Year: 2024
Type: conference-paper
Abstract: The rapid advancement of artificial intelligence (AI) has significantly transformed the landscape of phishing attacks, presenting new challenges for detection and defense. AI-generated phishing emails, which leverage machine learning and natural language processing (NLP), have become increasingly sophisticated, making traditional detection methods ineffective. This research analyzes the evolution and impact of AI-driven phishing attacks, comparing the distinguishing linguistic and contextual patterns of AI-generated versus human-generated phishing emails. The study utilizes a comprehensive dataset, insights from informal discussions with Chief Information Security Officers (CISOs), and an analysis of historical phishing incidents before and after the release of advanced generative models like ChatGPT. Findings reveal that AI-generated phishing emails exhibit higher success rates due to their ability to bypass conventional spam filters and mimic human communication styles. Additionally, the research identifies significant gaps in current defense strategies and recommends a multi-layered security framework that integrates AI-specific detection tools, real-time threat intelligence, and machine learning-based anomaly detection to mitigate these evolving threats. This study emphasizes the need for organizations to proactively adapt to the growing sophistication of AI-powered phishing by implementing advanced defenses that are capable of keeping pace with the rapidly changing cyber threat landscape.
Authors: Shreyas Kumar, Anisha Menezes, Sarthak Giri, Srujan Kotikela
Institution: Texas A&M University
Language: English
Topic: Spam and Phishing Detection
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4405025437