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Effixis, a leading provider of Natural Language Processing solutions, collaborated with a governmental institution to develop an AI-powered dashboard that revolutionized the way cybersecurity news research is conducted. The objective was to create a tool that would automatically analyze and categorize technology and innovation news in the cybersecurity domain, using NLP techniques to understand the meaning of the text and identify relevant articles.
To develop the dashboard, Effixis obtained a large volume of cybersecurity news articles from various online sources. Advanced NLP models, such as BERT and LSTM, were used to analyze the articles and identify key information such as the topic, tone, and relevance to cybersecurity. A custom-trained text classification model was also developed to categorize the articles into specific topics such as network security, cloud security, and data privacy. Effixis also integrated novelty detection functionality to identify emerging topics in the cybersecurity domain.
The resulting dashboard provided our partner with a user-friendly interface to search and filter through vast amounts of cybersecurity news and updates. The tool not only saved time, but also provided insights into emerging trends and topics in the cybersecurity field, helping our partner stay ahead of potential threats. The dashboard was developed using Streamlit and deployed on a cloud server, making it accessible from anywhere.
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.
Natural Language Processing
Azure Cloud
Python
Streamlit
This collaboration resulted in an innovative tool that revolutionized cybersecurity news research. The AI-powered dashboard automatically analyzes and categorizes technology and innovation news in the cybersecurity domain, providing insights into emerging trends and topics in the field. The dashboard saves time and helps them stay ahead of potential threats. The collaboration also resulted in a joint paper exploring the potential of LLMs in cybersecurity. Effixis looks forward to continuing this partnership and contributing to the field of cybersecurity.
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