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Advanced Machine Learning, AI, and Cybersecurity in Web3: Theoretical Knowledge and Practical Application

Advanced Machine Learning, AI, and Cybersecurity in Web3: Theoretical Knowledge and Practical Application
Author: Bouarara, Hadj Ahmed
Publisher: IGI Global
Total Pages: 354
Release: 2024-08-23
Genre: Computers
ISBN: 1668486881

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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.


AI, Machine Learning and Deep Learning

AI, Machine Learning and Deep Learning
Author: Fei Hu
Publisher: CRC Press
Total Pages: 347
Release: 2023-06-05
Genre: Computers
ISBN: 1000878872

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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


Artificial Intelligence and Cybersecurity

Artificial Intelligence and Cybersecurity
Author: Ishaani Priyadarshini
Publisher: CRC Press
Total Pages: 222
Release: 2022-02-04
Genre: Technology & Engineering
ISBN: 1000530639

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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.


Artificial Intelligence for Cybersecurity

Artificial Intelligence for Cybersecurity
Author: Mark Stamp
Publisher: Springer Nature
Total Pages: 388
Release: 2022-07-15
Genre: Computers
ISBN: 3030970876

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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.


AI and Machine Learning for Network and Security Management

AI and Machine Learning for Network and Security Management
Author: Yulei Wu
Publisher: John Wiley & Sons
Total Pages: 308
Release: 2022-11-08
Genre: Computers
ISBN: 1119835879

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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.


AI-Enabled Threat Detection and Security Analysis for Industrial IoT

AI-Enabled Threat Detection and Security Analysis for Industrial IoT
Author: Hadis Karimipour
Publisher: Springer Nature
Total Pages: 250
Release: 2021-08-03
Genre: Computers
ISBN: 3030766136

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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.


AI, Blockchain and Self-Sovereign Identity in Higher Education

AI, Blockchain and Self-Sovereign Identity in Higher Education
Author: Hamid Jahankhani
Publisher: Springer Nature
Total Pages: 315
Release: 2023-06-22
Genre: Computers
ISBN: 3031336275

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This book aims to explore the next generation of online learning challenges including the security and privacy issues of digital transformation strategies that is required in teaching and learning. Also, what efforts does the industry need to invest in changing mind-sets and behaviours of both students and faculty members in adoption of virtual and blended learning? The book provides a comprehensive coverage of not only the technical and ethical issues presented by the use of AI, blockchain and self-sovereign identity, but also the adversarial application of AI and its associated implications. The authors recommend a number of novel approaches to assist in better detecting, thwarting and addressing AI challenges in higher education. The book provides a valuable reference for cyber security experts and practitioners, network security professionals and higher education strategist and decision-makers. It is also aimed at researchers seeking to obtain a more profound knowledge of machine learning and deep learning in the context of cyber security and AI in higher education. Each chapter is written by an internationally renowned expert who has extensive experience in industry or academia. Furthermore, this book blends advanced research findings with practice-based methods to provide the reader with advanced understanding and relevant skills.


Modern Approaches in IoT and Machine Learning for Cyber Security

Modern Approaches in IoT and Machine Learning for Cyber Security
Author: Vinit Kumar Gunjan
Publisher: Springer Nature
Total Pages: 415
Release: 2024-01-08
Genre: Technology & Engineering
ISBN: 3031099559

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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.


Machine Learning for Cyber Agents

Machine Learning for Cyber Agents
Author: Stanislav Abaimov
Publisher: Springer Nature
Total Pages: 235
Release: 2022-01-27
Genre: Computers
ISBN: 3030915859

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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.


Implications of Artificial Intelligence for Cybersecurity

Implications of Artificial Intelligence for Cybersecurity
Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
Total Pages: 99
Release: 2020-01-27
Genre: Computers
ISBN: 0309494508

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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.