En este proyecto se evalúan y comparan diferentes técnicas de aprendizaje automático para la detección de intrusiones en red.
Codes for the paper entitled "Optimization of Predictive Performance of Intrusion Detection System Using Hybrid Ensemble Model for Secure Systems"
Attack Detection, Parameter Optimization and Performance Analysis in Enterprise Networks (ML Networks) for Intrusion Detection System IDS.
Lightweight encrypted session abstraction with X25519 handshake and AES-GCM encryption. Pluggable transport and generic addressing. Designed for secure peer-to-peer and embedded communication.
SecureStream is a network security project that employs machine learning and real-time traffic monitoring to detect anomalies in network data. Powered by the CSE-CIC-IDS2018 dataset and cicflowmeter, it enables swift identification of potential threats, enhancing overall network security.
Network Threat Detection with Optimized Machine Learning
🚀 Detect network intrusions with this ML-based system using the NSL-KDD dataset. Features include model training, API deployment, and an interactive dashboard.
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