A Deep Recurrent Neural Network Based Approach for Internet of Things Malware Threat Hunting

HaddadPajouh, H., Dehghantanha, A orcid.org/0000-0002-9294-7554, Khayami, R. et al. (1 more author) (2018) A Deep Recurrent Neural Network Based Approach for Internet of Things Malware Threat Hunting. Future Generation Computer Systems. ISSN 0167-739X

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Copyright, Publisher and Additional Information: © 2018 Elsevier. This is an author produced version of a paper subsequently published in Future Generation Computer Systems. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: ARM-based IoT malware detection; IoT malware detection; Long short term memory; Machine learning; OpCodes analysis; Deep learning threat hunting
Dates:
  • Published (online): 17 March 2018
  • Accepted: 4 March 2018
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 11:57
Last Modified: 17 Mar 2019 01:39
Published Version: https://doi.org/10.1016/j.future.2018.03.007
Status: Published online
Publisher: Elsevier
Refereed: Yes
Identification Number: https://doi.org/10.1016/j.future.2018.03.007

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