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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.

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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, AdnanORCID iD for 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

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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.