期刊文献+

基于域名系统属性的速变服务网络检测方法 被引量:1

Fast-Flux Detection Method Based on Domain Name System Attribute
下载PDF
导出
摘要 基于对速变服务网络(Fast-flux service network,FFSN)的工作原理、申请流程、相关特征等分析,设计FFSN的检测流程,并提出了一种区分速变服务网络与合法网络的方法:详细分析两者相关域名系统属性的差异,构建检测特征,使用决策树算法检测速变服务网络的存在。实验证明,该方法可有效识别FFSN,具有较高的检测率。 The fast-flux service network (FFSN) testing process is designed based on the analysis of its working principle, application process and related characteristics. A method for distinguishing rapid change service network and legal network is put forward and the system attributes differences of the related domain name system are analyzed with details. The testing characteristics are constructed and the existence of rapid change service network is tested by decision tree algorithm. The experimental results show that this method can effectively identify FFSN and has a high detection rate.
作者 王佳佳 叶钰 李世杰 刘惠光 王一帆 WANG Jia-jia;YE Yu;LI Shi-jie;LIU Hui-guang;WANG Yi-fan(School of Information Technology, Taizhou Polytechnic College, Taizhou 225300, China)
出处 《南通职业大学学报》 2019年第3期77-82,共6页 Journal of Nantong Vocational University
基金 泰州职业技术学院博硕基金项目(TZYBS-17-6) 泰州职业技术学院大学生创新创业训练项目(YJDC2018017)
关键词 速变服务网络(FFSN) 域名系统 决策树算法 网络检测 网络安全 fast-flux service network (FFSN) domain name system decision tree algorithm network detection network security
  • 相关文献

参考文献2

二级参考文献21

  • 1Riden J. Know your enemy: fast-flux service net- works [EB/OL]. (2008-08-16)[2015-05-01]. http:// www.honeynet.org/papers/ff. 被引量:1
  • 2Perdisci R, Corona I, Giacinto G. Early detection of malicious flux networks via large-scale passive DNS traffic analysis. IEEE Transactions on Dependable and Secure Computing, 2012, 9(5): 714-726. 被引量:1
  • 3Weimer F. Passive DNS replication // FIRST Conference on Computer Security Incident. Singa- pore, 2005:1-13. 被引量:1
  • 4Mockapetris P V. Domain names, concepts and facilities [EB/OL]. (1987)[2015-03-01]. http://tools.iet f.org/html/rfc 1034. 被引量:1
  • 5Holz T, Gorecki C, Rieck K, et al. Measuring and detecting fast-flux service networks // NDSS, San Diego, 2008:487--492. 被引量:1
  • 6Passerini E, Paleari R, Martignoni L, et al. Fluxor: detecting and monitoring fast-flux service networks// Detection of Intrusions and Malware, and Vulnera- bility Assessment. Berlin: Springer, 2008:186-206. 被引量:1
  • 7Huang S Y, Mao C H, Lee H M. Fast-flux service network detection based on spatial snapshot mecha- nism for delay-free detection//Proceedings of the 5th ACM Symposium on Information, Computer and Communications Security. Beijing, 2010:101-111. 被引量:1
  • 8Antonakakis M, Perdisci R, Dagon D, et al. Building a dynamic reputation system for DNS // USENIX Security Symposium. Washington DC, 2010:273-290. 被引量:1
  • 9Bilge L, Kirda E, Kruegel C, et al. EXPOSURE: finding malicious domains using passive DNS analysis//NDSS. San Diego, 2011:1-5. 被引量:1
  • 10Pedregosa F, Varoquaux G, Gramfort A, et al. Scikit- learn: machine learning in Python. The Journal of Machine Learning Research, 2011, 12:2825-2830. 被引量:1

共引文献14

同被引文献2

引证文献1

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