Implementation of Evolutionary Algorithm for Graph Anonymization (EAGA)
EAGA is an algorithm for k-degree anonymization on networks. It uses the concept of evolutionary algorithm to anonymize the degree sequence of the network. Then, it applies edge swap to modify graph structure in order to implement to the anonymized k-degree sequence.
It was published in:
Casas-Roma, J., Herrera-Joancomartí, J., & Torra, V. (2013). Evolutionary Algorithm for Graph Anonymization. Arxiv: http://arxiv.org/abs/1310.0229v2
Abstract: In recent years there has been a significant increase in the use of graphs as a tool for representing information. It is very important to preserve the privacy of users when one wants to publish this information, especially in the case of social graphs. In this case, it is essential to implement an anonymization process in the data in order to preserve users’ privacy. In this paper we present an algorithm for graph anonymization, called Evolutionary Algorithms for Graph Anonymization (EAGA), based on edge modifications to preserve the k-anonymity model.