Shilpa
Computer Science
June 2025
Modern, real-time detection systems have become necessary due to the increasing frequency and sophistication of cyber-attacks on social media platforms in recent years. This study uses a group of Natural Language Processing (NLP) models in an inventive way to improve cyber threat identification. In order to take use of each individual technique's advantages, the ensemble combines many NLP approaches, which increases the overall efficacy and accuracy of cyber threat assessment. Our ensemble approach creates a robust system that can capture the finer points and contextual subtleties found in social media material by combining state-of-the-art language models, deep learning architectures, and classic machine learning techniques. The ensemble is efficient and uses lightweight embeddings and parallel processing to enable real-time detection. The ensemble is a durable and proactive defence system because of its capacity to dynamically adapt to new cyber threats
806- 819
© Airo Journals 2021
