parHSOM parallelizes HSOM training to achieve faster convergence on five cybersecurity datasets across multiple grid sizes and testbeds while preserving detection performance.
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DyMETER unifies hypernetwork-driven parameter adaptation and dynamic thresholding for online anomaly detection under concept drift.
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parHSOM: A novel parallel Hierarchical Self-Organizing Map implementation
parHSOM parallelizes HSOM training to achieve faster convergence on five cybersecurity datasets across multiple grid sizes and testbeds while preserving detection performance.
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Catching Every Ripple: Enhanced Anomaly Awareness via Dynamic Concept Adaptation
DyMETER unifies hypernetwork-driven parameter adaptation and dynamic thresholding for online anomaly detection under concept drift.