Dissertations@Portsmouth - Details for item no. 14528

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Carre, Abigail (2024) the impact of artificial intelligence (AI) on phishing. (unpublished BSc dissertation), University of Portsmouth, Portsmouth

Abstract

The rapid growth of the internet and the proliferation of electronic devices have facilitated a surge in cybercrime, particularly in the form of phishing scams. Phishing attacks, where attackers exploit email links to perpetrate fraudulent activities, pose a significant threat to user security. Artificial Intelligence (AI) has emerged as a cornerstone technology in the Fourth Industrial Revolution, offering promising solutions for cybersecurity. While AI-based protective measures have demonstrated efficiency, they often lack comprehensive explanations for classifying URLs as phishing, leaving room for improvement. This study delves into the historical context of phishing scams and the integration of AI within cybersecurity. Through an extensive examination encompassing literature reviews, empirical studies, and case analyses, it sheds light on the evolving landscape of AI-driven phishing. The study elucidates the sophisticated tactics employed by attackers and explores AI's potential in fortifying defensive strategies, such as proactive threat detection and adaptive authentication. However, the deployment of AI in mitigating phishing risks is not without challenges. Adversarial attacks, concerns surrounding data privacy, and ethical dilemmas pose significant hurdles that necessitate careful consideration. The research underscores the importance of interdisciplinary collaboration and responsible AI development in navigating the complexities of the cyber landscape effectively. By fostering a culture of cybersecurity awareness and promoting innovative approaches, stakeholders can strive towards establishing a safer and more resilient digital ecosystem in the face of emerging threats.

Course: Criminology and Forensic Studies - BSc (Hons) - C2039F

Date Deposited: 2024-11-20

URI/permalink: https://library.port.ac.uk/dissert/dis14528.html