A sparse protocol parsing method for IIoT protocols based on HMM hybrid model He, Yunhua, Shen, Jialong, Xiao, Ke, Sood, Keshav, Wang, Chao and Sun, Limin 2020, A sparse protocol parsing method for IIoT protocols based on HMM hybrid model, in ICC 2020 : Proceedings of the 2020 IEEE International Conference on Communications, Institute of Electrical and Electronics Engineers, Piscataway, N.J., pp. 1-6, doi: 10.1109/icc40277.2020.9149040. Attached Files Name Description MIMEType Size Downloads Title A sparse protocol parsing method for IIoT protocols based on HMM hybrid model Author(s) He, Yunhua Shen, Jialong Xiao, Ke Sood, Keshav Wang, Chao Sun, Limin Conference name IEEE Communications Society. International Conference (2020 : Online, Ireland) Conference location Online, Ireland Conference dates 2020/06/07 - 2020/06/11 Title of proceedings ICC 2020 : Proceedings of the 2020 IEEE International Conference on Communications Editor(s) [Unknown] Publication date 2020 Series IEEE Communications Society International Conference Start page 1 End page 6 Total pages 6 Publisher Institute of Electrical and Electronics Engineers Place of publication Piscataway, N.J. Keyword(s) Industrial Internet of Things protocol inference genetic algorithm hidden Markov model ISBN 978-1-7281-5089-5 Language eng DOI 10.1109/icc40277.2020.9149040 Indigenous content off HERDC Research category E1 Full written paper - refereed Persistent URL http://hdl.handle.net/10536/DRO/DU:30140687 Document type: Conference Paper Collections: Faculty of Science, Engineering and Built Environment School of Information Technology Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Fri, 07 Aug 2020, 15:03:00 EST Sat, 08 Aug 2020, 05:00:18 EST Tue, 11 Aug 2020, 06:03:33 EST Sat, 29 Aug 2020, 02:41:25 EST Tue, 08 Sep 2020, 12:01:25 EST Tue, 08 Sep 2020, 12:02:58 EST Tue, 08 Sep 2020, 12:03:35 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 52 Abstract Views, 2 File Downloads  -  Detailed Statistics Created: Fri, 07 Aug 2020, 15:03:00 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.