Detecting crypto-ransomware in IoT networks based on energy consumption footprint

Azmoodeh, A., Dehghantanha, A. orcid.org/0000-0002-9294-7554, Conti, M. et al. (1 more author) (2017) Detecting crypto-ransomware in IoT networks based on energy consumption footprint. Journal of Ambient Intelligence and Humanized Computing. ISSN 1868-5137

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Copyright, Publisher and Additional Information: © The Author(s) 2017. This article is an open access publication. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Keywords: Ransomware detection; Power consumption; Internet of Things security; Machine learning; Malware detection; Android
Dates:
  • Published (online): 23 August 2017
  • Accepted: 28 July 2017
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 12 Mar 2018 10:53
Last Modified: 12 Mar 2018 10:53
Published Version: https://doi.org/10.1007/s12652-017-0558-5
Status: Published online
Publisher: Springer
Refereed: Yes
Identification Number: https://doi.org/10.1007/s12652-017-0558-5

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