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NetSentinel
2023
Overview
Traditional intrusion detection systems rely on known attack signatures, making them blind to zero-day exploits and novel attack techniques. NetSentinel takes a behavioral approach — it learns the normal traffic patterns of a network and alerts on significant deviations, regardless of whether the specific attack pattern has been seen before.\n\nThe system was designed for mid-to-large enterprise networks where the volume of traffic makes manual analysis impossible, but where the cost of a breach far exceeds the investment in detection.
Key Features
- Real-time traffic analysis with sub-second latency
- Unsupervised anomaly detection — no labeled attack data needed
- Adaptive baselines that learn from network changes
- Integration with SIEM platforms (Splunk, ELK Stack)
- Automated incident response playbooks
- Network segment profiling and comparison
- Exportable threat intelligence feeds
Description
Real-time network intrusion detection system using machine learning anomaly detection.