Deep Learning Strategies for Security Enhancement in Wireless Sensor Networks

Deep Learning Strategies for Security Enhancement in Wireless Sensor Networks

K. Martin Sagayam (Karunya Institute of Technology and Sciences, India), Bharat Bhushan (HMR Institute of Technology and Management, New Delhi, India), A. Diana Andrushia (Karunya Institute of Technology and Sciences, India) and Victor Hugo C. de Albuquerque (Universidade de Fortaleza, Brazil)
Release Date: June, 2020|Copyright: © 2020 |Pages: 405
DOI: 10.4018/978-1-7998-5068-7
ISBN13: 9781799850687|ISBN10: 1799850684|EISBN13: 9781799850694|ISBN13 Softcover: 9781799852759
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Description & Coverage
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.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Clustering Protocols
  • Computational Intelligence
  • Data Integrity
  • Distributed Learning Strategies
  • Energy Harvesting
  • Intrusion Detection
  • Machine Learning
  • Quality of Service
  • Query Processing
  • Sink Mobility
  • Virtualization
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Editor Biographies
Mr. Bharat Bhushan has gracefully worked as Network Engineer in HCL Info systems Ltd. for a year. He is an alumnus as well as a Ph.D. scholar of BITs Mesra. He got numerous international certifications like Cisco Certified Network Associate, Cisco certified network professional Trained, Cisco Certified Entry Networking Technician, Microsoft Certified Technology Specialist, Microsoft Certified IT Professional, Red-hat Certified Engineer.He has published over 100 research papers in highly renowned National/International Journals and Conferences. His publications include 3 SCI Indexed Journals, 3 SCOPUS Indexed book chapters and 37 International conferences indexed by IEEE and Springer. He is currently in the process of editing 4 books to be published by the most famed publishers like Elsevier, IGI Global, and CRC Press. Due to his philosophical vision, he has been given the opportunity of chairing sessions in as many as 7 International conferences of high repute indexed by IEEE and Springer. He has also been invited as a speaker in various national and international conferences.
Victor Hugo C. de Albuquerque has a PhD in Mechanical Engineering with emphasis on Materials from the Federal University of Paraíba (2010), an MSc in Teleinformatics Engineering from the Federal University of Ceará (2007), and he graduated in Mechatronics Technology at the Federal Center of Technological Education of Ceará (2006). He is currently Assistant VI Professor of the Graduate Program in Applied Informatics at the University of Fortaleza (UNIFOR). He has experience in Computer Systems, mainly in the research fields of: Applied Computing, Intelligent Systems, Visualization and Interaction, with specific interest in Pattern Recognition, Artificial Intelligence, Image Processing and Analysis, as well as Automation with respect to biological signal/image processing, image segmentation, biomedical circuits and human/brain-machine interaction, NeuroBiofeedback, Neurorehabilitation, Visual Stimulation, including Augmented and Virtual Reality Simulation Modeling for animals and humans. Additionally, he has research at the microstructural characterization field through the combination of non-destructive techniques with signal/image processing and analysis, and pattern recognition.
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