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EPPS: Efficient and Privacy-Preserving Personal Health Information Sharing in Mobile Healthcare Social Networks

机译:EPPS:移动医疗社交网络中的高效且保护隐私的个人健康信息共享

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摘要

Mobile healthcare social networks (MHSNs) have emerged as a promising next-generation healthcare system, which will significantly improve the quality of life. However, there are many security and privacy concerns before personal health information (PHI) is shared with other parities. To ensure patients’ full control over their PHI, we propose a fine-grained and scalable data access control scheme based on attribute-based encryption (ABE). Besides, policies themselves for PHI sharing may be sensitive and may reveal information about underlying PHI or about data owners or recipients. In our scheme, we let each attribute contain an attribute name and its value and adopt the Bloom filter to efficiently check attributes before decryption. Thus, the data privacy and policy privacy can be preserved in our proposed scheme. Moreover, considering the fact that the computational cost grows with the complexity of the access policy and the limitation of the resource and energy in a smart phone, we outsource ABE decryption to the cloud while preventing the cloud from learning anything about the content and access policy. The security and performance analysis is carried out to demonstrate that our proposed scheme can achieve fine-grained access policies for PHI sharing in MHSNs.
机译:移动医疗保健社交网络(MHSN)已经成为有前途的下一代医疗保健系统,它将大大改善生活质量。但是,在与其他奇偶校验共享个人健康信息(PHI)之前,存在许多安全和隐私问题。为了确保患者完全控制自己的PHI,我们提出了一种基于基于属性的加密(ABE)的细粒度且可扩展的数据访问控制方案。此外,用于PHI共享的策略本身可能很敏感,并且可能会泄露有关底层PHI或有关数据所有者或接收者的信息。在我们的方案中,我们让每个属性包含一个属性名称及其值,并采用Bloom过滤器在解密之前有效地检查属性。因此,可以在我们提出的方案中保留数据隐私和策略隐私。此外,考虑到计算成本随着访问策略的复杂性以及智能手机中资源和能源的限制而增长的事实,我们将ABE解密外包给了云,同时阻止了云对内容和访问策略的任何了解。进行安全性和性能分析以证明我们提出的方案可以实现MHSN中PHI共享的细粒度访问策略。

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