Effixis worked closely with a governmental institution to develop this innovative solution. A large volume of cybersecurity news articles was collected and analyzed using state-of-the-art NLP models. A custom-trained text classification model was developed to categorize the articles into specific topics, and novelty detection functionality was integrated to identify emerging trends in the cybersecurity domain. The resulting dashboard was developed using Streamlit and deployed on a cloud server, making it accessible from anywhere.

As part of the collaboration, Effixis and the governmental institution worked together on a joint paper titled “Leveraging Large Language Models for Cyber-defence Campus: Opportunities and Challenges,” exploring the potential of LLMs in cybersecurity. The paper discusses various use cases, including text classification, sentiment analysis, and anomaly detection, and represents a significant contribution to the field of cybersecurity. The paper can be accessed through the following link: https://arxiv.org/abs/2303.12132.