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Found 2 papers, 1 papers with code
Dynamic data fusion using multi-input models for malware classification
To solve this, we investigated four cases: a text-only model, a hexadecimal-only model, a multi-input model using both text and hexadecimal inputs, and a model based on combining the individual results.
Multi-Level Anomaly Detection on Time-Varying Graph Data
This work presents a novel modeling and analysis framework for graph sequences which addresses the challenge of detecting and contextualizing anomalies in labelled, streaming graph data.
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