loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

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.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.144.254.231

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

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

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic