基于内容识别的NDN缓存污染防御策略
首发时间:2018-01-12
摘要:数据命名网络(NamedDataNetwork,NDN)是最具潜力的下一代互联架构之一。由于NDN普遍缓存的特性,NDN同时临新的安全威胁,即缓存污染攻击。本文针对NDN中的缓存污染攻击,提出了一种基于内容识别的缓存污染防御策略。该策略首先通过基于决策树的支持向量机对缓存内部的数据进行分类,识别污染内容。其次,根据缓存内容识别结果,该策略分别针对两种缓存污染攻击手段提出了相应的防御策略。通过仿真验证,本文所提出的防御策略具有较好的抵御缓存污染攻击的能力。
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Cache Pollution Defense Strategy based on Content Identification in Named Data Network
Abstract:Named Data Networking(NDN)is one of the most promosing next-generation Internet architecture. Because of the ubiquitous in-network caching of NDN, NDN suffers from a new security threats, cache pollution attack. In this paper, a cache pollution defense strategy based on content identification is presented to mitigate the cache pollution in NDN. In this strategy, decision-tree-based support vector machine is used to classify cached content. Based on the classification result, two corresponding defense strategies for two kinds of cache pollution are proposed. According to the simulation results, the defense strategy performs well in the mitigation of cache pollution attack.
Keywords: Computer Network Named Data Network Cache Pollution Attack
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