SOURCE-LINKED INTELLIGENCE

Cost-Aware Hierarchical Multi-Agent Ransomware Detection and Family Attribution

arXiv · AI, language, vision and robotics · article · Sep 4, 2026 · UTC

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 by a Meta Orchestrator. Static analysis is used a

Read original source ↗ Open in workspace

recordType

paper

region

Global