Name
Abstract | ||
|---|---|---|
Sequence alignment algorithms, inspired by methods used in bioinformatics, have recently gained popularity in network applications. Smith-Waterman (SW) algorithm is one of the widely used alignment algorithm, but it has deficiency in alignment of network flows. In this paper, we propose an algorithm named ESW (Extended Smith Waterman) and a combinatorial reduction algorithm. Through combining merge clustering, special data structure and ESW, the combinatorial reduction algorithm can extract signatures from network flows containing worms more efficiently. The algorithms keep the accurate property of SW and have a low complexity. Our software implementation shows that the algorithms are suitable for network traffic and has remarkable superiority in dealing with background noise and cross infection. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ICNSC.2008.4525505 | ICNSC |
Keywords | Field | DocType |
special data structure,worms,invasive software,merge clustering,network traffic,combinatorial reduction algorithm,network flows,extended smith waterman algorithm,computer networks,digital signatures,traffic,bioinformatics,sequence alignment algorithm,data structures,sequence alignment,background noise,filtering,clustering algorithms,network flow,data mining,data structure,internet,payloads | Flow network,Sequence alignment,Data mining,Data structure,Background noise,Computer science,Algorithm,Digital signature,Smith–Waterman algorithm,Merge (version control),Cluster analysis | Conference |
ISSN | ISBN | Citations |
1810-7869 | 978-1-4244-1686-8 | 1 |
PageRank | References | Authors |
0.37 | 6 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xinghui Wang | 1 | 1 | 0.71 |
| Xu Du | 2 | 37 | 15.92 |