Analysis of network intrusion detection based on machine learning

Network security is the basis of social and economic development and order stability, and the situation of network intrusion is becoming more and more serious, which can ensure network security through network detection and analyzing network intrusion detection based on machine learning algorithms. Traditional network intrusion detection means have defects in intrusion identification, so introduce an ant colony algorithm and design a network intrusion detection method. The optimal selection of weights and thresholds can be achieved by path finding and other means to achieve the purpose of effective network intrusion detection. Through experiments to confirm the high network intrusion detection accuracy, and the advantages of fast speed and low error rate, it can be seen that the detection model has a high application value.