This chapter provides a comprehensive exploration of the role of Natural
Language Processing (NLP) in fortifying cybersecurity measures. As the digital
landscape continues to evolve, the complexity and frequency of cyber threats have
necessitated the integration of advanced, intelligent solutions. NLP, a subfield of
artificial intelligence (AI) concerned with the interaction between computers and
human language, presents a compelling methodology to enhance cybersecurity
defenses. This chapter elucidates the multifaceted applications of NLP within the
cybersecurity realm, providing a detailed examination of ten distinct areas, including
but not limited to malware classification, social engineering attack detection, and
predictive analytics for cyber threats. Leveraging NLP techniques, we posit that
cybersecurity processes can be significantly optimized, bolstering rapid response times
and amplifying the overall security posture. Furthermore, the chapter delves into the
challenges that may arise in deploying NLP for cybersecurity, including data quality,
domain-specific language intricacies, and ethical considerations. The discussion
culminates in outlining potential future research directions, emphasizing the need for
improved NLP algorithms, cross-domain integration, and the importance of adversarial
NLP in maintaining robust security systems. This chapter serves as a guidepost in the
journey toward an enriched cybersecurity framework powered by the linguistic
capabilities of NLP.
Keywords: Adversarial NLP, Cybersecurity, Malware classification, Natural language processing, Predictive analytics, Social engineering attack detection.
