Download or read book Advanced Machine Learning AI and Cybersecurity in Web3 Theoretical Knowledge and Practical Application written by Bouarara, Hadj Ahmed and published by IGI Global. This book was released on 2024-08-23 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the evolving landscape of Web3, the use of advanced machine learning, artificial intelligence, and cybersecurity transforms industries through theoretical exploration and practical application. The integration of advanced machine learning and AI techniques promises enhanced security protocols, predictive analytics, and adaptive defenses against the increasing number of cyber threats. However, these technological improvements also raise questions regarding privacy, transparency, and the ethical implications of AI-driven security measures. Advanced Machine Learning, AI, and Cybersecurity in Web3: Theoretical Knowledge and Practical Application explores theories and applications of improved technological techniques in Web 3.0. It addresses the challenges inherent to decentralization while harnessing the benefits offered by advances, thereby paving the way for a safer and more advanced digital era. Covering topics such as fraud detection, cryptocurrency, and data management, this book is a useful resource for computer engineers, financial institutions, security and IT professionals, business owners, researchers, scientists, and academicians.

Download or read book ADVANCED MACHINE LEARNING AI AND CYBERSECURITY IN WEB3 written by HADJ AHMED. BOUARARA and published by . This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Artificial Intelligence and Cyber Security in Industry 4 0 written by Velliangiri Sarveshwaran and published by Springer Nature. This book was released on 2023-07-15 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides theoretical background and state-of-the-art findings in artificial intelligence and cybersecurity for industry 4.0 and helps in implementing AI-based cybersecurity applications. Machine learning-based security approaches are vulnerable to poison datasets which can be caused by a legitimate defender's misclassification or attackers aiming to evade detection by contaminating the training data set. There also exist gaps between the test environment and the real world. Therefore, it is critical to check the potentials and limitations of AI-based security technologies in terms of metrics such as security, performance, cost, time, and consider how to incorporate them into the real world by addressing the gaps appropriately. This book focuses on state-of-the-art findings from both academia and industry in big data security relevant sciences, technologies, and applications. ​

Download or read book Artificial Intelligence for Cybersecurity written by Mark Stamp and published by Springer Nature. This book was released on 2022-07-15 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores new and novel applications of machine learning, deep learning, and artificial intelligence that are related to major challenges in the field of cybersecurity. The provided research goes beyond simply applying AI techniques to datasets and instead delves into deeper issues that arise at the interface between deep learning and cybersecurity. This book also provides insight into the difficult "how" and "why" questions that arise in AI within the security domain. For example, this book includes chapters covering "explainable AI", "adversarial learning", "resilient AI", and a wide variety of related topics. It’s not limited to any specific cybersecurity subtopics and the chapters touch upon a wide range of cybersecurity domains, ranging from malware to biometrics and more. Researchers and advanced level students working and studying in the fields of cybersecurity (equivalently, information security) or artificial intelligence (including deep learning, machine learning, big data, and related fields) will want to purchase this book as a reference. Practitioners working within these fields will also be interested in purchasing this book.

Download or read book AI Machine Learning and Deep Learning written by Fei Hu and published by CRC Press. This book was released on 2023-06-05 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today, Artificial Intelligence (AI) and Machine Learning/ Deep Learning (ML/DL) have become the hottest areas in information technology. In our society, many intelligent devices rely on AI/ML/DL algorithms/tools for smart operations. Although AI/ML/DL algorithms and tools have been used in many internet applications and electronic devices, they are also vulnerable to various attacks and threats. AI parameters may be distorted by the internal attacker; the DL input samples may be polluted by adversaries; the ML model may be misled by changing the classification boundary, among many other attacks and threats. Such attacks can make AI products dangerous to use. While this discussion focuses on security issues in AI/ML/DL-based systems (i.e., securing the intelligent systems themselves), AI/ML/DL models and algorithms can actually also be used for cyber security (i.e., the use of AI to achieve security). Since AI/ML/DL security is a newly emergent field, many researchers and industry professionals cannot yet obtain a detailed, comprehensive understanding of this area. This book aims to provide a complete picture of the challenges and solutions to related security issues in various applications. It explains how different attacks can occur in advanced AI tools and the challenges of overcoming those attacks. Then, the book describes many sets of promising solutions to achieve AI security and privacy. The features of this book have seven aspects: This is the first book to explain various practical attacks and countermeasures to AI systems Both quantitative math models and practical security implementations are provided It covers both "securing the AI system itself" and "using AI to achieve security" It covers all the advanced AI attacks and threats with detailed attack models It provides multiple solution spaces to the security and privacy issues in AI tools The differences among ML and DL security and privacy issues are explained Many practical security applications are covered

