Detection effectiveness
In validation testing, the solution achieved full detection effectiveness with a very low false positive rate.
Precision: 99.99%
FPR: 0.0102%
Precision: 100.00%
FPR: 0.0000%
Precision: 99.97%
FPR: 0.0340%
Precision: 99.96%
FPR: 0.0300%
Precision: 99.98%
FPR: 0.0055%
Operational performance
Example of effectiveness
BDSP Architecture Present: BDSP Tytan
bdspTytan is a proprietary, signature-less network anomaly detection engine designed to protect against DDoS attacks, reconnaissance activity, and complex masking traffic patterns.
Solution overview
bdsp Tytan v4 has been designed to detect modern network threats:
- zero-day DDoS attacks
- low-and-slow / stealth campaigns
- reconnaissance activity, including port scans
- fragmentation attacks
- smokescreen and masking traffic patterns
Integration
The solution has been designed as a modular analytics layer for integration with existing security infrastructure, including NDR platforms, SIEM environments, scrubbing centers, operator-grade environments, and large-scale telemetry pipelines.
Validation
The solution's effectiveness has been validated through cross-dataset testing on independent datasets, including MAWI, UGR16 v4, and CIC-DDoS / Zero-Day.
Applications
BDSP architecture is ideally suited for improving control systems and software for electric motors, satellites, GPS systems, medical devices, wind energy systems, encryption technologies, and many other advanced applications.