DocumentCode
1814522
Title
Anomaly Traffic Detection Model Based on Dynamic Aggregation
Author
Sun, Zhixin ; Gong, Jin
Author_Institution
Coll. of Comput., Nanjing Univ. of Posts & Telecommun., Nanjing, China
fYear
2010
fDate
29-31 July 2010
Firstpage
46
Lastpage
50
Abstract
Integrated with the ideas of aggregation and network model, this paper presented an anomaly detection model based on DAATDM, i.e. the dynamic and aggregate anomaly detection model. Besides, it established an anomaly traffic detection system based on DAATDM. DAATDM not only analyzed the aggregation of network parameters but also built a weighted statistical model for aggregate parameters which can be set dynamically. DAATDM can adjust its dependency on network parameters so as to enhance the flexibility of anomaly detection and identify attack features.
Keywords
object detection; parameter estimation; statistical analysis; traffic engineering computing; DAATDM; anomaly traffic detection model; dynamic aggregation; network parameters; weighted statistical model; Aggregates; Computational modeling; Computer crime; Computers; Feature extraction; Floods; IP networks; Aggregation; Anomaly traffic; Dynamic detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Electronic Commerce and Security (ISECS), 2010 Third International Symposium on
Conference_Location
Guangzhou
Print_ISBN
978-1-4244-8231-3
Electronic_ISBN
978-1-4244-8231-3
Type
conf
DOI
10.1109/ISECS.2010.19
Filename
5557438
Link To Document