Yeboah-Ofori, Abel ORCID: https://orcid.org/0000-0001-8055-9274, Haralambos, Mouratidis, Ismai, Umar, Islam, Shareeful and Spyridon, Papastergiou (2021) Cyber supply chain threat analysis and prediction using machine learning and ontology. In: AIAI 2021: Artificial Intelligence Applications and Innovations, 25-27 Jun 2021, Greece.

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Abstract

Cyber Supply Chain (CSC) security requires a secure integrated network among the sub-systems of the inbound and outbound chains. Adversaries are deploying various penetration and manipulation attacks on an CSC integrated network’s node. The different levels of integrations and inherent system complexities pose potential vulnerabilities and attacks that may cascade to other parts of the supply chain system. Thus, it has become imperative to implement systematic threats analyses and predication within the CSC domain to improve the overall security posture. This paper presents a unique approach that advances the current state of the art on CSC threat analysis and prediction by combining work from three areas: Cyber Threat Intelligence (CTI), Ontologies, and Machine Learning (ML). The outcome of our work shows that the conceptualization of cybersecurity using ontological theory provides clear mechanisms for understanding the correlation between the CSC security domain and enables the mapping of the ML prediction with 80% accuracy of potential cyberattacks and possible countermeasures.

Item Type:	Conference or Workshop Item (Paper)
ISSN:	1868-4238
ISBN:	9783030791490
Identifier:	10.1007/978-3-030-79150-6_41
Page Range:	pp. 518-530
Identifier:	10.1007/978-3-030-79150-6_41
Additional Information:	The final publication is available at Springer via https://doi.org/10.1007/978-3-030-79150-6_41
Keywords:	artificial intelligence, computational linguistics, computer networks, data mining, databases, image processing, information retrieval, internet, machine learning, network protocols, neural networks, robotics, semantics, signal processing, software engineering, telecommunication networks, user interfaces
Subjects:	Computing > Information security > Cyber security
Related URLs:	Publisher Organisation
Depositing User:	Dr Abel Yeboah-Ofori
Date Deposited:	26 Nov 2021 03:02
Last Modified:	04 Nov 2024 12:32
URI:	https://repository.uwl.ac.uk/id/eprint/8030

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