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中文摘要：
快速而准确地提取蠕虫特征对于有效防御多态蠕虫的传播至关重要，但是目前的特征产生方法在噪音干扰下无法产生正确的蠕虫特征．提出基于彩色编码的特征自动提取算法CCSF（color coding signature finding）来解决有噪音干扰情况下的多态蠕虫特征提取问题．CCSF算法将可疑池中的n条序列分成m组，然后运用彩色编码对每组序列进行特征提取．通过对每组提取出来的特征集合进行过滤筛选，最终产生正确的蠕虫特征．采用多类蠕虫对CCSF算法进行测试，并与其他蠕虫特征提取方法进行比较，结果表明，CCSF算法能够在有噪音干扰的条件下准确地提取出多态蠕虫的特征孩特征不包含碎片汤于应用到IDS（intrusion detection svstem）中对多态蠕虫进行检测．
英文摘要：
A fast and accurate generation of worm signatures is essential in efficiently defending worm propagation. Most of the recent signature generation approaches do not generate accurate signatures for polymorphic worms in environments with noise. In this paper, a CCSF （color coding signature finding） algorithm is presented to solve the problem of a polymorphic worm signature generation with noise by using color coding. In the CCSF algorithm, n sequences are divided into m group, and signatures for every group sequence are generated by color coding. After filtering all signatures, an accurate worm signature is generated. CCSF＇s range of polymorphic worms is evaluated. When comparing CCSF with other existing approaches, CCSF shows a distinct advantages in generating accurate signatures for polymorphic worms in the presence of noise. Signatures generated do not contain fragments and can be used conveniently to detect polymorphic worms in IDS （intrusion detection system）.
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