Natural Language Processing and AI in Cybersecurity: Strengthening Threat Intelligence through Digitalization

Abstract

As digitalization continues to transform industries, cybersecurity faces increasingly complex threats that require advanced technological solutions. Natural Language Processing (NLP), a subset of Artificial Intelligence (AI), is emerging as a crucial tool for strengthening threat intelligence in the cybersecurity landscape. By enabling machines to understand, interpret, and respond to human language, NLP helps cybersecurity systems analyze vast amounts of unstructured data, such as emails, chat logs, and social media, which are often exploited in cyberattacks. This paper explores the role of NLP and AI in augmenting cybersecurity practices, particularly in identifying, predicting, and mitigating threats. One of the most significant applications of NLP in cybersecurity is its ability to detect phishing, fraud, and malware embedded in textual data. NLP algorithms can analyze text for suspicious patterns, keywords, and linguistic anomalies, helping organizations respond swiftly to potential attacks. Additionally, NLP assists in analyzing threat reports, research papers, and social media conversations to gather insights on emerging cyber threats in real-time. The integration of NLP with AI allows for the development of more adaptive, automated systems capable of learning from evolving threat landscapes. AI enhances these capabilities by applying machine learning models that continuously improve in detecting, analyzing, and responding to cyber threats based on the linguistic data they process.