Evaluation of Network Dynamic Defense Effectiveness Based on Ant Colony Optimization Algorithm

In recent years, the idea of NDD (Network Dynamic Defense) has received increasing attention from academia and industry, and mobile target defense technologies applied to multiple levels of information systems have been continuously proposed, achieving certain defense effects. NDD is a network security mechanism that increases the difficulty and cost of attacks by effectively reducing the similarity, certainty, and stationarity of network systems during deployment and operation. This article attempts to evaluate the effectiveness of NDD based on the ACO (Ant Colony Optimization) algorithm. The research results show that the risk value of this method can generally be controlled around 2.5. However, the hazard values of the other two methods are above 3.5. It can be seen that the evaluation method in this article has high comprehensiveness and accuracy in assessing network security risks, making it easy for network administrators to clarify network dynamics and accurately reflect the security risks of police equipment multi video monitoring networks. By using the ACO algorithm’s intrusion success probability limit theorem and proving the theorem through the limit transformation of the intrusion success probability calculation formula, the optimal transformation space calculation method is ultimately obtained.