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Authors: Idris Zakariyya ; M. Omar Al-Kadri ; Harsha Kalutarage and Andrei Petrovski

Affiliation: School of Computing Science and Digital Media, Robert Gordon University, AB10 7JG and U.K.

Keyword(s): Computational Cost, IoT Security, Feature Reduction, Resource Consumption, Machine Learning.

Abstract: Using Machine Learning (ML) for Internet of Things (IoT) security monitoring is a challenge. This is due to their resource constraint nature that limits the deployment of resource-hungry monitoring algorithms. Therefore, the aim of this paper is to investigate resource consumption reduction of ML algorithms in IoT security monitoring. This paper starts with an empirical analysis of resource consumption of Artificial Immune System (AIS) algorithm, and then employs carefully selected feature reduction techniques to reduce the computational cost of running the algorithm. The proposed approach significantly reduces computational cost as illustrated in the paper. We validate our results using two benchmarks and one purposefully simulated data set.

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Paper citation in several formats:
Zakariyya, I. ; Al-Kadri, M. ; Kalutarage, H. and Petrovski, A. (2019). Reducing Computational Cost in IoT Cyber Security: Case Study of Artificial Immune System Algorithm. In Proceedings of the 16th International Joint Conference on e-Business and Telecommunications - SECRYPT; ISBN 978-989-758-378-0; ISSN 2184-3236, SciTePress, pages 523-528. DOI: 10.5220/0008119205230528

@conference{secrypt19,
author={Idris Zakariyya and M. Omar Al{-}Kadri and Harsha Kalutarage and Andrei Petrovski},
title={Reducing Computational Cost in IoT Cyber Security: Case Study of Artificial Immune System Algorithm},
booktitle={Proceedings of the 16th International Joint Conference on e-Business and Telecommunications - SECRYPT},
year={2019},
pages={523-528},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008119205230528},
isbn={978-989-758-378-0},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on e-Business and Telecommunications - SECRYPT
TI - Reducing Computational Cost in IoT Cyber Security: Case Study of Artificial Immune System Algorithm
SN - 978-989-758-378-0
IS - 2184-3236
AU - Zakariyya, I.
AU - Al-Kadri, M.
AU - Kalutarage, H.
AU - Petrovski, A.
PY - 2019
SP - 523
EP - 528
DO - 10.5220/0008119205230528
PB - SciTePress

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