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Full Description
The integration of new technologies is resulting in an increased demand for security and authentication in all types of data communications. Cybersecurity is the protection of networks and systems from theft. Biometric technologies use unique traits of particular parts of the body such facial recognition, iris, fingerprints and voice to identify individuals' physical and behavioural characteristics. Although there are many challenges associated with extracting, storing and processing such data, biometric and cybersecurity technologies along with artificial intelligence (AI) are offering new approaches to verification procedures and mitigating security risks.
This book presents cutting-edge research on the use of AI for biometrics and cybersecurity including machine and deep learning architectures, emerging applications and ethical and legal concerns. Topics include federated learning for enhanced cybersecurity; artificial intelligence-based biometric authentication using ECG signal; deep learning for email phishing detection methods; biometrics for secured IoT systems; intelligent authentication using graphical one-time-passwords; and AI in social cybersecurity.
Artificial Intelligence for Biometrics and Cybersecurity: Technology and applications is aimed at artificial intelligence, biometrics and cybersecurity experts, industry and academic researchers, network security engineers, cybersecurity professionals, and advanced students and newcomers to the field interested in the newest advancements in artificial intelligence for cybersecurity and biometrics.
Contents
Chapter 1: Introduction
Chapter 2: AI in biometrics and cybersecurity
Chapter 3: Biometric security performance: analysis methods and tools for evaluation and assessment
Chapter 4: Leveraging generative adversarial networks and federated learning for enhanced cybersecurity: a concise review
Chapter 5: A survey on face recognition methods with federated leaning
Chapter 6: Artificial intelligence-based biometric authentication using ECG signal
Chapter 7: A comparative analysis of email phishing detection methods: a deep learning perspective
Chapter 8: Securing hardware coprocessors against piracy using biometrics for secured IoT systems
Chapter 9: Intelligent authentication system using graphical one-time passwords
Chapter 10: Role of AI in social cybersecurity: real-world case studies
Chapter 11: Ethical and privacy concerns and challenges
Chapter 12: Conclusion
