Name
Abstract | ||
|---|---|---|
•Multiple attributes from IP flows are combined to detect anomalous events.•GA metaheuristic used for Digital Signature of Network Segment using Flow Analysis.•Unsupervised training technique applied efficiently for network traffic profiling.•Fuzzy Logic improved accuracy and false positives compared to state of art. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.eswa.2017.09.013 | Expert Systems with Applications |
Keywords | Field | DocType |
Network management,Network Anomaly Detection System,Genetic Algorithm,Fuzzy Logic | Flow network,Traffic generation model,Data mining,Anomaly detection,Network segment,Computer science,Fuzzy logic,Network simulation,Artificial intelligence,Network management,Network traffic control,Machine learning | Journal |
Volume | Issue | ISSN |
92 | C | 0957-4174 |
Citations | PageRank | References |
11 | 0.47 | 29 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anderson H. Hamamoto | 1 | 11 | 0.47 |
| Luiz Fernando Carvalho | 2 | 77 | 7.40 |
| Lucas Dias H. Sampaio | 3 | 26 | 4.10 |
| Taufik Abrão | 4 | 126 | 36.18 |
| Mario Lemes Proença Jr. | 5 | 188 | 20.31 |