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Understanding AI in Cybersecurity and Secure AI : Challenges, Strategies and Trends / by Dilli Prasad Sharma, Arash Habibi Lashkari, Mahdi Daghmehchi Firoozjaei, Samaneh Mahdavifar, Pulei Xiong

By: Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Progress in ISPublisher: Cham : Springer Nature Switzerland, 2025Publisher: Cham : Imprint: Springer, 2025Description: 1 Online-Ressource (XIV, 250 p. 50 illus., 43 illus. in color.)ISBN:
  • 9783031915246
Other title:
  • Artificial intelligence
Subject(s): Additional physical formats: 9783031915239 | 9783031915253 | 9783031915260 | Erscheint auch als: 9783031915239 Druck-Ausgabe | Erscheint auch als: 9783031915253 Druck-Ausgabe | Erscheint auch als: 9783031915260 Druck-Ausgabe | Erscheint auch als: Understanding AI in Cybersecurity and Secure AI. Druck-Ausgabe Cham : Springer International Publishing AG, 2025. 250 SeitenDDC classification:
  • 658.05 23
DOI: DOI: 10.1007/978-3-031-91524-6Online resources: Summary: Part I: General -- Chapter 1: Why AI and Security? -- Chapter 2: Understanding AI and ML -- Part II: AI in Security -- Chapter 3: AI in Security -- Chapter 4: AI for Network Security -- Chapter 5: AI for Software Security -- Chapter 6: AI for Cloud Security -- Chapter 7: AI for IoT and OT Security -- Part III: Secure AI -- Chapter 8: AI Security and Privacy -- Chapter 9: Defense Methods for Adversarial Attacks and Privacy Issues in Secure AI -- Chapter 10: General Framework for AI Security and Privacy -- Chapter 11: AI Safety and Fairness -- Chapter 12: AI Security Challenges, Opportunities and Future Work -- Chapter 13: Conclusion.Summary: This book presents an overview of the emerging topics in Artificial Intelligence (AI) and cybersecurity and addresses the latest AI models that could be potentially applied to a range of cybersecurity areas. Furthermore, it provides different techniques of how to make the AI algorithms secure from adversarial attacks. The book presents the cyber threat landscape and explains the various spectrums of AI and the applications and limitations of AI in cybersecurity. Moreover, it explores the applications and limitations of secure AI. The authors discuss the three categories of machine learning (ML) models and reviews cutting-edge recent Deep Learning (DL) models. Furthermore, the book provides a general AI framework in security as well as different modules of the framework; similarly, chapter four proposes a general framework for secure AI. It explains different aspects of network security including malware and attacks. The book also includes a comprehensive study of various scopes of application security; categorised into three groups of smartphone, web application, and desktop application and delves into the concepts of cloud security. The authors discuss state-of-the-art Internet of Things (IoT) security and describe various challenges of AI for cybersecurity, such as data diversity, model customising, explainability, and time complexity and includes some future work. They provide a comprehensive understanding of adversarial machine learning including the up-to-date adversarial attacks and defences. The book finishes off with a discussion of the challenges and future work in secure AI. Overall, this book covers applications of AI models to various fields of cybersecurity and appeals not only to an scholarly audience but also to professionals wanting to learn more about the new developments in these areas.PPN: PPN: 1927327644Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-BUM | ZDB-2-SXBM
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