Intrusion detection systems (IDS) are devices that send an alarm once any malicious activity is detected. However, it is a passive device as compared to intrusion prevention systems. There is a need for an intelligent IDS since that has a low false positives rate as compared to traditional IDS. The classification of cyber security attacks were done on a Canadian dataset due to its large size. Our main objective with this study was to focus on comparing deep learning classifiers against existing IDS classification algorithms.
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