Proceedings of the 16th International Joint Conference on E-Business and Telecommunications 2019
DOI: 10.5220/0008119205230528
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Reducing Computational Cost in IoT Cyber Security: Case Study of Artificial Immune System Algorithm

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… Show more

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Cited by 2 publications
(2 citation statements)
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“…The lack of universal standards may result in compatibility issues and hinder seamless integration across different IoT devices and systems. Businesses need to carefully evaluate and choose IoT solutions that are compatible with their existing infrastructure to avoid costly implementation errors state Petrovski et al, (2019). Furthermore Jankulovski et al, (2021) explains, the initial investment required for IoT implementation can be substantial, especially for smaller FMCG companies in North Republic of Macedonia.…”
Section: Implementation Of Iot In the Fmcg Sector In North Republic O...mentioning
confidence: 99%
“…The lack of universal standards may result in compatibility issues and hinder seamless integration across different IoT devices and systems. Businesses need to carefully evaluate and choose IoT solutions that are compatible with their existing infrastructure to avoid costly implementation errors state Petrovski et al, (2019). Furthermore Jankulovski et al, (2021) explains, the initial investment required for IoT implementation can be substantial, especially for smaller FMCG companies in North Republic of Macedonia.…”
Section: Implementation Of Iot In the Fmcg Sector In North Republic O...mentioning
confidence: 99%
“…Furthermore, AI can leverage data analysis to identify valuable waste streams and materials for recovery and recycling. Zakariyya et al (2019) presented techniques to reduce the computational cost of running AI algorithms, while Nam et al ( 2023) tackled the complex resource planning problem associated with AI workloads. These studies collectively highlight the role of AI as a powerful tool for analyzing data, managing resources, and optimizing processes (Porras & Daugherty, 2022;Sasikumar et al, 2022).…”
Section: Enhancing Resource Management Through Artificial Intelligencementioning
confidence: 99%