Name
Abstract | ||
|---|---|---|
The increasing number of network attacks causes growing problems for network operators and users. Thus, detecting anomalous traffic is of primary interest in IP networks management. In this paper we present a novel method for network anomaly detection, based on the idea of discovering Heavy Change (HC) in the distribution of the Heavy Hitters in the network traffic. To assess the validity of the proposed method, we have performed an extensive experimental evaluation phase, during which our system performance have been compared to a more “classical” HC-based approach. The performance analysis, presented in this paper, demonstrates the effectiveness of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/IWCMC.2011.5982727 | IWCMC |
Keywords | Field | DocType |
heavy hitter distribution,ip networks,network attacks,network traffic,anomaly detection,sketch,ip networks management,heavy change detection,anomalous traffic,hc-based approach,telecommunication network management,heavy change,telecommunication security,telecommunication traffic,performance analysis,heavy hitter,network operators,data models,data structures,statistical analysis,ddos attack,indexing terms,real time systems,approximation algorithms,system performance,traffic flow | Approximation algorithm,Data modeling,Data structure,Traffic generation model,Anomaly detection,Computer science,Telecommunication security,Computer network,Operator (computer programming),Distributed computing,Sketch | Conference |
ISSN | ISBN | Citations |
2376-6492 | 978-1-4244-9539-9 | 2 |
PageRank | References | Authors |
0.37 | 13 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christian Callegari | 1 | 81 | 9.05 |
| Stefano Giordano | 2 | 609 | 86.56 |
| Michele Pagano | 3 | 198 | 31.51 |
| Teresa Pepe | 4 | 123 | 11.26 |