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Intrusion Detection Systems (IDS) provide substantial measures to protect networks assets. IDSs are software /hardware systems dedicated to exposing network threats. Signature-based, and anomalies detection are conventional approaches applied for the detection. Signature-based approach inspects the network traffic for a predefined threats signature pattern. This technique suffers limitations in detecting unprecedented attacks. The anomalies detection systems deploy methods to separate the normal and abnormal network traffics. These methods experience inaccurate results, e.g., high false-positives and true- negative alarms. Anomalies detection adopted various methods, for instance, statistical methods, rule-based, and machine learning algorithms. The neural network is one of the machine learning algorithms utilized in intrusion detection, unfortunately, with discouraging accuracy results. Recently …