Strategic Approaches to Intrusion Detection in Cloud–IoT

Future-proof your digital infrastructure with this essential book, which provides a comprehensive exploration of both traditional and advanced machine and deep learning models to implement resilient and intelligent intrusion detection systems for securing complex cloud-IoT environments.

The rapid growth of cloud computing and the Internet of Things has transformed industry by enabling real-time data collection, processing, and automation. However, this increasing interconnectivity also introduces significant security challenges, including data breaches, unauthorized access, and cyber threats. Ensuring the security and privacy of cloud-IoT environments requires advanced intrusion detection mechanisms, privacy-preserving strategies, and efficient resource management. This book explores various advanced methods to achieve these goals, including machine and deep learning models, to protect cloud-IoT systems against cyber threats. This book covers both traditional and advanced techniques to implement intrusion detection systems and provides detailed comparative analysis. By offering practical insights, readers will gain a deeper understanding of how to effectively implement intelligent security solutions, ensuring resilience, privacy, and protection against evolving cyber threats in cloud-IoT environments.

Readers will find the volume:

• Provides comprehensive coverage of topics like machine and deep learning for intelligent security;
• Explores cyber-IoT systems and intrusion detection systems for identifying suspicious activities and mitigating potential threats;
• Discusses various security mechanisms to safeguard the cloud-IoT environment and implement various techniques to detect intrusions early on.

Audience

Research scholars and industry professionals in information technology, artificial intelligence and cybersecurity looking to innovate cybersecurity for cloud computing and IoT.

Partha Ghosh, PhD is an Associate Professor in the Department of Information Technology and the Head of the Department of Computer Science and Business Systems at the Netaji Subhash Engineering College, Kolkata, India. He has published more than 20 research papers in reputed journals and conferences. His research interests include cloud computing, machine learning, intrusion detection systems, optimization techniques, feature selection, computer networks, and security.

Rajdeep Chakraborty, PhD is a Professor in the Computer Science and Engineering Department at Medi-Caps University, Indore, Madhya Pradesh, India with nearly two decades of research and teaching experience. He has made notable contributions through various publications, including patents, books, journal articles, and conference papers. His research interests include cryptography, network security, cybersecurity, IoT, and blockchain.

Anupam Ghosh, PhD is a Professor and Head of the Department of Computer Science and Engineering at Netaji Subhash Engineering College, Kolkata, India with more than 22 years of experience. He has published more than 100 international papers in reputed journals and conferences. His research focuses on AI, machine learning, deep learning, image processing, soft computing, and bioinformatics.

Ahmed A. Elngar, PhD is an Associate Professor and Head of the Computer Science Department in the School of Computers and Artificial Intelligence at Beni-Suef University, Egypt and an Associate Professor of Computer Science in the College of Computer Information Technology at American University in the United Arab Emirates. He has published more than 150 scientific research papers in prestigious international journals and more than 35 books. His research interests include the Internet of Things, network security, intrusion detection, machine learning, data mining, and artificial intelligence.