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DNSSEC域名解析的形式化描述及量化分析研究
  • ISSN号:1000-1239
  • 期刊名称:《计算机研究与发展》
  • 时间:0
  • 分类:TP393.08[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术] U491.13[交通运输工程—交通运输规划与管理;交通运输工程—道路与铁道工程]
  • 作者机构:[1]Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, P. R. China, [2]Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100195, P. R. China, [3]University of Chinese-Academy of Science, Beijing 100190,P. R. China
  • 相关基金:Supported by the National Natural Science Foundation of China ( No. 61070185, 61003261 ) and the Knowledge Innovation Program of the Chi- nese Academy of Sciences (No. XDA06030200).
中文摘要:

Increasing time-spent online has amplified users’ exposure to the threat of information leakage.Although existing security systems(such as firewalls and intrusion detection systems) can satisfy most of the security requirements of network administrators,they are not suitable for detecting the activities of applying the HTTP-tunnel technique to steal users’ private information.This paper focuses on a network behavior-based method to address the limitations of the existing protection systems.At first,it analyzes the normal network behavior pattern over HTTP traffic and select four features.Then,it presents an anomaly-based detection model that applies a hierarchical clustering technique and a scoring mechanism.It also uses real-world data to validate that the selected features are useful.The experiments have demonstrated that the model could achieve over 93%hit-rate with only about 3%falsepositive rate.It is regarded confidently that the approach is a complementary technique to the existing security systems.

英文摘要:

Increasing time-spent online has amplified users' exposure to tile tilreat oI miormanon leakage. Although existing security systems (such as firewalls and intrusion detection systems) can satisfy most of the security requirements of network administrators, they are not suitable for detecting the activities of applying the HTTP-tunnel technique to steal users' private information. This paper focuses on a network behavior-based method to address the limitations of the existing protection systems. At first, it analyzes the normal network behavior pattern over HTI'P traffic and select four features. Then, it pres- ents an anomaly-based detection model that applies a hierarchical clustering technique and a scoring mechanism. It also uses real-world data to validate that the selected features are useful. The experiments have demonstrated that the model could achieve over 93% hit-rate with only about 3% false- positive rate. It is regarded confidently that the approach is a complementary technique to the existing security systems.

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期刊信息
  • 《计算机研究与发展》
  • 中国科技核心期刊
  • 主管单位:中国科学院
  • 主办单位:中国科学院计算技术研究所
  • 主编:徐志伟
  • 地址:北京市科学院南路6号中科院计算所
  • 邮编:100190
  • 邮箱:crad@ict.ac.cn
  • 电话:010-62620696 62600350
  • 国际标准刊号:ISSN:1000-1239
  • 国内统一刊号:ISSN:11-1777/TP
  • 邮发代号:2-654
  • 获奖情况:
  • 2001-2007百种中国杰出学术期刊,2008中国精品科...,中国期刊方阵“双效”期刊
  • 国内外数据库收录:
  • 俄罗斯文摘杂志,荷兰文摘与引文数据库,美国工程索引,日本日本科学技术振兴机构数据库,中国中国科技核心期刊,中国北大核心期刊(2004版),中国北大核心期刊(2008版),中国北大核心期刊(2011版),中国北大核心期刊(2014版),中国北大核心期刊(2000版)
  • 被引量:40349