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Published by Associated Publishing Company, 2018
ISBN 10: 8185211663 ISBN 13: 9788185211664
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Published by Academic Press 2022-06-21, 2022
ISBN 10: 0323858457 ISBN 13: 9780323858458
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Published by Emerald Publishing Limited, 2026
ISBN 10: 1836086032 ISBN 13: 9781836086031
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Published by Emerald Publishing Limited, 2026
ISBN 10: 1836086032 ISBN 13: 9781836086031
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Published by Emerald Publishing Limited, 2026
ISBN 10: 1836086032 ISBN 13: 9781836086031
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ISBN 10: 1836086032 ISBN 13: 9781836086031
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Published by Emerald Publishing Limited, 2026
ISBN 10: 1836086032 ISBN 13: 9781836086031
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Published by The Institution of Engineering and Technology, 2025
ISBN 10: 1839537574 ISBN 13: 9781839537578
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Published by The Institution of Engineering and Technology, 2025
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Published by Emerald Publishing Limited, 2026
ISBN 10: 1836086032 ISBN 13: 9781836086031
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Published by Emerald Publishing Limited, 2026
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Published by The Institution of Engineering and Technology, 2025
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Published by Institution of Engineering and Technology, GB, 2025
ISBN 10: 1837240310 ISBN 13: 9781837240319
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Hardback. Condition: New. As AI technologies progress and influence more facets of our lives, the requirement for openness and interpretability becomes increasingly important. Explainable AI (XAI) has the potential to be a paradigm shift in the next generation of AI systems. XAI strives to make AI algorithms and methods understandable by tackling trust, bias, compliance, and accountability challenges. XAI improves model disclosure, produces intrinsically interpretable deep learning approaches, offers real-time rationales, and promotes legitimate AI practice. These advances assist in the development of a more ethically sound AI ecosystem. As the IoT evolves and supply chains become more complex, novel avenues for attack arise. The ever-changing threat landscape includes powerful adversaries such as malicious actors and hackers who are always refining their strategies, and demand ongoing monitoring and adaptive responses. Cybersecurity helps safeguard data, identify fraud, protect vital infrastructure, and ensure confidentiality. Considering the dynamic nature of the cybersecurity battlefront, a holistic approach must include pre-emptive threat intelligence, staff training, effective security tools, regular upgrades, and global collaboration. Explainable AI (XAI) explains security alerts, reduces false positives and enables faster incident response. The objective of this book is to explore how the integration of XAI-based cybersecurity algorithms and methods support threat detection and decision-making by preserving privacy and trust, ensuring interpretability and accountability, and optimizing computational and communication costs. This book will be a useful reference for computing and security researchers, scientists, and IT professionals in academia and industry, who are developing and designing innovative cyber threat and vulnerability detection systems and solutions, as well as advanced students and lecturers to better understand AI and XAI algorithms for cybersecurity applications.
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Published by The Institution of Engineering and Technology, 2025
ISBN 10: 1839537574 ISBN 13: 9781839537578
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Condition: New. 1st edition NO-PA16APR2015-KAP.