Cost-Aware Hierarchical Multi-Agent Ransomware Detection and Family Attribution
Quick summary
arXiv:2609.04820v1 Announce Type: cross Abstract: Ransomware detection and family attribution require analysis of different modalities because it can use packing, obfuscation, process manipulation and runtime evasion techniques. However, conventional multimodal usually uses all available modalities for every sample resulting in unnecessary computational cost and increased latency. In this paper, we present a Cost Aware Hierarchical Multi-Agent System (HMAS) for adaptive ransomware detection. The proposed architecture organizes specialized agents into hierarchical domain controllers coordinated
Key takeaways
- arXiv:2609.04820v1 Announce Type: cross Abstract: Ransomware detection and family attribution require analysis of different modalities because it can use packing, obfuscation, process manipulation and runtime evasion techniques.
- However, conventional multimodal usually uses all available modalities for every sample resulting in unnecessary computational cost and increased latency.
- In this paper, we present a Cost Aware Hierarchical Multi-Agent System (HMAS) for adaptive ransomware detection.
Why it matters
“Cost-Aware Hierarchical Multi-Agent Ransomware Detection and Family Attribution” highlights the need for repeatable measurement rather than a single impressive demonstration. Independent validation across datasets and clearly stated limitations determine whether a result can guide product decisions.
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