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This paper presents an online real-time network response system, which can determine whether a LAN is suffering from a flooding attack within a very short time unit. The detection engine of the system is based on the incremental mining of fuzzy association rules from network packets, in which membership functions of fuzzy variables are optimized by a genetic algorithm. The proposed online system belongs...
None of the previously proposed Network Intrusion Detection Systems (NIDSs), which are subject to fuzzy association rules, can meet real-time requirements because they all apply static mining approaches. This study proposed a real-time NIDS with incremental mining for fuzzy association rules. By consistently comparing the two rule sets, one mined from online packets and the other mined from training...
The fuzzy association rule has been proven to be effective to present userspsila network behavior offline from a huge amount of collected packets. However, not only effectiveness, efficiency is important as well for Network Intrusion Detection Systems (NIDSs). None of those proposed NIDSs subject to fuzzy association rule can meet the real-time requirement because they all applied static mining approach...
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