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Secure Fine-Grained Encrypted Keyword Search for E-Healthcare Cloud

机译:确保精细粒度加密关键字搜索电子医疗保健云

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摘要

E-Healthcare systems are increasingly popular due to the introduction of wearable healthcare devices and sensors. Personal health records (PHRs) are collected by these devices and stored in a remote cloud. Due to privacy concern, these records should not be accessible by any unauthorized party, and the cloud providers should not be able to learn any information from the stored records. To address the above issues, one promising solution is to employ attribute based encryption (ABE) for fine-grained access control and searchable encryption for keyword search on encrypted data. However, most of existing ABE schemes leak the privacy of access policy which may also contain sensitive information. On the other hand, for users' devices with limited computing power and bandwidth, the mechanism should enable them to be able to search the PHRs efficiently. Unfortunately, most existing works on ABE do not support efficient keyword search on encrypted data. In this work, we propose an efficient hidden policy ABE scheme with keyword search. Our scheme enables efficient keyword search with constant computational overhead and constant storage overhead. Moreover, we enhance the recipient's privacy which hides the access policy. As of independent interest, we present a trapdoor malleability attack and demonstrate that some of previous schemes may suffer from such attack.
机译:由于推出可穿戴医疗保健装置和传感器,电子医疗保健系统越来越受欢迎。个人健康记录(PHRS)由这些设备收集并存储在远程云中。由于隐私问题,任何未经授权的方都不应访问这些记录,并且云提供商不应该能够从存储的记录中学习任何信息。为了解决上述问题,一个有希望的解决方案是为在加密数据上使用基于属性的加密(ABE)进行细粒度访问控制和可搜索的加密。但是,现有的大多数ABE计划泄露了访问策略的隐私,该策略也可能包含敏感信息。另一方面,对于具有有限计算功率和带宽的用户设备,该机制应使其能够有效地搜索PHRS。不幸的是,ABE上的大多数现有工作不支持加密数据的有效关键字搜索。在这项工作中,我们提出了一个有效的隐藏策略ABE方案,其中包含关键字搜索。我们的方案使能有效的关键字搜索具有恒定的计算开销和恒定存储开销。此外,我们加强了收件人隐私,隐藏获取政策。由于独立兴趣,我们展示了一个陷阱间隙攻击,并证明了以前的一些计划可能会遭受这种攻击。

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