Intrusion detection algorithm selection

This research is used to develop and evaluate an intrusion detection system. It contains network traffic data that can be analyzed to distinguish between normal and malicious activities. This research serves as the basis for training and testing different machine learning algorithms in order to determine the most effective model for intrusion detection. Various machine learning techniques will be implemented and compared based on their performance in detecting potential cyber attacks. In addition, optimization methods will be applied to improve the accuracy and efficiency of the selected model for intrusion detection tasks.