ISSN 1000-1239 CN 11-1777/TP

计算机研究与发展 ›› 2015, Vol. 52 ›› Issue (10): 2382-2394.doi: 10.7544/issn1000-1239.2015.20150494

所属专题: 2015网络安全与隐私保护研究进展

• 信息安全 • 上一篇    下一篇

基于环概化的半同构泛化算法研究

何贤芒1,4,陈银冬2,李东3,郝艳妮3   

  1. 1(宁波大学信息科学与工程学院 浙江宁波 315211); 2(汕头大学工学院 广东汕头 515063); 3(国家自然科学基金委员会信息中心 北京 100085); 4(复旦大学计算机科学技术学院 上海 200433) (hexianmang@nbu.edu.cn)
  • 出版日期: 2015-10-01
  • 基金资助: 
    基金项目:国家自然科学基金项目(61103244,61202007);广东省自然科学基金项目(2015A030313433);广东省高等学校优秀青年教师培养计划项目(Yq2013074);广东省高校工程技术研究中心建设项目(GCZX-A1306);汕头大学学术创新团队建设项目(ITC12001);信息与通信工程浙江省重中之重学科开放基金项目;宁波市自然科学基金项目(2013A610110)

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

摘要: 为了防止个人隐私的泄漏,通常在数据共享前需要对其在准标识符上的属性值作概化处理,以消除链接攻击,从而实现在共享中对敏感属性的匿名保护.数据的概化处理增加了属性值的不确定性,也不可避免地造成一定的信息损失.基于环概化(ring generalization)的异构处理算法能够在减少匿名化所导致的数据信息损失的同时,提供更强的隐私保护.提出生成所有基于环概化置换的算法,同时研究置换计数问题,证明了其基数满足O(α\+n),α>1.在此基础上,提出了一种半同构泛化算法,能在数据共享中实现匿名数据保护,同时降低概化所带来的数据信息损失.

关键词: 数据匿名, 隐私保护, 环概化, 异构算法, k-匿名

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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