Leveraging AI for Enhanced Botnet Detection - A Review of Machine Learning Approach for Cybersecurity
Harsha Sonune, Nilima Kulkarni · 2024
Botnets represent a substantial threat to cybersecurity, enabling malicious actors to execute large-scale attacks that compromise network integrity and data confidentiality. Current detection methods often fall short in addressing the rapidly evolving strategies employed by botnets. This study has an aim of designing and developing a sophisticated botnet detection system leveraging artificial intelligence (AI) techniques. By integrating machine learning algorithms and advanced data analysis methods, the proposed system seeks to accurately identify and mitigate botnet activities in real-time. The study will evaluate the effectiveness of various AI models in detecting botnet traffic, provide a comparative analysis of their performance, and propose an optimal framework for implementation in cybersecurity infrastructures.