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April 20, 2026, 9:16 a.m.
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SOURCE: Rehman F. Emerging Trends in Information System Security Using AI...2025
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COVER
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MEDIAINFO
Textbook in PDF format This book is a comprehensive exploration into the intersection of cutting-edge technologies and the critical domain of cybersecurity; this book delves deep into the evolving landscape of cyber threats and the imperative for innovative solutions. From establishing the fundamental principles of cyber security to scrutinizing the latest advancements in AI and Machine Learning, each chapter offers invaluable insights into bolstering defenses against contemporary threats. Readers are guided through a journey that traverses the realms of cyber analytics, threat analysis, and the safeguarding of information systems in an increasingly interconnected world. With chapters dedicated to exploring the role of AI in securing IoT devices, employing supervised and unsupervised learning techniques for threat classification, and harnessing the power of recurrent neural networks for time series analysis, this book presents a holistic view of the evolving cybersecurity landscape. Moreover, it highlights the importance of next-generation defense mechanisms, such as generative adversarial networks (GANs) and federated learning techniques, in combating sophisticated cyber threats while preserving privacy. This book is a comprehensive guide to integrating AI and Data Science into modern cybersecurity strategies. It covers topics like anomaly detection, behaviour analysis, and threat intelligence, and advocates for proactive risk mitigation using AI and data science. The book provides practical applications, ethical considerations, and customizable frameworks for implementing next-gen cyber defense strategies. It bridges theory with practice, offering real-world case studies, innovative methodologies, and continuous learning resources to equip readers with the knowledge and tools to mitigate cyber threats. With the proliferation of internet-connected devices and the ongoing digitization initiatives undertaken by organizations, there has been a significant surge in cyber-attacks in recent years. The increase in cyber threats demands a fundamental change in cyber security measures, prompting an extensive review of Artificial Intelligence (AI) use. This survey explores the domains of Machine Learning (ML), Deep Learning (DL), and Natural Language Processing (NLP) in the field of cyber security, illustrating their complex roles and contributions. The paper investigates the latest developments in ML, highlighting its ability to adapt, the complex layers of DL, and the linguistic intelligence of NLP. The paper explores Machine Learning to detect known risks and Deep Learning to tackle complicated challenges. It then smoothly transitions into discussing the linguistic analysis of NLP in many cyber security fields. Nevertheless, incorporating AI presents challenges, such as financial issues, potential risks associated with generative AI, and ethical deliberations. This study guides cyber security specialists in navigating the ever-changing realm of AI applications. It offers valuable information to strengthen digital defenses against emerging threats. Preface AI-Drivceen Modern Cybersecurity Approach: A Systematic Literature Revie Cyber Security in the Post Quantum Computer Era: Threats and Perspectives Deep Neural Network for DoS Detection in Wireless Sensors Networks Survey on IoT Security Threats Application and Architectures Lightweight Cryptography Algorithms for IoT Devices Guarding the Digital Gateway: An In-Depth Analysis of Cybersecurity Challenges in India Predictive Modeling for Food Security Assessment Using Synthetic Minority Over-Sampling Technique Exploring the Secure Unleashing of Digital Potential: A Study on How Cloud Security Works Together with Digital Transformation in Financial Institutions of Pakistan Reviewing Theoretical Perspectives on IT Governance and Compliance in Banking: Insights from US Regulatory Frameworks Overcoming Challenges and Implementing Effective Information Security Policies for Remote Work Environments Generative Adversarial Networks (GAN) Insights for Cyber Security Applications Gen-Cybersecurity and Information Systems Securit
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