Name
Title | ||
|---|---|---|
Building Efficient Regular Expression Matchers Through GA Optimization With ML Surrogates |
Abstract | ||
|---|---|---|
Important network functions such as traffic classification and intrusion detection often depend on high-throughput regular expression matching. To achieve high performance, regular expressions can be represented as state machines, which are then merged. However, determining which individual state machines should ideally be merged together is a challenging optimization problem. We address this prob... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/NoF52522.2021.9609828 | 2021 12th International Conference on Network of the Future (NoF) |
Keywords | DocType | ISBN |
Regular expressions,Genetic algorithms,Surrogate models,Traffic classification,DPI,IDS,DFA,NFA | Conference | 978-1-6654-2434-9 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jonathan Hillblom | 1 | 0 | 0.34 |
| Johan Garcia | 2 | 101 | 12.66 |
| Anders Waldenborg | 3 | 0 | 0.34 |