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Categorization of malicious behaviors using ontology-based cognitive agents

机译:使用基于本体的认知代理对恶意行为进行分类

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Every organization uses computer networks (consisting of networks of networks) for resource sharing (i.e. printer, files, etc.) and communication. Computer networks today are increasingly complex, and managing such networks requires specialized expertise. Monitoring systems help network administrators in monitoring and protecting their network by not allowing users to run illegal application or changing the configuration of network nodes. In this paper we have developed an agent based system for activity monitoring on networks (ABSAMN) and proposed Categorization of Malicious Behaviors using Cognitive Agents (CMBCA). This uses ontology to predict unknown illegal applications based on known illegal application behaviors. CMBCA is an intelligent multi agent system used to detect known and unknown malicious activities carried out users over the network. We have compared An Agent Based System for Activity Monitoring on Network (ABSAMN) and Categorization of Malicious Behaviors using Cognitive Agents (CMBCA) concurrently at the university campus having seven labs equipped with 20 to 300 PCs in various labs. Both systems were tested on the same configuration; results indicate that CMBCA outperforms ABSAMN in every aspect.
机译:每个组织都使用计算机网络(由网络网络组成)进行资源共享(即打印机,文件等)和通信。当今的计算机网络越来越复杂,管理这些网络需要专门的专业知识。监视系统通过不允许用户运行非法应用程序或更改网络节点的配置来帮助网络管理员监视和保护其网络。在本文中,我们开发了基于代理的网络活动监控系统(ABSAMN),并提出了使用认知代理(CMBCA)进行的恶意行为分类。这使用本体基于已知的非法应用程序行为来预测未知的非法应用程序。 CMBCA是一个智能的多代理系统,用于检测通过网络执行的用户的已知和未知恶意活动。我们在大学校园内同时比较了一个基于代理的网络活动监视系统(ABSAMN)和使用认知代理(CMBCA)进行的恶意行为分类,该大学校园有七个实验室,每个实验室配备20到300台PC。两个系统都在相同的配置上进行了测试;结果表明,CMBCA在各个方面均优于ABSAMN。

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