Hybrid Latent-Structural Fusion (HLSF) for Cyber Anomaly Detection
Malicious anomalous activity detection is a fundamental challenge for cyber security systems. Both tensor decomposition under statistical framework with CANDECOMP-PARAFAC alternating Poisson regression (CP-APR) and normalizing flows have proven to be powerful unsupervised machine learning methods that model multi-dimensional data and capture complex and multi-faceted details of behavior profiles in cyber security applications. In this study, we propose Hybrid Latent-Structural Fusion (HLSF), a w
Record details
Published: 20 July 2026
Source: arXiv red teaming query
Category: Research
Topics: Military & security
Retrieved: 22 July 2026
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ethics.ai (20 July 2026), “Hybrid Latent-Structural Fusion (HLSF) for Cyber Anomaly Detection,” evidence record 12623, https://ethics.ai/record/12623 (originally published by arXiv red teaming query).
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