Automated Emerging Cyber Threat Identification and Profiling based on Natural Language Processing using BERT Model

After the absolute dependence on digital technologies and the Internet as a modern requirement, cybersecurity has become of utmost importance to everyone. This frightening development in cyber threats through malware, phishing, ransomware, and APTs has brought too many risks to individuals, organizations, and communities. These threats do nothing but continue to grow in terms of quantity and quality, sometimes even surpassing the usual security measures. Hence, the need for new out-of-the-box solutions that relentlessly change and adapt to the threats must be addressed by the concerned authorities. NLP is an interdisciplinary field that deals with the communication between supercomputers and people using popular natural language. In the contemporary digital-friendly environment, the widespread use of the Internet and digital devices has raised the alarm about cybersecurity protection. The widespread prevalence and sophistication of malicious online operations such as malware, phishing, ransomware, and advanced persistent threats (APTs) entail high stakes for individuals, organizations, and even entire countries. BERT, a leading NLP technique, will be used to execute a study concentrated on the application of the BERT model to the building of an automated system for spotting and profiling new cyber threats. BERT's ability to recognize the context of sentences enhances accuracy in threat detection and classification and makes it a useful approach against modern cyber threats. This research directly brings to the field something special in the form of a new method for integrating NLP into the existing cybersecurity field, thereby aiming mainly at the bid to secure digital infrastructures against the menace of cyber threats.