Likhitha

The extensive and ever-changing nature of Internet of Things (IoT) networks presents unique cybersecurity challenges, making them especially vulnerable to botnet attacks. The inability of current security systems to distinguish between hostile and benign traffic usually leads to high false alarm rates and suboptimal detection accuracy. The Botnet Attack Detection and Defense (BADD) mechanism, which is supervised learning-based and employs a convolutional neural network (CNN) models are our solution to this issue. BADD uses predefined time periods to buffer traffic data and extract parametric information to do predictive analysis and identify potential botnet attacks.