Name
Abstract | ||
|---|---|---|
We propose discrimination methods that classify cluster of traffic behaviour of flash crowds and DDoS attacks such as traffic pattern and characteristics and check cluster randomness. The behavior-based clustering consolidates packet into clusters based on similarity of observed behavior, e.g., source IPs are clustered together based on their pattern of destination port usage. The main objectives are to find way to proactively resolve problems such as DDoS attacks by detection and resolving attacks in their early development stages. |
Year | Venue | Keywords |
|---|---|---|
2009 | SECRYPT 2009: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON SECURITY AND CRYPTOGRAPHY | DDoS,Flash crowd,Cluster |
Field | DocType | Citations |
Crowds,Denial-of-service attack,Computer security,Computer science,Computer network,Cluster analysis | Conference | 0 |
PageRank | References | Authors |
0.34 | 6 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Young-jun Heo | 1 | 4 | 2.52 |
| Jintae Oh | 2 | 25 | 7.28 |
| Jongsoo Jang | 3 | 55 | 13.43 |