- Our Project aims to enhance cybersecurity by visualizing network logs and using machine learning algorithms to detect anomalies like DDOS attacks.
- It simplifies the complex and large-scale network logs for users, making threat detection more accessible and less reliant on manual inspection, by providing an flask interface built with Python.
- Machine learning models such as Isolation Forest, Local Outlier Factor, and Single-Class SVM are utilized to automatically identify outliers in network logs, improving the detection of security threats.
- The results are displayed on a Flask web application, offering users clear and actionable insights into detected anomalies and model performance.
