Automated Secure Computing for Next-Generation Systems

  • 9h 34m
  • Amit Kumar Tyagi
  • John Wiley & Sons (US)
  • 2024

AUTOMATED SECURE COMPUTING FOR NEXT-GENERATION SYSTEMS

This book provides cutting-edge chapters on machine-empowered solutions for next-generation systems for today’s society.

Security is always a primary concern for each application and sector. In the last decade, many techniques and frameworks have been suggested to improve security (data, information, and network). Due to rapid improvements in industry automation, however, systems need to be secured more quickly and efficiently.

It is important to explore the best ways to incorporate the suggested solutions to improve their accuracy while reducing their learning cost. During implementation, the most difficult challenge is determining how to exploit AI and ML algorithms for improved safe service computation while maintaining the user’s privacy. The robustness of AI and deep learning, as well as the reliability and privacy of data, is an important part of modern computing. It is essential to determine the security issues of using AI to protect systems or ML-based automated intelligent systems. To enforce them in reality, privacy would have to be maintained throughout the implementation process. This book presents groundbreaking applications related to artificial intelligence and machine learning for more stable and privacy-focused computing.

By reflecting on the role of machine learning in information, cyber, and data security, Automated Secure Computing for Next-Generation Systems outlines recent developments in the security domain with artificial intelligence, machine learning, and privacy-preserving methods and strategies. To make computation more secure and confidential, the book provides ways to experiment, conceptualize, and theorize about issues that include AI and machine learning for improved security and preserve privacy in next-generation-based automated and intelligent systems. Hence, this book provides a detailed description of the role of AI, ML, etc., in automated and intelligent systems used for solving critical issues in various sectors of modern society.

Audience

Researchers in information technology, robotics, security, privacy preservation, and data mining. The book is also suitable for postgraduate and upper-level undergraduate students.

About the Author

Amit Kumar Tyagi, PhD, is an assistant professor, at the National Institute of Fashion Technology, New Delhi, India. He has published more than 100 papers in refereed international journals, conferences, and books. He has filed more than 20 national and international patents in the areas of deep learning, Internet of Things, cyber-physical systems, and computer vision. His current research focuses on smart and secure computing and privacy, amongst other interests.

In this Book

  • Digital Twin Technology—Necessity of the Future in Education and Beyond
  • An Intersection Between Machine Learning, Security, and Privacy
  • Decentralized, Distributed Computing for Internet of Things-Based Cloud Applications
  • Artificial Intelligence–Blockchain-Enabled–Internet of Things-Based Cloud Applications for Next-Generation Society
  • Artificial Intelligence for Cyber Security—Current Trends and Future Challenges
  • An Automatic Artificial Intelligence System for Malware Detection
  • Early Detection of Darknet Traffic in Internet of Things Applications
  • A Novel and Efficient Approach to Detect Vehicle Insurance Claim Fraud Using Machine Learning Techniques
  • Automated Secure Computing for Fraud Detection in Financial Transactions
  • Data Anonymization on Biometric Security Using Iris Recognition Technology
  • Analysis of Data Anonymization Techniques in Biometric Authentication System
  • Detection of Bank Fraud Using Machine Learning Techniques
  • An Internet of Things-Integrated Home Automation with Smart Security System
  • An Automated Home Security System Using Secure Message Queue Telemetry Transport Protocol
  • Machine Learning-Based Solutions for Internet of Things-Based Applications
  • Machine Learning-Based Intelligent Power Systems
  • Quantum Computation, Quantum Information, and Quantum Key Distribution
  • Quantum Computing, Qubits with Artificial Intelligence, and Blockchain Technologies—A Roadmap for the Future
  • Qubits, Quantum Bits, and Quantum Computing—The Future of Computer Security System
  • Future Technologies for Industry 5.0 and Society 5.0
  • Futuristic Technologies for Smart Manufacturing—Research Statement and Vision for the Future
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