Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
Bro: a system for detecting network intruders in real-time
Computer Networks: The International Journal of Computer and Telecommunications Networking
Heaviest Increasing/Common Subsequence Problems
CPM '92 Proceedings of the Third Annual Symposium on Combinatorial Pattern Matching
Matrix Longest Common Subsequence Problem, Duality and Hibert Bases
CPM '92 Proceedings of the Third Annual Symposium on Combinatorial Pattern Matching
Polygraph: Automatically Generating Signatures for Polymorphic Worms
SP '05 Proceedings of the 2005 IEEE Symposium on Security and Privacy
Unexpected means of protocol inference
Proceedings of the 6th ACM SIGCOMM conference on Internet measurement
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Autograph: toward automated, distributed worm signature detection
SSYM'04 Proceedings of the 13th conference on USENIX Security Symposium - Volume 13
On web browsing privacy in anonymized NetFlows
SS'07 Proceedings of 16th USENIX Security Symposium on USENIX Security Symposium
Network Traffic Classification by Common Subsequence Finding
ICCS '08 Proceedings of the 8th international conference on Computational Science, Part I
Privacy oracle: a system for finding application leaks with black box differential testing
Proceedings of the 15th ACM conference on Computer and communications security
Comparing files using structural entropy
Journal in Computer Virology
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String comparison algorithms, inspired by methods used in bioinformatics, have recently gained popularity in network applications. In this paper we demonstrate the need for careful selection of alignment models if such algorithms are to yield the desired results when applied to network traffic. We introduce a novel variant of the Jacobson-Vo algorithm employing a flexible gap-minimising alignment model suitable for network traffic, and find that our software implementation outperforms the commonly used Smith-Waterman approach by a factor of 33 on average and up to 58.5 in the best case on a wide range of network protocols.