Techniques And Trends In Cybersecurity
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Author : Prithviraj Dasgupta
language : en
Publisher: Springer Nature
Release Date : 2021-01-22
Adversary Aware Learning Techniques And Trends In Cybersecurity written by Prithviraj Dasgupta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-22 with Computers categories.
This book is intended to give researchers and practitioners in the cross-cutting fields of artificial intelligence, machine learning (AI/ML) and cyber security up-to-date and in-depth knowledge of recent techniques for improving the vulnerabilities of AI/ML systems against attacks from malicious adversaries. The ten chapters in this book, written by eminent researchers in AI/ML and cyber-security, span diverse, yet inter-related topics including game playing AI and game theory as defenses against attacks on AI/ML systems, methods for effectively addressing vulnerabilities of AI/ML operating in large, distributed environments like Internet of Things (IoT) with diverse data modalities, and, techniques to enable AI/ML systems to intelligently interact with humans that could be malicious adversaries and/or benign teammates. Readers of this book will be equipped with definitive information on recent developments suitable for countering adversarial threats in AI/ML systems towards making them operate in a safe, reliable and seamless manner.
Modern Approaches In Iot And Machine Learning For Cyber Security
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Author : Vinit Kumar Gunjan
language : en
Publisher: Springer Nature
Release Date : 2023-12-07
Modern Approaches In Iot And Machine Learning For Cyber Security written by Vinit Kumar Gunjan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-07 with Technology & Engineering categories.
This book examines the cyber risks associated with Internet of Things (IoT) and highlights the cyber security capabilities that IoT platforms must have in order to address those cyber risks effectively. The chapters fuse together deep cyber security expertise with artificial intelligence (AI), machine learning, and advanced analytics tools, which allows readers to evaluate, emulate, outpace, and eliminate threats in real time. The book’s chapters are written by experts of IoT and machine learning to help examine the computer-based crimes of the next decade. They highlight on automated processes for analyzing cyber frauds in the current systems and predict what is on the horizon. This book is applicable for researchers and professionals in cyber security, AI, and IoT.