Name
Abstract | ||
|---|---|---|
Recently, network traffic has become more complex and diverse because of the emergence of new applications and services. Therefore, the importance of application-level traffic classification is increasing rapidly, and it has become a very popular research area. Although a lot of methods for traffic classification have been introduced in literature, they have some limitations to achieve an acceptable level of performance in real-time application-level traffic classification. In this paper, we propose a novel application-level traffic classification method using payload size sequence signature. The proposed method generates unique payload size sequence signatures for each application using packet order, direction, and payload size of the first N packets in a flow and uses them to identify application traffic. The evaluation shows that this method can classify application traffic easily and quickly with high accuracy and completeness rates, over 99.93% and 93.45%, respectively. Furthermore, the method can classify each application traffic into its respective individual application. The evaluation shows that the method can classify all applications traffic, known and unknown (new) applications into their respective applications, and it can classify applications traffic that use the same application protocol or are encrypted into each other. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1002/nem.1981 | INTERNATIONAL JOURNAL OF NETWORK MANAGEMENT |
Field | DocType | Volume |
Traffic classification,Data mining,Traffic generation model,Computer science,Network packet,Encryption,Application protocol,Completeness (statistics),Payload | Journal | 27 |
Issue | ISSN | Citations |
5 | 1055-7148 | 3 |
PageRank | References | Authors |
0.39 | 10 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kyu-Seok Shim | 1 | 7 | 7.72 |
| Jae-Hyun Ham | 2 | 7 | 1.90 |
| Baraka D. Sija | 3 | 6 | 2.58 |
| Myung-Sup Kim | 4 | 325 | 45.01 |