通信学报 ›› 2014, Vol. 35 ›› Issue (9): 12-19.doi: 10.3969/j.issn.1000-436x.2014.09.002

• 论文Ⅰ 网络攻击与防范 • 上一篇    下一篇

基于种子——扩充的多态蠕虫特征自动提取方法

汪洁,何小贤   

  1. 中南大学 信息科学与工程学院,湖南 长沙 410083
  • 出版日期:2014-09-25 发布日期:2017-06-14
  • 基金资助:
    国家自然科学基金资助项目

Automated polymorphic worm signature generation approach based on seed-extending

Jie WANG,Xiao-xian HE   

  1. School of Information Science and Engineering,Central South University,Changsha 410083,China
  • Online:2014-09-25 Published:2017-06-14
  • Supported by:
    The National Natural Science Foundation of China

摘要:

提出基于种子—扩充的多态蠕虫特征自动提取方法 SESG。SESG 算法首先按序列的权重大小将其放入一个队列,然后依序 次对队列中的种子序列进行扩充,从而对各类蠕虫以及噪音序列进行分类,并从分类后的蠕虫列中提取其特征。测试结果表明,SESG 算法能够在包含噪音的可疑池中很好地区分各类蠕虫序列,更易于提取有效的蠕虫特征。

关键词: 信息安全, 种子扩充算法, 多态蠕虫, 蠕虫检测, 蠕虫特征

Abstract:

A polymorphic worm signature generation approach based on seed-extending,SESG,was proposed.Firstly,algorithm SESG puts all sequences into a queue based on their weight.Seed sequence in the queue is extended,and all kinds of worm sequences and noise sequences are classified.Finally,worm signature is generated from classified worm sequences.Experiments are run to test SESG and compared with other approaches.Experiment results show that SESG can classify worm sequences and noise sequences from suspicious flow pool over other existed approaches,which can generate effective worm signature more easily.

Key words: nformation security, seed-extending algorithm, polymorphic worm, worm detection, worm signature

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