Abstract
In order to protect social network privacy information, a variety of social network graph anonymization technologies are proposed. The purpose of graph anonymization is to prevent privacy leakage through map modification operations, and at the same time guarantee the availability of data of anonymous graphs in social network analysis. The accuracy of reachability query is an important indicator to measure the availability of graph data. However, the current study ignores the influence of graph anonymity on the reachability of nodes, resulting in loss of greater accessibility information.In order to maintain the reachability of nodes in the anonymous graph, reachability preserving anonymization (RPA) is proposed.The (RPA) algorithm, whose basic idea is to group nodes and adopt greedy policies for anonymity, thereby reducing the loss of accessibility information in the anonymous process. In order to ensure the practicality of RPA algorithm, it is optimized for its execution efficiency.Use the candidate neighbor index, to further accelerate the anonymous process of RPA algorithm for each node. Experimental results based on real social network data show that the high execution efficiency of the RPA algorithm also validates the high precision of generating anonymous graphs for reachability queries.
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