الفهرس 
Introduction and Review of Earlier WorkOnly 14 pages are availabe for public view
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Abstract
Network security breaches are jumping to a higher level every day,so network intrusion detection systems (NIDSs) must keep pace with this enormous increase in intrusion methods. Most of current NIDSs are rule-based systems, which deoend on ststic rules that are very difficult in encoding and can’t be useful in the detection of novel intrusions.Therefore,this thesis is concerned with proposing a hybrid network intrusion detection framwork that depends on data mining classification and clustering techniques in misuse and anomaly intrision detection.