An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Tracing Network Attacks to Their Sources
IEEE Internet Computing
DDoS attack detection using K-Nearest Neighbor classifier method
Telehealth/AT '08 Proceedings of the IASTED International Conference on Telehealth/Assistive Technologies
Hi-index | 0.00 |
Distributed Denial-of-Service(DDoS) attack can be done by generating a large volume of traffic through spoofing the IP address of DoS attacker The e-mail based attack is also similar with existing DDoS attack in network traffic status In response to such attacks, IP traceback technology has been proposed For example, the method identifies the source of a spoofed e-mail attack and restructures the path on the network through which the attacking packet has been transmitted This study proposed an improved marking technique that identifies DDoS traffics with TTL information at routers by applying the SVM module for malicious traffic control and cope with DDoS attack packets efficiently According to the result of experiments, the proposed technique reduced network load and improved filter/traceback performance.