Deterministic memory-efficient string matching algorithms for intrusion detection

By Nathan Tuck, Timothy Sherwood, Brad Calder, George Varghese. IEEE INFOCOM 2004, 2004

468 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Hardware and Architecture

View Paper: https://www.semanticscholar.org/paper/a3ced50247160da1a7c77dc643cf92dc03333e6a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Jonathan S. Turner
2. P. Crowley
3. S. Sushanth Kumar
4. Fang Yu
5. Sarang Dharmapurikar
6. Pavel Laskov

In Computer Networks and Communications

1. Jonathan S. Turner
2. P. Crowley
3. S. Sushanth Kumar
4. Fang Yu
5. Sarang Dharmapurikar
6. Pavel Laskov
7. Jennifer Rexford
8. Raouf Boutaba

In Hardware and Architecture

1. Jonathan S. Turner
2. P. Crowley
3. S. Sushanth Kumar
4. Fang Yu
5. Sarang Dharmapurikar

Citations in the corpus

• Algorithms to accelerate multiple regular expressions matching for deep packet inspection (2006, methodology): “In [11], Tuck et al. presents techniques to enhance the worst-case performance of Aho-Corasick algorithm.”
• Hamsa: fast signature generation for zero-day polymorphic worms with provable attack resilience (2006, background): “INPUT: Suspicious traffic pool M = {M1, M2 . . .}; the minimum token length `min and the minimum coverage λ. OUTPUT: A set of tokens T = {t1, t2, . . .} which meet the minimum length and coverage requirements and for each token the associated sample vector V(ti) = [ai1, . . . , ai|M|], i ∈ [1, |M”