Download or read book Deep Learning Applications for Cyber Security written by Mamoun Alazab and published by Springer. This book was released on 2019-08-14 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cybercrime remains a growing challenge in terms of security and privacy practices. Working together, deep learning and cyber security experts have recently made significant advances in the fields of intrusion detection, malicious code analysis and forensic identification. This book addresses questions of how deep learning methods can be used to advance cyber security objectives, including detection, modeling, monitoring and analysis of as well as defense against various threats to sensitive data and security systems. Filling an important gap between deep learning and cyber security communities, it discusses topics covering a wide range of modern and practical deep learning techniques, frameworks and development tools to enable readers to engage with the cutting-edge research across various aspects of cyber security. The book focuses on mature and proven techniques, and provides ample examples to help readers grasp the key points.

Download or read book Advanced Smart Computing Technologies in Cybersecurity and Forensics written by Keshav Kaushik and published by CRC Press. This book was released on 2021-12-15 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the topics related to artificial intelligence, the Internet of Things, blockchain technology, and machine learning. It brings together researchers, developers, practitioners, and users interested in cybersecurity and forensics. The first objective is to learn and understand the need for and impact of advanced cybersecurity and forensics and its implementation with multiple smart computational technologies. This objective answers why and how cybersecurity and forensics have evolved as one of the most promising and widely-accepted technologies globally and has widely-accepted applications. The second objective is to learn how to use advanced cybersecurity and forensics practices to answer computational problems where confidentiality, integrity, and availability are essential aspects to handle and answer. This book is structured in such a way so that the field of study is relevant to each reader’s major or interests. It aims to help each reader see the relevance of cybersecurity and forensics to their career or interests. This book intends to encourage researchers to develop novel theories to enrich their scholarly knowledge to achieve sustainable development and foster sustainability. Readers will gain valuable knowledge and insights about smart computing technologies using this exciting book. This book: • Includes detailed applications of cybersecurity and forensics for real-life problems • Addresses the challenges and solutions related to implementing cybersecurity in multiple domains of smart computational technologies • Includes the latest trends and areas of research in cybersecurity and forensics • Offers both quantitative and qualitative assessments of the topics Includes case studies that will be helpful for the researchers Prof. Keshav Kaushik is Assistant Professor in the Department of Systemics, School of Computer Science at the University of Petroleum and Energy Studies, Dehradun, India. Dr. Shubham Tayal is Assistant Professor at SR University, Warangal, India. Dr. Akashdeep Bhardwaj is Professor (Cyber Security & Digital Forensics) at the University of Petroleum & Energy Studies (UPES), Dehradun, India. Dr. Manoj Kumar is Assistant Professor (SG) (SoCS) at the University of Petroleum and Energy Studies, Dehradun, India.

Download or read book Artificial Intelligence and Cybersecurity written by Ishaani Priyadarshini and published by CRC Press. This book was released on 2022-02-04 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence and cybersecurity are two emerging fields that have made phenomenal contributions toward technological advancement. As cyber-attacks increase, there is a need to identify threats and thwart attacks. This book incorporates recent developments that artificial intelligence brings to the cybersecurity world. Artificial Intelligence and Cybersecurity: Advances and Innovations provides advanced system implementation for Smart Cities using artificial intelligence. It addresses the complete functional framework workflow and explores basic and high-level concepts. The book is based on the latest technologies covering major challenges, issues and advances, and discusses intelligent data management and automated systems. This edited book provides a premier interdisciplinary platform for researchers, practitioners and educators. It presents and discusses the most recent innovations, trends and concerns as well as practical challenges and solutions adopted in the fields of artificial intelligence and cybersecurity.

