Title :
Detection and Control of Anomaly Network Data Flows
Author :
Wenfang, Zhang ; Chi, Xu
Author_Institution :
Sch. of Archit. & Urban Planning, Hunan City Univ., Yiyang, China
Abstract :
Data flows is a type of dynamic data. After the detection of anomaly data flows, the next problem is how to control these anomaly data flows effectively and prevent network jam. Router queue management is an effective method of controlling anomaly data flows. When network is busy router can prevent it by active droppings. The characters of unresponsive of network congestion control and high-bandwidth were researched deeply to explore the malicious flow effects on the large-scale network. After that, experiments were implemented to present the network congestion collapse resulted from malicious flows and its influences on the network resource allocations.
Keywords :
computer network management; computer network reliability; computer network security; data flow analysis; queueing theory; telecommunication congestion control; telecommunication network routing; active dropping; anomaly network data flow control; anomaly network data flow detection; dynamic data; large-scale network; malicious flow effect; network congestion collapse; network congestion control; network jam prevention; network resource allocation; router queue management; Bandwidth; Data mining; Data models; Hidden Markov models; Internet; Intrusion detection;
Conference_Titel :
Computer Science & Service System (CSSS), 2012 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4673-0721-5
DOI :
10.1109/CSSS.2012.154