A Dynamic Flooding Attack Detection System Based on Different Classification Techniques and Using SNMP MIB Data

Provided by: International Journal of Computer Networks and Communications Security (IJCNCS)
Topic: Networking
Format: PDF
Currently, the amount of exchanged data in network has increased dramatically and consequently, detection of malicious data is an important issue for network's users and administrators. DoS and DDoS attacks have always taken consideration of attackers and researchers, and distinguishing them from normal packet is difficult. Therefore, using data mining techniques along traditional mechanism such as firewall, improves the performance of intrusion detection systems. This paper introduces flooding attack detection system based on SNMP MIB data, which selects effective MIB variables and compares some different classification algorithms based on chosen variables.

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