Network-Security-Using-Deep-Belief-Network

• Led a comprehensive project focused on enhancing network security through the application of Deep Belief Networks (DBNs) to detect anomalies and potential threats within a complex network environment. Developed and implemented a novel model leveraging DBNs to enhance the organization’s cybersecurity posture. • Intrusion Detection System (IDS) leveraging the power of Deep Belief Networks (DBN). The primary goal of the project was to enhance the organization’s network security by developing a cutting-edge IDS solution that could effectively detect and mitigate potential cyber threats. • Conducted in-depth research on IDS methodologies, evaluated machine learning algorithms, and explored the benefits of integrating DBN for network traffic analysis and anomaly detection, contributing to enhanced cybersecurity measures. • The IDS with DBN demonstrated superior accuracy in identifying previously unknown and complex network anomalies. The solution’s real-time capabilities allowed for swift response to potential threats, significantly reducing the risk of security breaches