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On Lightweight Method for Intrusions Detection in the Internet of Things

Shakhov, Vladimir; Jan, Sana Ullah; Ahmed, Saeed; Koo, Insoo

Authors

Vladimir Shakhov

Saeed Ahmed

Insoo Koo



Abstract

Integration of the internet into the entities of the different domains of human society is emerging as a new paradigm called the Internet of Things. At the same time, the ubiquitous and wide-range systems make them prone to attacks. Security experts have warned of the potential risk of huge numbers of unsecured devices united into the global ubiquitous system. To unlock the potential of Internet of Things it needs to improve the security of applications. An intrusion detection mechanism is an important element of security paradigm. However conventional intrusion detection methods are expected to fail, because many user devices have constrained resources. In this paper, we consider a lightweight attack detection strategy utilizing machine learning techniques, which is appropriate for low-resource IoT devices.

Presentation Conference Type Conference Paper (Published)
Conference Name 2019 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom)
Start Date Jun 3, 2019
End Date Jun 6, 2019
Online Publication Date Aug 26, 2019
Publication Date 2019
Deposit Date Oct 21, 2022
Publisher Institute of Electrical and Electronics Engineers
Book Title 2019 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom)
DOI https://doi.org/10.1109/blackseacom.2019.8812813
Keywords intrusion detection, Internet of Things, wireless sensor networks, machine learning
Public URL http://researchrepository.napier.ac.uk/Output/2937027