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Advanced Machine Learning, AI, and Cybersecurity in Web3

Advanced Machine Learning, AI, and Cybersecurity in Web3
Author: Hadj Ahmed Bouarara
Publisher:
Total Pages: 0
Release: 2024-08-23
Genre: Computers
ISBN: 9781668486863

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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.


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

Download Advanced Machine Learning, AI, and Cybersecurity in Web3: Theoretical Knowledge and Practical Application Book in PDF, ePub and Kindle

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.


Artificial Intelligence and Cyber Security in Industry 4.0

Artificial Intelligence and Cyber Security in Industry 4.0
Author: Velliangiri Sarveshwaran
Publisher: Springer Nature
Total Pages: 374
Release: 2023-07-15
Genre: Computers
ISBN: 9819921155

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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. ​


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, 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


Deep Learning Applications for Cyber Security

Deep Learning Applications for Cyber Security
Author: Mamoun Alazab
Publisher: Springer
Total Pages: 246
Release: 2019-08-14
Genre: Computers
ISBN: 3030130576

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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.


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.


Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection

Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection
Author: Shilpa Mahajan
Publisher: John Wiley & Sons
Total Pages: 373
Release: 2024-06-12
Genre: Computers
ISBN: 139419644X

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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.


Artificial Intelligence in Cyber Security: Theories and Applications

Artificial Intelligence in Cyber Security: Theories and Applications
Author: Tushar Bhardwaj
Publisher: Springer Nature
Total Pages: 144
Release: 2023-11-10
Genre: Technology & Engineering
ISBN: 3031285816

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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.