Deep Learning Strategies for Security Enhancement in Wireless Sensor Networks

Deep Learning Strategies for Security Enhancement in Wireless Sensor Networks
ePUB
  • eBook:
    Deep Learning Strategies for Security Enhancement in Wireless Sensor Networks
  • Author:
    K. Martin Sagayam, Bharat Bhushan, A. Diana Andrushia, Victor Hugo C. de Albuquerque
  • Edition:
    1 edition
  • Categories:
  • Data:
    June 12, 2020
  • ISBN:
    1799850684
  • ISBN-13:
    9781799850687
  • Language:
    English
  • Pages:
    405 pages
  • Format:
    ePUB

Book Description
Wireless sensor networks have gained significant attention industrially and academically due to their wide range of uses in various fields. Because of their vast amount of applications, wireless sensor networks are vulnerable to a variety of security attacks. The protection of wireless sensor networks remains a challenge due to their resource-constrained nature, which is why researchers have begun applying several branches of artificial intelligence to advance the security of these networks. Research is needed on the development of security practices in wireless sensor networks by using smart technologies.
Deep Learning Strategies for Security Enhancement in Wireless Sensor Networks provides emerging research exploring the theoretical and practical advancements of security protocols in wireless sensor networks using artificial intelligence-based techniques. Featuring coverage on a broad range of topics such as clustering protocols, intrusion detection, and energy harvesting, this book is ideally designed for researchers, developers, IT professionals, educators, policymakers, practitioners, scientists, theorists, engineers, academicians, and students seeking current research on integrating intelligent techniques into sensor networks for more reliable security practices.

Content

Chapter 1. Introducing Machine Learning to Wireless Sensor Networks
Chapter 2. Secured Energy-Efficient Routing in Wireless Sensor Networks Using Machine Learning Algorithm
Chapter 3. Security and Privacy Challenges of Deep Learning
Chapter 4. Wireless Environment Security
Chapter 5. Modelling a Deep Learning-Based Wireless Sensor Network Task Assignment Algorithm
Chapter 6. The Threat of Intelligent Attackers Using Deep Learning
Chapter 7. Attacks, Vulnerabilities, and Their Countermeasures in Wireless Sensor Networks
Chapter 8. Recent Trends in Channel Assignment Techniques in Wireless Mesh Networks
Chapter 9. Integrated Intrusion Detection System (IDS) for Security Enhancement in Wireless Sensor Networks
Chapter 10. A Speed Control-Based Big Data Collection Algorithm (SCBDCA) Using Clusters and Portable Sink WSNs
Chapter 11. Analysis of Black-Hole Attack With Its Mitigation Techniques in Ad-hoc Network
Chapter 12. Fundamentals of Wireless Sensor Networks Using Machine Learning Approaches
Chapter 13. Security in Rail IoT Systems
Chapter 14. The Internet of Things in the Russian Federation
Chapter 15. Artificial Intelligence and SHGs
Chapter 16. Applicability of WSN and Biometric Models in the Field of Healthcare
Chapter 17. Augmented Data Prediction Efficiency for Wireless Sensor Network Application by AI-ML Technology

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