Topology construction method of anti-tracking network based on cross-domain decentralized gravity model

With the increasing threats of network tracking and information leakage, privacy protection has become a widely concern in the field of network security. As an important means of protecting the privacy of network users, anti-tracking networks have gradually become one of the important research directions. However, the existing topology structures of anti-tracking networks still have problems such as intra-domain aggregation and key nodes, which are vulnerable to attack, tracking and destruction, and can not meet the privacy requirements. Therefore, this paper proposes a topology construction method based on cross-domain decentralized gravity model (CDTC). Firstly, the model comprehensively considers the local neighbor information, the location information of nodes, and the path information between nodes to calculate the node attraction. Secondly, each node determines its link status with other nodes through the model by ranking its local nodes, achieving optimization of the network topology. Finally, experiments on typical network structures and open network datasets, the experimental results show that the proposed model has better decentralization, cross-domain, and anti-tracking performance.