Guembe, Blessing and Azeta, Ambrose and Misra, Sanjay and Osamor, Victor Chukwudi and Fernandez-Sanz, Luis and Pospelova, Vera (2022) The Emerging Threat of Ai-driven Cyber Attacks: A Review. Applied Artificial Intelligence, 36 (1). ISSN 0883-9514
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Abstract
Cyberattacks are becoming more sophisticated and ubiquitous. Cybercriminals are inevitably adopting Artificial Intelligence (AI) techniques to evade the cyberspace and cause greater damages without being noticed. Researchers in cybersecurity domain have not researched the concept behind AI-powered cyberattacks enough to understand the level of sophistication this type of attack possesses. This paper aims to investigate the emerging threat of AI-powered cyberattacks and provide insights into malicious used of AI in cyberattacks. The study was performed through a three-step process by selecting only articles based on quality, exclusion, and inclusion criteria that focus on AI-driven cyberattacks. Searches in ACM, arXiv Blackhat, Scopus, Springer, MDPI, IEEE Xplore and other sources were executed to retrieve relevant articles. Out of the 936 papers that met our search criteria, a total of 46 articles were finally selected for this study. The result shows that 56% of the AI-Driven cyberattack technique identified was demonstrated in the access and penetration phase, 12% was demonstrated in exploitation, and command and control phase, respectively; 11% was demonstrated in the reconnaissance phase; 9% was demonstrated in the delivery phase of the cybersecurity kill chain. The findings in this study shows that existing cyber defence infrastructures will become inadequate to address the increasing speed, and complex decision logic of AI-driven attacks. Hence, organizations need to invest in AI cybersecurity infrastructures to combat these emerging threats.
Item Type: | Article |
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Subjects: | Pacific Library > Computer Science |
Depositing User: | Unnamed user with email support@pacificlibrary.org |
Date Deposited: | 14 Jun 2023 06:30 |
Last Modified: | 11 Jun 2024 05:49 |
URI: | http://editor.classicopenlibrary.com/id/eprint/1562 |