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ASEAN Journal on Science and Technology for Development

Abstract

In the context of escalating cyber threats, phishing attacks continue to pose significant challenges to cybersecurity measures, exploiting human vulnerabilities to gain unauthorized access to sensitive information. Innovative solutions are required because traditional detection methods frequently fail to identify and mitigate these assaults successfully. To improve phishing attack detection, this study makes use of Explainable Artificial Intelligence (AI) tools, which provide decision-making processes with transparency and prediction accuracy. The paper begins by outlining the pervasive nature of phishing attacks in today's digital landscape, emphasizing their detrimental impact on individuals, organizations, and society at large. It then discusses the limitations of existing detection methods, which often lack interpretability and fail to provide insights into the underlying rationale behind their decisions. To tackle these challenges, the paper proposes the adoption of Explainable AI, which combines sophisticated machine learning algorithms with transparent decision-making mechanisms. The study examines the use of Explainable AI in phishing attack detection across a range of disciplines, including industry applications, contributions to academic research, and workable implementation tactics, through a survey of current trends and advances in the field. By elucidating the underlying principles of Explainable AI and its role in bolstering cybersecurity measures, this paper aims to provide valuable insights for researchers, practitioners, and policymakers alike. In conclusion, the integration of Explainable AI holds immense promise for enhancing phishing attack detection capabilities, offering a balanced approach that prioritizes both accuracy and interpretability. By fostering transparency in decision-making processes and enabling human supervision and intervention, Explainable AI emerges as a pivotal tool in the ongoing battle against cyber threats, safeguarding digital assets and preserving trust in the digital ecosystem.

Keywords

Phishing attacks; Cybersecurity; Explainable Artificial Intelligence (AI); Detection methods; Transparency; Decision-making processes

Publication Date

2024

Received Date

24/08/2024

Revised Date

17/10/2024

Accepted Date

05/11/2024

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