Review of Intrusion Detection Systems Based on Machine Learning
Mohammed Hasan Ali, Karrar Al-Jawaheri, Myasar Mundher Adnan, Safa Riyadh Waheed, Karrar Abdulameer Kadhim, Mohd Shafry Mohd Rahim · 2021
Current days’ attacks detection represents a vital security tool because of monitoring activity for single device data follow or networks of devices. Moreover, traditional intrusion detection system still facing several limitations such as high rate of false alarm and low detection rate. Last decade machine learning represents one of the important development based on intrusion detection. This work divided various intrusion detection system based on machine learning as single models and hybrid models. Which gives the researchers new opportunities in this field. Furthermore, evaluation and measurement for complexity, a new type of dataset and time for running because of all these measurements necessary for more accurate results in comparison with relating works.