On Lightweight Method for Intrusions Detection in the Internet of Things

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

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.

Citation

Shakhov, V., Jan, S. U., Ahmed, S., & Koo, I. (2019, June). On Lightweight Method for Intrusions Detection in the Internet of Things. Presented at 2019 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom), Sochi, Russia

• 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