TON_IoT Telemetry Dataset: A New Generation Dataset of IoT and IIoT for Data-Driven Intrusion Detection Systems Alsaedi, A., Moustafa, N., Tari, Z., Mahmood, A. and Anwar, Adnan 2020, TON_IoT Telemetry Dataset: A New Generation Dataset of IoT and IIoT for Data-Driven Intrusion Detection Systems, IEEE ACCESS, vol. 8, pp. 165130-165150, doi: 10.1109/ACCESS.2020.3022862. Attached Files Name Description MIMEType Size Downloads Title TON_IoT Telemetry Dataset: A New Generation Dataset of IoT and IIoT for Data-Driven Intrusion Detection Systems Author(s) Alsaedi, A. Moustafa, N. Tari, Z. Mahmood, A. Anwar, Adnan orcid.org/0000-0003-3916-1381 Journal name IEEE ACCESS Volume number 8 Start page 165130 End page 165150 Total pages 21 Publisher IEEE Place of publication Piscataway, N.J. Publication date 2020 ISSN 2169-3536 Keyword(s) Science & Technology Technology Computer Science, Information Systems Engineering, Electrical & Electronic Telecommunications Computer Science Engineering Intrusion detection Telemetry Sensors Internet of Things Machine learning Australia Internet of Things (IoT) Industrial Internet of Things (IIoT) cybersecurity intrusion detection systems (IDSs) dataset INDUSTRIAL INTERNET ATTACK DETECTION SECURITY THINGS RANSOMWARE ANALYTICS THREAT Language eng DOI 10.1109/ACCESS.2020.3022862 Indigenous content off Field of Research 08 Information and Computing Sciences 09 Engineering 10 Technology HERDC Research category C1 Refereed article in a scholarly journal Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30144065 Document type: Journal Article Collections: Faculty of Science, Engineering and Built Environment School of Information Technology Open Access Collection Related Links Link Description Link to full-text (open access)     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. 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. Versions Version Filter Type Thu, 15 Oct 2020, 09:13:26 EST Thu, 15 Oct 2020, 09:14:19 EST Thu, 15 Oct 2020, 11:07:02 EST Thu, 15 Oct 2020, 11:14:25 EST Mon, 19 Oct 2020, 11:45:41 EST Mon, 19 Oct 2020, 11:47:18 EST Mon, 19 Oct 2020, 15:02:09 EST Filtered Full Citation counts:   Cited 2 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 59 Abstract Views, 0 File Downloads  -  Detailed Statistics Created: Thu, 15 Oct 2020, 09:14:19 EST

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