Secure Identity-Based Data Sharing and Profile Matching for Mobile Healthcare Social Networks in Cloud Computing
Secure Identity-Based Data Sharing and Profile Matching for Mobile Healthcare Social Networks in Cloud Computing
复制标题
云计算中移动医疗社交网络基于身份的安全数据共享和配置文件匹配
DOI：
10.1109/access.2018.2852784
复制
发表时间：
2018-01-01
期刊：
影响因子：
3.9
通讯作者：
Yang, Yixian
中科院分区：
文献类型：
--
作者：
Huang, Qinlong;Yue, Wei;Yang, Yixian
云计算和社交网络通过以具有成本效益的方式提供实时数据共享，正在改变医疗保健的方式。然而，数据安全问题是移动的医疗保健社交网络（MHSNs）广泛应用的主要障碍之一，因为健康信息被认为是高度敏感的。在本文中，我们介绍了一个安全的数据共享和配置文件匹配方案的MHSN在云计算。患者可以使用基于身份的广播加密技术将其加密的健康记录外包到云存储中，并以安全有效的方式与一组医生共享。然后，我们提出了一个基于属性的条件数据重新加密的结构，允许医生谁满足密文中的预定义条件，授权云平台将密文转换为一个新的密文的基于身份的加密方案的专家，而不会泄露任何敏感信息。此外，我们提供了一个配置文件匹配机制的MHSN基于基于身份的加密与平等测试，这有助于患者找到朋友的隐私保护的方式，并实现了灵活的授权加密的健康记录，抵抗关键字猜测攻击。此外，该机制降低了患者侧的计算成本。安全性分析和实验结果表明，该方案对于保护MHSN中数据的安全性和隐私性是切实可行的。
Cloud computing and social networks are changing the way of healthcare by providing real-time data sharing in a cost-effective manner. However, data security issue is one of the main obstacles to the wide application of mobile healthcare social networks (MHSNs), since health information is considered to be highly sensitive. In this paper, we introduce a secure data sharing and profile matching scheme for the MHSN in cloud computing. The patients can outsource their encrypted health records to cloud storage with an identity-based broadcast encryption technique, and share them with a group of doctors in a secure and efficient manner. We then present an attribute-based conditional data re-encryption construction which permits the doctors who satisfy the pre-defined conditions in the ciphertext to authorize the cloud platform to convert a ciphertext into a new ciphertext of an identity-based encryption scheme for specialist without leaking any sensitive information. Furthermore, we provide a profile matching mechanism in the MHSN based on identity-based encryption with an equality test, which helps patients to find friends in a privacy-preserving way and achieves flexible authorization on the encrypted health records with resisting the keywords guessing attack. Moreover, this mechanism reduces the computation cost on the patient side. The security analysis and experimental evaluation show that our scheme is practical for protecting the data security and privacy in the MHSN.