全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

僵尸网络指纹特征自动提取技术

DOI: 10.13190/jbupt.201104.109.wangxl, PP. 109-112

Keywords: 僵尸网络,指纹特征提取,聚类

Full-Text   Cite this paper   Add to My Lib

Abstract:

为了能够快速掌握指纹特征并及时准确检测新型僵尸网络,对指纹特征提取算法进行了研究.在已有算法的基础上依据僵尸网络指纹特征分布的特点,提出了适用于该指纹特征自动提取的算法及系统设计框架,使其能够自适应地对不同功能的数据流分别进行指纹特征提取.实验结果表明,改进后算法获取的有效指纹特征数要远远优于改进前算法提取的有效特征数,从而能够更好地检测僵尸网络的众多变种.

References

[1]  林平, 余循宜, 刘芳, 等. 基于流统计特性的网络流量分类算法[J]. 北京邮电大学学报, 2008, 31(2): 15-19.
[2]  Kim H, Karp B. Autograph: toward automated, distributed worm signature detection//Proceedings of the 13th conference on USENIX Security Symposium. Berkeley: USENIX Association, 2004.
[3]  Singh S, Estan C, Varghese G, et al. Automated worm fingerprinting//Proceedings of the 6th Conference on Symposium on Opearting Systems Design & Implementation. Berkeley: USENIX Association, 2004.
[4]  Patrick Haffner. ACAS: automated construction of application signatures//Proceedings of the 2005 ACM SIGCOMM Workshop on Mining Network Data. New York: ACM, 2005: 197-202.
[5]  Ye Mingjiang, Xu Ke, Wu Jianping. Auto sig-automatically generating signatures for applications//IEEE International Conference on Computer and Information Technology. Xiamen: , 2009: 104-109.
[6]  Yang Jie, Ma Jing. Signature based identification of P2P streaming media traffic//2010 2nd International Conference on Intellectual Technology in Industrial Practice. China: Institute of Electrical and Electronics Engineers, 2010: 308-312.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133