侯睿,韩敏,陈璟,何柳婷,毛腾跃.命名数据网络中基于信息熵的Interest洪泛攻击检测与防御[J].中南民族大学学报自然科学版,2019,(2):273-277
命名数据网络中基于信息熵的Interest洪泛攻击检测与防御
Information entropy-based Interest Flooding Attack detection and defense in Named Data Networking
  
DOI:10.12130/znmdzk.20190222
中文关键词: 命名数据网络  兴趣包泛洪攻击  信誉值  信息熵
英文关键词: Named Data Networking  Interest Flooding Attack  reputation value  information entropy
基金项目:国家自然科学基金资助项目(60841001);中央高校基本科研业务费专项资金资助项目(CZT19011)
作者单位
侯睿,韩敏*,陈璟,何柳婷,毛腾跃 中南民族大学 计算机科学学院武汉430074 
摘要点击次数: 122
全文下载次数: 128
中文摘要:
      在命名数据网络中,兴趣包洪泛攻击通过向网络发送大量恶意interest包来消耗网络资源,从而对NDN造成较大危害.针对目前所提出的IFA攻击检测与防御方法存在攻击模式单一、在应对复杂攻击模式时效果不明显等局限.提出一种基于信息熵的改进方法(EIM),该方法通过与NDN路由器相连的用户的信誉值和信息熵相结合来限制攻击者发送的恶意interest包,很好地解决了现有方法在应对复杂的攻击模式时的局限性.仿真结果表明EIM较信息熵方法能够更有效地缓解IFA.
英文摘要:
      In Named Data Networking (NDN), Interest Flooding Attack (IFA) sends plenty of malicious interest packets into a network to exhaust its resource, thus cause enormous damage. For the current proposed IFA attack detection and defense method, only a single attack mode is involved, so that the effect is not obvious when dealing with complex attack modes. An information Entropy-based Improved Method (EIM) is proposed for IFA in this paper. EIM combines a user’s reputation value and information entropy of the NDN router, which is directly connected to the user, to restrict the malicious interest packet sent by attackers, and solves the limitation of the existing method in dealing with the complex attack mode. Simulation results show that EIM can alleviate IFA more effectively than information entropy method.
查看全文   查看/发表评论  下载PDF阅读器
关闭