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New HMAS system offers cost-effective ransomware detection

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a Cost-Aware Hierarchical Multi-Agent System (HMAS) for more efficient ransomware detection and family attribution. This system uses a hierarchical organization of specialized agents, coordinated by a Meta Orchestrator, to adaptively select analysis modalities. It prioritizes low-cost static analysis and selectively employs dynamic and memory analysis only when necessary, guided by a cost model that balances performance with computational expense. Experiments show HMAS achieves high accuracy in detection and attribution while reducing analysis costs by nearly 44% compared to exhaustive methods, with a significant portion of cases resolved using only static evidence. AI

IMPACT This research could lead to more efficient and cost-effective cybersecurity tools for detecting and classifying ransomware threats.

RANK_REASON Academic paper detailing a new system for ransomware detection. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New HMAS system offers cost-effective ransomware detection

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Academic paper detailing a new system for ransomware detection. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Mubashar Iqbal, Asifullah Khan ·

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

    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 a…

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