Anomaly Base Network Intrusion Detection by Using Random Decision Tree and Random Projection A Fast Network Intrusion Detection Technique

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Provided by: Macrothink Institute
Topic: Security
Format: PDF
Network Intrusion Detection Systems (NIDSs) have become an important component in network security infrastructure. Currently, many NIDSs are rule-based systems whose performances highly depend on their rule sets. Unfortunately, due to the huge volume of network traffic, coding the rules by security experts becomes difficult and time-consuming. Since data mining techniques can build network intrusion detection models adaptively, data mining-based NIDSs have significant advantages over rule-based NIDSs. Network and system security is of paramount importance in the present data communication environment.
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