Developing An Ontology Of Cyber-Operations In Networks Of Computers

Andrei Zamfira, H. Ciocarlie
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引用次数: 4

Abstract

Many detection techniques have been proposed until now that struggle to keep up with the inherent complexity of applications, networks and protocols, resulting also in the growing rate of attacks that exploit them. Security frameworks that are created using an ontological approach are the next-gen systems of defense that have some advantages over the conventional techniques because they can capture the context of information and are capable to filter these contents depending on some certain factors. This paper proposes a method of creating an ontology that can be used for improving detection capabilities of attacks at all application levels. The ontology serves as a data model and knowledge base of the cyberoperations domain that conceptualizes and stores various types of data needed in the process of detecting an aware situation, such as information about attacks (types), OSI stack levels to which are targeted (software, network, hardware), countermeasure methods, resources necessary, knowledge required etc. The quality of the proposed model was assessed using a methodology known as OntoClean, that is a comprehensive suite of metrics for ontology evaluation that can comprise up to 15 criteria, as will be discussed during this paper. The ontology was tested in attack detection using a prototype web application firewall. In the evaluation process we used the famous dataset Kyoto2006+ proposed by the University of Kyoto in this scope. The results yielded for attacks detection by our proposed system were compared to other existing security solutions, like ModSecurit and Snort. In the conclusion section are stated the future directions of this research towards constructing reliable systems for cyber-security.
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计算机网络中网络操作本体的发展
到目前为止,已经提出了许多检测技术,难以跟上应用程序、网络和协议固有的复杂性,这也导致利用它们的攻击速度不断增长。使用本体论方法创建的安全框架是下一代防御系统,它比传统技术有一些优势,因为它们可以捕获信息的上下文,并能够根据某些特定因素过滤这些内容。本文提出了一种创建本体的方法,该本体可用于提高所有应用层对攻击的检测能力。本体是网络作战领域的数据模型和知识库,它概念化和存储检测感知情况过程中所需的各种类型的数据,如攻击信息(类型)、目标OSI堆栈级别(软件、网络、硬件)、对策方法、所需资源、所需知识等。所提议的模型的质量是使用一种称为OntoClean的方法来评估的,这是一套全面的本体评估指标,可以包含多达15个标准,这将在本文中讨论。利用原型web应用防火墙对本体进行了攻击检测。在评估过程中,我们使用了京都大学在该范围内提出的著名数据集Kyoto +。我们提出的系统对攻击检测产生的结果与其他现有的安全解决方案(如ModSecurit和Snort)进行了比较。在结论部分,提出了构建可靠的网络安全系统的未来研究方向。
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