arXiv · cs.AI · Mubashar Iqbal, Hifsa Asif, Saddam Hussain Khan, Umme Zahoora, Asifullah Khan · 10 小时前模型评分37
成本感知分层多智能体系统实现勒索软件检测与家族归因
Cost-Aware Hierarchical Multi-Agent Ransomware Detection and Family Attribution
导读
研究者提出成本感知的分层多智能体系统（HMAS，Hierarchical Multi-Agent System），把证据获取建模为有预算的顺序决策问题，从静态证据起步，仅在置信度低或信号冲突时升级分析。
分类置信度
中 · 待人工复核
- 只有单一媒体来源，需要人工复核。
来源级别：媒体与个人
应用领域：其他
事件类型：研究发布
证据摘录
- “this http URL proposea cost aware Hierarchical Multi Agent System (HMAS) that frames evidence acquisition as a budgeted sequential decision problem enabling timely ransomware detection.”
- “The orchestrator starts with static evidence and escalates only if confidence is low or signals disagree.”
- “A locally hosted language model provides a limited, accoutable review without replacing the deterministic pipeline.”
来源：arXiv · cs.AI · arxiv.org