ISSN 1000-1239 CN 11-1777/TP

Journal of Computer Research and Development ›› 2015, Vol. 52 ›› Issue (10): 2382-2394.doi: 10.7544/issn1000-1239.2015.20150494

Special Issue: 2015网络安全与隐私保护研究进展

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Study on Semi-Homogenous Algorithm Based on Ring Generalization

He Xianmang1,4, Chen Yindong2, Li Dong3, Hao Yanni3   

  1. 1(Faculty of Information Science and Engineering, Ningbo University, Ningbo, Zhejiang 315211);2(College of Engineering, Shantou University, Shantou, Guangdong 515063);3(Information Center, National Natural Science Foundation of China, Beijing 100085);4(School of Computer Science, Fudan University, Shanghai 200433)
  • Online:2015-10-01

Abstract: Data privacy has been a hot research topic in the database theory and cryptography communities in the past few decades. To prevent the disclosure of privacy, it requires preserving the anonymity of sensitive attributes in data sharing. The attribute values on quasi-identifiers often have to be generalized before data sharing to avoid linking attack, and thus to achieve the anonymity in data sharing. However, without careful treatment, it’s of high risk of privacy leakage for data anonymity. Among these solutions , data generalization is an important technique for privacy preserving in data publication and attracts considerable attention in the literature, which increases the uncertainty of attribute values, and leads to the loss of information to some extent. The non-homogenous algorithm which is based on ring generalization, can reduce the information loss, and in the meanwhile, offering strong privacy preservation. This paper presents an algorithm to generate all the permutations, and studies the cardinality of the permutations based on the ring generalization. In addition, we prove that its cardinality is O(α\+n), α>1. Furthermore, we propose a semi-generalization algorithm which can meet the requirement of preserving anonymity of sensitive attributes in data sharing, and greatly reduce the amount of information loss resulting from data generalization for implementing data anonymization.

Key words: data anonymization, privacy preservation, ring generalization, non-homogenous algorithm, k-anonymity

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