Unsupervised Anomaly Detection in Network Intrusion Detection Using Clusters
نویسندگان
چکیده
Most current network intrusion detection systems employ signature-based methods or data mining-based methods which rely on labeled training data. This training data is 90 typically expensive to produce. Moreover, these methods have difficulty in detecting new types of attack. In this paper, we have discussed anomaly based instruction detection, pros and cons of anomaly detection, supervised and unsupervised anomaly detection.
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