Download or read book Securing the Future Cybersecurity Strategies with AI ML and Generative AI written by Purshotam Singh Yadav and published by JEC PUBLICATION. This book was released on with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: .....

Download or read book Artificial Intelligence in Cyber Security Theories and Applications written by Tushar Bhardwaj and published by Springer Nature. This book was released on 2023-11-10 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights the applications and theory of artificial intelligence in the domain of cybersecurity. The book proposes new approaches and ideas to present applications of innovative approaches in real-time environments. In the past few decades, there has been an exponential rise in the application of artificial intelligence technologies (such as deep learning, machine learning, blockchain) for solving complex and intricate problems arising in the domain of cybersecurity. The versatility of these techniques has made them a favorite among scientists and researchers working in diverse areas. This book serves as a reference for young scholars, researchers, and industry professionals working in the field of Artificial Intelligence and Cybersecurity.

Download or read book Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection written by Shilpa Mahajan and published by John Wiley & Sons. This book was released on 2024-06-12 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensive resource providing strategic defense mechanisms for malware, handling cybercrime, and identifying loopholes using artificial intelligence (AI) and machine learning (ML) Applying Artificial Intelligence in Cyber Security Analytics and Cyber Threat Detection is a comprehensive look at state-of-the-art theory and practical guidelines pertaining to the subject, showcasing recent innovations, emerging trends, and concerns as well as applied challenges encountered, and solutions adopted in the fields of cybersecurity using analytics and machine learning. The text clearly explains theoretical aspects, framework, system architecture, analysis and design, implementation, validation, and tools and techniques of data science and machine learning to detect and prevent cyber threats. Using AI and ML approaches, the book offers strategic defense mechanisms for addressing malware, cybercrime, and system vulnerabilities. It also provides tools and techniques that can be applied by professional analysts to safely analyze, debug, and disassemble any malicious software they encounter. With contributions from qualified authors with significant experience in the field, Applying Artificial Intelligence in Cyber Security Analytics and Cyber Threat Detection explores topics such as: Cybersecurity tools originating from computational statistics literature and pure mathematics, such as nonparametric probability density estimation, graph-based manifold learning, and topological data analysis Applications of AI to penetration testing, malware, data privacy, intrusion detection system (IDS), and social engineering How AI automation addresses various security challenges in daily workflows and how to perform automated analyses to proactively mitigate threats Offensive technologies grouped together and analyzed at a higher level from both an offensive and defensive standpoint Providing detailed coverage of a rapidly expanding field, Applying Artificial Intelligence in Cyber Security Analytics and Cyber Threat Detection is an essential resource for a wide variety of researchers, scientists, and professionals involved in fields that intersect with cybersecurity, artificial intelligence, and machine learning.

Download or read book Artificial Intelligence and Cybersecurity written by Tuomo Sipola and published by Springer Nature. This book was released on 2022-12-07 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses artificial intelligence (AI) and cybersecurity from multiple points of view. The diverse chapters reveal modern trends and challenges related to the use of artificial intelligence when considering privacy, cyber-attacks and defense as well as applications from malware detection to radio signal intelligence. The chapters are contributed by an international team of renown researchers and professionals in the field of AI and cybersecurity. During the last few decades the rise of modern AI solutions that surpass humans in specific tasks has occurred. Moreover, these new technologies provide new methods of automating cybersecurity tasks. In addition to the privacy, ethics and cybersecurity concerns, the readers learn several new cutting edge applications of AI technologies. Researchers working in AI and cybersecurity as well as advanced level students studying computer science and electrical engineering with a focus on AI and Cybersecurity will find this book useful as a reference. Professionals working within these related fields will also want to purchase this book as a reference.

Download or read book AI Tools for Protecting and Preventing Sophisticated Cyber Attacks written by Babulak, Eduard and published by IGI Global. This book was released on 2023-08-10 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ubiquity and pervasive access to internet resources 24/7 by anyone from anywhere is enabling access to endless professional, educational, technical, business, industrial, medical, and government resources worldwide. To guarantee internet integrity and availability with confidentiality, the provision of proper and effective cyber security is critical for any organization across the world. AI Tools for Protecting and Preventing Sophisticated Cyber Attacks illuminates the most effective and practical applications of artificial intelligence (AI) in securing critical cyber infrastructure and internet communities worldwide. The book presents a collection of selected peer-reviewed chapters addressing the most important issues, technical solutions, and future research directions in cyber security. Covering topics such as assessment metrics, information security, and toolkits, this premier reference source is an essential resource for cyber security experts, cyber systems administrators, IT experts, internet and computer network professionals, organizational leaders, students and educators of higher education, researchers, and academicians.

