A Roadmap for SMEs to Adopt an AI Based Cyber Threat Intelligence
Date
2023
Journal Title
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Publisher
Springer Science and Business Media Deutschland GmbH
Abstract
Cybersecurity has started to become the most significant concern among organizations as the number of threats and criminal activities in the past decade has increased exponentially. Cybercriminals and their attacking techniques have become increasingly sophisticated over the past couple of years. Conventional security measures will no longer be able to detect and mitigate the propagation of such advanced attacking trends. More and more hackers have started focusing on Small and medium-sized enterprises (SMEs) taking advantage of their limited resources. Therefore, SMEs will have to quickly adopt Artificial Intelligence (AI) based cybersecurity system in their infrastructure to defend themselves effectively and efficiently. It is currently forecasted that by 2021, 75% of all organizations will use AI and Machine learning (ML) applications in their security architecture to protect against all cyber threats. In this paper, the researchers identify the various challenges faced by SMEs in adopting an AI based cybersecurity due to their knowledge gap and lack of expertise. The researcher intends to provide a good background on AI, Cyber Threat Intelligence (CTI) and highlight some of the significant benefits provided by an AI based CTI system. A simple roadmap is developed using a qualitative research methodology to help SMEs effectively implement an AI based Cyber Threat Intelligent system in their infrastructure. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Description
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Book chapter
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Keywords
AI, Artificial intelligence, Cyber threat intelligence, Cybersecurity, Deep learning, Machine learning, ML
Citation
Varma, A. J., Taleb, N., Said, R. A., Ghazal, T. M., Ahmad, M., Alzoubi, H. M., & Alshurideh, M. (2023). A Roadmap for SMEs to Adopt an AI Based Cyber Threat Intelligence. In M. Alshurideh, B.H. Al Kurdi, R. Masa’deh, H.M. Alzoubi & S. Salloum (Eds.) The Effect of Information Technology on Business and Marketing Intelligence Systems, 1056 (pp. 1903-1926). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-031-12382-5_105