期刊文献+

数据挖掘对信息安全的影响 被引量:11

Influence of Data Mining on Information Security
在线阅读 下载PDF
导出
摘要 数据挖掘是目前学术界研究的热点,它在应用领域取得了巨大的成功。数据挖掘技术的发展极大地推动了信息安全领域的研究工作,同时,它也对信息安全有一定的消极影响。论述数据挖掘技术对信息安全各领域的积极作用,并给出了对其不利影响的应对策略。 Data mining is the hot topic of research on academic circles and big success had been gained in its application domain. The development of data mining technique stimulated the study of information security, meanwhile, on which it also has negative impact. Discusses the impetuses of data mining technique to different information security domains and gives solutions to the corresponding bad influence of data mining on information security.
作者 郑卓远 周娅
出处 《现代计算机》 2008年第3期36-39,共4页 Modern Computer
关键词 数据挖掘 信息安全 入侵检测 计算机犯罪取证 安全审计 恶意代码检测 隐私保护 Data Mining Information Security Intrusion Detection Computer Crime Forensic Security Auditing Malicious Code Detection Privacy Preservation
  • 相关文献

参考文献10

  • 1Wenke Lee; Stolfo, S.J., Mok, K.W.; A Data Mining Framework for Building Intrusion Detection Models. Security and Privacy, 1999. Proceedings of the 1999 IEEE Symposium on 9-12 May 1999:120-132.
  • 2QIN Xin-zhou; Wenke Lee; Lewis, L.; Cabrera, J.B.D.; Integrating Intrusion Detection and Network Management. Network Operations and Management Symposium, 2002.NOMS 2002. 2002 IEEE/IFIP.15-19 April 2002:329-344.
  • 3Agrawal R, Srikant R. Privacy-Preserving Data Mining. In: Weidong C, Jeffrey F, eds. Proc. of the ACM SIGMOD Conf. on Management of Data. Dallas: ACM Press, 2000:439-450.
  • 4Schultz, M.G.; Eskin, E.; Zadok, F.; Stolfo, S.J.;Data Mining Methods for Detection of New Malicious Executables. Security and Privacy, 2001. S&P 2001. PrQceedings. 2001 IEEE Symposium on 14-16 May 2001:38-49.
  • 5Evfimievski A, Srikant R, Agrawal R, Gehrke J. Privacy Preserving Mining of Association Rules. In: Hand D, Keim D, Ng R, eds. Proc. of the 8th ACM S1GKDD Int'l Conf. on Knowledge Discovery and Data Mining. Edmonton: ACM Press, 2002 : 217-228.
  • 6Oliveira SRM, Zaiane OR. Privacy Preserving Frequent Itemset Mining. In: Clifton C, EstivillCastro V, eds. Proc. of the IEEE Int'lConf. on Data Mining Workshop on Privacy, Security and Data Mining. Maebashi: IEEE Computer Society, 2002:43-54.
  • 7徐兴元,傅和平,熊中朝.基于数据挖掘的入侵检测技术研究[J].微计算机信息,2007,23(03X):74-75. 被引量:17
  • 8邹仕洪,阙喜戎,龚向阳,程时端.基于数据挖掘与CIDF的自适应入侵检测系统[J].计算机工程与应用,2002,38(11):184-186. 被引量:13
  • 9聂林,张玉清,王闵.入侵防御系统的研究与分析[J].计算机应用研究,2005,22(9):131-133. 被引量:11
  • 10钟秀玉.基于数据挖掘的动态取证技术研究[J].微机发展,2005,15(12):173-176. 被引量:2

二级参考文献22

  • 1王杰,李冬梅.数据挖掘在网络入侵检测系统中的应用[J].微计算机信息,2006,22(04X):73-75. 被引量:15
  • 2于秀林 任雪松.多元统计分析[M].中国统计出版社,1997..
  • 3Bamshad M,Cooley R,Srivastava J. Data preparation for mining world wide web browsing patterns[ J ]. Journal of Knowledge and Information Systems, 1999,1 (1): 5 - 32.
  • 4Raikow D. Building your own honeypot[EB/OL]. http://www. linuxsecurity. com./2004.
  • 5Reith M, Carr C, Gunsch G. An Exanmination of Digital Forensic Model[J ]. International Journal of Digital Evidence,2002,1(3) :1 - 12.
  • 6Farmer D, Venema W. The coroner's toolkit (TCT) [ EB/OL]. http://www. fish. com/tct/. 2002.
  • 7David Newman, Joel Snyder, Rodney Thayer. Crying Wolf: False Alarms Hide Attacks[EB/OL]. http://www.nwfusion.com/techinsider/2002/0624security1.html, 2002.
  • 8Vandyke SoftwareTM. Survey Shows How IT Perceives & Responds to Constantly Changing Security Threates[EB/OL]. http://www.vandyke.com,2003.
  • 9Andrew Plato. What is an Intrusion Prevention System[EB/OL].http://www.anitian.com/corp/papers/ips_defined.pdf,2004.
  • 10Secure Computing Corporation. Intrusion Prevention Systems (IPS), Part One[EB/OL]. http://www.co ndyn.net/download/Intru-Preven-WP1-Aug03-vF.pdf, 2003.

共引文献39

同被引文献36

  • 1贺蓉,赵振西,周学海,陈尚义,赵巍.联合挖掘发现网络安全事件[J].计算机系统应用,2006,15(2):41-43. 被引量:10
  • 2张琴.网络安全事件频频发生用户损失谁来承担[N].经济参考报,2007-07-05.
  • 3王比学.我国信息网络安全事件持续多发今年达65.7%[N].人民日报,2007-10-08.
  • 4iResearch:中国个人网络安全市场凸显四大发展趋势[EB/OL].www.iResearch.com.cn/Consulting/online_security/DetailNews.asp?id=68842.
  • 5SEIFERT J W. Data mining and the search for security: challenges for connecting the dots and databases [ J ]. Government Information Quarterly, 2004 (21) : 461-480.
  • 6林杰斌,刘明德,陈湘.数据挖掘与0LAP理论与实务[M].北京:清华大学出版社,2002.195-199.
  • 7AGRAWAL R, IMIELINAKI T, SWAMI A. Mining association rules between sets of items in large database [ C] //Proc of the ACM SIGMOD Conferenee on Management of Data, 1993.
  • 8李明华,刘全,刘忠,郗连霞.数据挖掘中聚类算法的新发展[J].计算机应用研究,2008,25(1):13-17. 被引量:50
  • 9李森,胡学钢,李正吉.Web数据挖掘研究综述[J].山东纺织经济,2008,25(1):98-100. 被引量:6
  • 10查全民,汪荣贵,何畏.基于量子遗传聚类的入侵检测方法[J].计算机应用研究,2010,27(1):240-243. 被引量:3

引证文献11

二级引证文献61

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部