Cybercriminals employ sophisticated methods to infiltrate and extract sensitive information from governments, individuals, and organizations by compromising business emails, leading to illicit financial gain, impersonation, and identity theft. Despite the growing body of research on cyber fraud, solutions for cyber resilience remain in its infancy. Successful cyberattacks often exploit users’ ignorance and data violation of organizational policies thereby, a solution criterion will be designed to protect the confidentiality, integrity, and availability of information technology and other information systems assets such as Big Data, IoT, CRMS, SCMS and Cloud Enterprise Systems. This research aims to examine various artificial intelligence (AI) algorithms that can prevent phishing attacks and implement AI-based intrusion detection and prevention systems (IDPS). By designing an AI-based approach and simulating a typical phishing attack, this study will demonstrate how AI can detect and analyse cyber threats in business application of a typical organizations in real time systems. The research will explore the integration of real-time detection and prevention of phishing attacks through AI, focusing on the performance and accuracy of AI algorithms using IDPS and analysing the logs generated by these systems. The findings will
highlight the importance of using AI algorithms in IDPS to enhance cyber resilience without requiring human intervention. This research will contribute to educating organizations on the effectiveness of AI in detecting and preventing phishing attacks, ultimately improving their cybersecurity posture.

Authors: Omolola Ajibade, Christian Asante, Funminiyi Olajide

Published in: International Conference on Information Society (i-Society-2024)

• Date of Conference: 26-28 August, 2024
• DOI: 10.20533/iSociety.2024.0010
• ISBN: 978-1-913572-72-3
• Conference Location: Churchill College, Cambridge, UK