DocumentCode
123474
Title
Polymorphic worms signature extraction based-on improved ant colony algorithm
Author
Wan YuWen ; You JinXin ; Guo Fan ; Xu ShuFang
Author_Institution
Coll. of Comput. Inf. & Eng., Jiangxi Normal Univ., Nanchang, China
fYear
2014
fDate
22-24 Aug. 2014
Firstpage
723
Lastpage
727
Abstract
Polymorphic worm signature extraction is a critical part of signature-based intrusion detection. Since the classical Hierarchical Multi-Sequence Alignment(HMSA) algorithm has bad time performance in extracting signatures when multiple sequences alignment was used and the extracted signatures were not precise enough, a new method called antMSA was proposed base on the improved ant optimal algorithm. The search strategy of the ant group was improved and introduced to the Contiguous Matches Encouraging Needleman-Wunsch(CMENW) algorithm to get a better solution quickly in global range by using the rapid convergence ability of the ant colony algorithm. The signature fragments were extracted and converted into the standard rules of the intrusion detection systems for subsequence defense. The experimental results show that the new method solves the stagnation problems of the classical ant optimal algorithm, and reduces the false positive rate and the false negative rate.
Keywords
ant colony optimisation; digital signatures; invasive software; CMENW algorithm; HMSA algorithm; antMSA; contiguous matches encouraging Needleman-Wunsch algorithm; false negative rate; false positive rate; hierarchical multisequence alignment algorithm; improved ant colony algorithm; optimal algorithm; polymorphic worm signature extraction; signature-based intrusion detection system; Computers; Grippers; Indexes; ant colony algorithm; intrusion detection; polymorphic worms; sequence alignment; signature extraction;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science & Education (ICCSE), 2014 9th International Conference on
Conference_Location
Vancouver, BC
Print_ISBN
978-1-4799-2949-8
Type
conf
DOI
10.1109/ICCSE.2014.6926557
Filename
6926557
Link To Document