A Bayesian Approach for an Efficient Data Reduction in IoT

Cristanel Razafimandimby, Valeria Loscrì, Anna Maria Vegni, Driss Aourir, Alessandro Neri. A Bayesian Approach for an Efficient Data Reduction in IoT. In Giancarlo Fortino, Carlos E. Palau, Antonio Guerrieri, Nora Cuppens, Frédéric Cuppens, Hakima Chaouchi, Alban Gabillon, editors, Interoperability, Safety and Security in IoT - Third International Conference, InterIoT 2017, and Fourth International Conference, SaSeIot 2017, Valencia, Spain, November 6-7, 2017, Proceedings. Volume 242 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, pages 3-10, Springer, 2017. [doi]

@inproceedings{RazafimandimbyL17-1,
  title = {A Bayesian Approach for an Efficient Data Reduction in IoT},
  author = {Cristanel Razafimandimby and Valeria Loscrì and Anna Maria Vegni and Driss Aourir and Alessandro Neri},
  year = {2017},
  doi = {https://doi.org/10.1007/978-3-319-93797-7_1},
  researchr = {https://researchr.org/publication/RazafimandimbyL17-1},
  cites = {0},
  citedby = {0},
  pages = {3-10},
  booktitle = {Interoperability, Safety and Security in IoT - Third International Conference, InterIoT 2017, and Fourth International Conference, SaSeIot 2017, Valencia, Spain, November 6-7, 2017, Proceedings},
  editor = {Giancarlo Fortino and Carlos E. Palau and Antonio Guerrieri and Nora Cuppens and Frédéric Cuppens and Hakima Chaouchi and Alban Gabillon},
  volume = {242},
  series = {Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering},
  publisher = {Springer},
  isbn = {978-3-319-93797-7},
}