Using Natural Language Processing (NLP) for Phishing and Spam Detection

Abstract

With the rapid advancement of digital communication, phishing and spam attacks have become pervasive cyber threats, targeting both individuals and organizations. This chapter explores the application of Natural Language Processing (NLP) in detecting and mitigating these malicious activities. By analyzing linguistic patterns and textual characteristics, NLP techniques can distinguish between legitimate and deceptive content, offering a robust, automated defense mechanism against a wide array of cyber threats. The chapter discusses various NLP-based methods, including text classification, feature extraction, sentiment analysis, and machine learning algorithms, that can effectively identify phishing and spam messages. Real-world case studies and practical implementations are also presented, providing insight into the operational efficacy of NLP in cybersecurity. The chapter concludes with future research directions, addressing the evolving tactics of cybercriminals and the potential of NLP to keep pace with emerging threats.