Research on network information leakage prevention method based on k-symmetric anonymous algorithm

Abstract

In order to prevent the leakage of privacy information in published network data and improve the security of network information, a network information leakage prevention method based on K-symmetric anonymity algorithm is proposed. The relationship between individuals in the network is analyzed, and the network information graph is constructed based on graph theory to intuitively reflect the relationship between nodes in the network. The detailed query method is used to judge whether each node in the network information graph has a corresponding self-conserved equivalent node, and the simple symmetric processing is carried out to ensure that each node has a self-conserved equivalent node. Use the K-symmetric anonymous processing method to copy all nodes that have been treated with simple symmetry so that each set of equivalence classes contains more than two nodes. With the addition of network nodes, the network topology changes significantly, which reduces the probability of the attacker identifying network nodes. The improved K-symmetric anonymous algorithm only performs symmetric processing on the nodes with moderately minimal processing results. While reducing the system overhead, the network topology also presents irregular changes, making it difficult for attackers to discover the topology of the original graph, and increasing the difficulty of network information cracking. The experimental results show that this method can effectively prevent network information leakage, and has good information availability and confidentiality. By constructing a network information graph and analyzing the relationship between individuals in the network based on graph theory, the effective protection of network information is realized. It improves the security of network information and reduces the risk of disclosure of private information.