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Dydact Signals2026-0314 min read

Thermodynamic Anomaly Detection in Network Byte Streams

SecurityNetwork AnalysisAnomaly Detection
Abstract

Network traffic analyzed at the byte level exhibits structural signatures that distinguish zero-day exploits from benign anomalies. We show that iterative refinement of raw packet data produces stability profiles where security-relevant events cluster in geometrically distinct regions, achieving a 94% true positive rate with a 0.3% false positive rate on the CICIDS-2017 benchmark.

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