Advanced Techniques and Best Practices for Phishing Detection

Advanced Techniques and Best Practices for Phishing Detection

Ravina Mittal (Chandigarh College of Engineering and Technology, Panjab University, Chandigarh, India), Sunil K. Singh (Chandigarh College of Engineering and Technology, Panjab University, Chandigarh, India), Sudhakar Kumar (Chandigarh College of Engineering and Technology, Panjab University, Chandigarh, India), Trannum Khullar (Chandigarh College of Engineering and Technology, Panjab University, Chandigarh, India), Rakesh Kumar (G.L. Bajaj Institute of Technology and Management, India), Brij B. Gupta (Asia University, Taichung, Taiwan, & University of Economics and Human Science, Warsaw, Poland), and Konstantinos Psannis (University of Macedonia, Greece)
Copyright: © 2025 |Pages: 38
DOI: 10.4018/979-8-3693-8784-9.ch008
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Abstract

Phishing attacks are among the most prevalent and dangerous cyber threats, exploiting both technological and human vulnerabilities to access sensitive information. As phishing techniques evolve, organizations must implement various detection strategies to stay ahead of cybercriminals. This chapter delves into phishing detection methods, covering traditional approaches like signature-based detection and content filtering, alongside advanced strategies such as heuristic analysis, machine learning, and artificial intelligence (AI). It evaluates the strengths, limitations, and practical applications of these methods in real-world scenarios. Additionally, the chapter explores emerging technologies like Natural Language Processing (NLP), blockchain, and behavioral analysis that are redefining phishing detection. By combining traditional and modern techniques, organizations can enhance their ability to identify and prevent phishing attacks, strengthening their overall cybersecurity.
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