I built a network security analyzer using information geometry (Riemannian manifolds) instead of traditional rule-based detection

After 30+ years in critical infrastructure security (power grid, banking), I got frustrated with SIEM tools that generate mountains of false positives. So I built something different. ASAF uses information geometry — specifically Fisher Information Matrices and geodesic analysis on statistical manifolds — to model network behavior. Instead of pattern matching against known signatures, it measures how the “shape” of network traffic deviates from its natural geometry. Key technical details: C++17/Eigen3, runs air-gapped (no cloud dependency) Ihara zeta function for network topology analysis Geodesic extrapolation via RK4 for predictive threat detection Maps findings to MITRE ATT&CK framework for actionable reports The core idea: network traffic lives on a statistical manifold. Normal traffic follows geodesics. Attacks create curvature anomalies that are mathematically detectable before traditional IDS/IPS triggers. Built for industrial/critical infrastructure environments where air-gap is mandatory. Happy to discuss the math or architecture. Been running it on real infrastructure in Mexico. Contact: entfernten.galaxie@gmail.com | https://consultoria.aivoix.mx submitted by /u/Former-Oil-4621 [link] [comments]Technical Information Security Content & DiscussionRead More