通信学报

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面向社交网络的隐私保护方案

吕志泉,洪 澄,张 敏,冯登国,陈开渠   

  1. 1.中国科学院 软件研究所 可信计算与信息保障实验室,北京 100190; 2. 中国科学院大学,北京 100049;3. 国家超级计算深圳中心,广东 深圳 518055
  • 出版日期:2014-08-25 发布日期:2014-08-15
  • 基金资助:
    国家自然科学基金资助项目(61232005, 61100237, 91118006);深圳市战略新兴产业发展专项资金基金资助项目(CXZZ20120831113048965)

Privacy-perserving scheme for social networks

  • Online:2014-08-25 Published:2014-08-15

摘要: 针对社交网络的隐私安全问题,提出了一种新的社交网络隐私保护方案。首先设计了带陷门的属性加密算法,由属性权威机构与数据属主协同完成用户私钥的生成与分发,有效降低了数据属主的密钥管理代价。然后,通过令牌树机制控制用户对属性陷门的获取,实现了高效的属性撤销。安全性分析表明,该方案能够避免社交网络服务提供商与系统内部非授权用户的合谋攻击,且不泄漏用户的任何属性信息。实验结果证实,该方案在计算代价、存储代价等方面比现有方案更有优越性。

Abstract: The security and privacy issues in SNS were studied and a privacy-preserving scheme PPSNS was proposed. PPSNS utilizes attribute-based encryption, allowing the SNS user to set up an enforcement of fine-grained access control upon the data he owns, thus the potential threats from unauthorized parties or even the SNS provider itself could be avoided. A token system in PPSNS is included to address the challenging issue of efficient attribute revocation. In addition, the users in PPSNS don’t have to manage as much information as they do in other encryption-based solutions, achieving a much lower cost in the client side. Analyses show that PPSNS is secure, and gives a better performance in computing and storage costs compared to most related works.

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