Evolutionary Algorithm for Graph Anonymization
نویسندگان
چکیده
In recent years, there has been a significant increase in the use of graph-formatted data. Socials networks, among others, represent relationships among users and present interesting information for researches and other third-parties. The problem appears when someone wants to publicly release this information, especially in the case of social or healthcare networks. In these cases, it is essential to implement an anonymization process in the data in order to preserve the privacy of users who appears in the network. In this paper we present an algorithm for graph anonymization, called Evolutionary Algorithm for Graph Anonymization (EAGA), based on edge modifications to preserve the k-anonymity model.
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عنوان ژورنال:
- CoRR
دوره abs/1310.0229 شماره
صفحات -
تاریخ انتشار 2013