Download or read book AI and Machine Learning for Network and Security Management written by Yulei Wu and published by John Wiley & Sons. This book was released on 2022-11-08 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI AND MACHINE LEARNING FOR NETWORK AND SECURITY MANAGEMENT Extensive Resource for Understanding Key Tasks of Network and Security Management AI and Machine Learning for Network and Security Management covers a range of key topics of network automation for network and security management, including resource allocation and scheduling, network planning and routing, encrypted traffic classification, anomaly detection, and security operations. In addition, the authors introduce their large-scale intelligent network management and operation system and elaborate on how the aforementioned areas can be integrated into this system, plus how the network service can benefit. Sample ideas covered in this thought-provoking work include: How cognitive means, e.g., knowledge transfer, can help with network and security management How different advanced AI and machine learning techniques can be useful and helpful to facilitate network automation How the introduced techniques can be applied to many other related network and security management tasks Network engineers, content service providers, and cybersecurity service providers can use AI and Machine Learning for Network and Security Management to make better and more informed decisions in their areas of specialization. Students in a variety of related study programs will also derive value from the work by gaining a base understanding of historical foundational knowledge and seeing the key recent developments that have been made in the field.

Download or read book Machine Learning Safety written by Xiaowei Huang and published by Springer Nature. This book was released on 2023-04-28 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning algorithms allow computers to learn without being explicitly programmed. Their application is now spreading to highly sophisticated tasks across multiple domains, such as medical diagnostics or fully autonomous vehicles. While this development holds great potential, it also raises new safety concerns, as machine learning has many specificities that make its behaviour prediction and assessment very different from that for explicitly programmed software systems. This book addresses the main safety concerns with regard to machine learning, including its susceptibility to environmental noise and adversarial attacks. Such vulnerabilities have become a major roadblock to the deployment of machine learning in safety-critical applications. The book presents up-to-date techniques for adversarial attacks, which are used to assess the vulnerabilities of machine learning models; formal verification, which is used to determine if a trained machine learning model is free of vulnerabilities; and adversarial training, which is used to enhance the training process and reduce vulnerabilities. The book aims to improve readers’ awareness of the potential safety issues regarding machine learning models. In addition, it includes up-to-date techniques for dealing with these issues, equipping readers with not only technical knowledge but also hands-on practical skills.

Download or read book Practical AI for Cybersecurity written by Ravi Das and published by CRC Press. This book was released on 2021-02-26 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: The world of cybersecurity and the landscape that it possesses is changing on a dynamic basis. It seems like that hardly one threat vector is launched, new variants of it are already on the way. IT Security teams in businesses and corporations are struggling daily to fight off any cyberthreats that they are experiencing. On top of this, they are also asked by their CIO or CISO to model what future Cyberattacks could potentially look like, and ways as to how the lines of defenses can be further enhanced. IT Security teams are overburdened and are struggling to find ways in order to keep up with what they are being asked to do. Trying to model the cyberthreat landscape is a very laborious process, because it takes a lot of time to analyze datasets from many intelligence feeds. What can be done to accomplish this Herculean task? The answer lies in Artificial Intelligence (AI). With AI, an IT Security team can model what the future Cyberthreat landscape could potentially look like in just a matter of minutes. As a result, this gives valuable time for them not only to fight off the threats that they are facing, but to also come up with solutions for the variants that will come out later. Practical AI for Cybersecurity explores the ways and methods as to how AI can be used in cybersecurity, with an emphasis upon its subcomponents of machine learning, computer vision, and neural networks. The book shows how AI can be used to help automate the routine and ordinary tasks that are encountered by both penetration testing and threat hunting teams. The result is that security professionals can spend more time finding and discovering unknown vulnerabilities and weaknesses that their systems are facing, as well as be able to come up with solid recommendations as to how the systems can be patched up quickly.

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.