@article{1441943,
      recid = {1441943},
      author = {Makkar, Aaisha, and Kumar, Neeraj},
      title = {Deep learning for security and privacy preservation in IoT  /},
      pages = {1 online resource (1 volume) :},
      abstract = {This book addresses the issues with privacy and security  in Internet of things (IoT) networks which are susceptible  to cyber-attacks and proposes deep learning-based  approaches using artificial neural networks models to  achieve a safer and more secured IoT environment. Due to  the inadequacy of existing solutions to cover the entire  IoT network security spectrum, the book utilizes artificial  neural network models, which are used to classify,  recognize, and model complex data including images, voice,  and text, to enhance the level of security and privacy of  IoT. This is applied to several IoT applications which  include wireless sensor networks (WSN), meter reading  transmission in smart grid, vehicular ad hoc networks  (VANET), industrial IoT and connected networks. The book  serves as a reference for researchers, academics, and  network engineers who want to develop enhanced security and  privacy features in the design of IoT systems.},
      url = {http://library.usi.edu/record/1441943},
      doi = {https://doi.org/10.1007/978-981-16-6186-0},
}