Artificial Intelligence and Cyber Defense System for Banking Industry: A Qualitative Study of AI Applications and Challenges
المؤلف | AL-Dosari, Khalifa |
المؤلف | Fetais, Noora |
المؤلف | Kucukvar, Murat |
تاريخ الإتاحة | 2023-06-25T05:13:31Z |
تاريخ النشر | 2022-08-23 |
اسم المنشور | Cybernetics and Systems |
المعرّف | http://dx.doi.org/10.1080/01969722.2022.2112539 |
الاقتباس | AL-Dosari, K., Fetais, N., & Kucukvar, M. (2022). Artificial Intelligence and Cyber Defense System for Banking Industry: A Qualitative Study of AI Applications and Challenges. Cybernetics and Systems, 1-29. |
الرقم المعياري الدولي للكتاب | 0196-9722 |
الملخص | Cyberattacks are becoming more and more intense in the banking industry (Ryzhkova et al. 2020). Banking industry is trying to adopt artificial intelligence to create cyber defence system so that the unauthorized access and cyber attacks would be minimized. Banks in Qatar acknowledge the threat of cybercrimes and the role of cybersecurity in sustainable growth. Meanwhile, the banking industry is experiencing a major technological disruption. It becomes important to understand the implications of such technologies as artificial intelligence (AI) on the cybersecurity of banks. The present paper aims to explore the impacts of AI on the cybersecurity of banks in Qatar. A thematic analysis of interviews of 9 experts in the banking industry of Qatar was conducted. A qualitative thematic analysis was conducted using NVIVO 12 tool. Four key themes were identified: (1) AI is a major tool for enhancing the cybersecurity of banks in Qatar; (2) banks face challenges in using AI for improving cybersecurity; (3) AI can be used destructively and thus poses a threat to cybersecurity in banks of Qatar; (4) employed AI-based tools have vulnerabilities that can be exploited. Overall, Qatar banks can be expected to face new challenges in the future, due to changes in regulatory frameworks and increasing availability of AI-powered malware. |
اللغة | en |
الناشر | Taylor & Francis |
الموضوع | AI powered-malware artificial intelligence cyberattack patterns decision-making fin tech machine learning |
النوع | Article |
الصفحات | 1-29 |
ESSN | 1087-6553 |
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