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基于双线性对的多用户公钥加密与多关键字搜索方案。

A Multi-User Public Key Encryption with Multi-Keyword Search out of Bilinear Pairings.

机构信息

State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China.

出版信息

Sensors (Basel). 2020 Dec 5;20(23):6962. doi: 10.3390/s20236962.

DOI:10.3390/s20236962
PMID:33291483
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7730920/
Abstract

Internet of Things (IoT) and cloud computing are adopted widely in daily life and industrial production. Sensors of IoT equipment gather personal, sensitive and important data, which is stored in a cloud server. The cloud helps users to save cost and collaborate. However, the privacy of data is also at risk. Public-key encryption with keyword search (PEKS) is convenient for users to use the data without leaking privacy. In this article, we give a scheme of PEKS for a multi-user to realize the multi-keyword search at once and extend it to show a rank based on keywords match. The receiver can finish the search by himself or herself. With private cloud and server cloud, most users' computing can be outsourced. Moreover, the PEKS can be transferred to a multi-user model in which the private cloud is used to manage receivers and outsource. The store cloud and the private cloud both obtain nothing with the keyword information. Then our IoT devices can easily run these protocols. As we do not use any pairing operations, the scheme is under more general assumptions that means the devices do not need to take on the heavy task of calculating pairing.

摘要

物联网(IoT)和云计算在日常生活和工业生产中得到了广泛应用。物联网设备的传感器收集个人的、敏感的和重要的数据,这些数据存储在云服务器中。云可以帮助用户节省成本和协作。然而,数据的隐私也存在风险。带有关键字搜索的公钥加密(PEKS)使用户在不泄露隐私的情况下方便地使用数据。在本文中,我们提出了一种多用户的 PEKS 方案,可以一次性实现多关键字搜索,并扩展到基于关键字匹配的排名。接收方可以自行完成搜索。通过私有云和服务器云,可以将大部分用户的计算外包出去。此外,PEKS 可以转换为多用户模型,其中私有云用于管理接收方并进行外包。存储云和私有云都不会获得关键字信息。然后,我们的物联网设备可以轻松运行这些协议。由于我们不使用任何配对操作,因此该方案基于更一般的假设,即设备不需要承担计算配对的繁重任务。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cbd/7730920/f5bc554f852e/sensors-20-06962-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cbd/7730920/594d388d9c64/sensors-20-06962-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cbd/7730920/8d200b2b7816/sensors-20-06962-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cbd/7730920/c0f1bba999cc/sensors-20-06962-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cbd/7730920/c31baed75449/sensors-20-06962-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cbd/7730920/592e06359bc1/sensors-20-06962-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cbd/7730920/eb4cbb31d18c/sensors-20-06962-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cbd/7730920/6446c8f9c97c/sensors-20-06962-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cbd/7730920/093334747e31/sensors-20-06962-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cbd/7730920/18e41cc55504/sensors-20-06962-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cbd/7730920/88fddb72717d/sensors-20-06962-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cbd/7730920/f5bc554f852e/sensors-20-06962-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cbd/7730920/594d388d9c64/sensors-20-06962-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cbd/7730920/8d200b2b7816/sensors-20-06962-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cbd/7730920/c0f1bba999cc/sensors-20-06962-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cbd/7730920/c31baed75449/sensors-20-06962-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cbd/7730920/592e06359bc1/sensors-20-06962-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cbd/7730920/eb4cbb31d18c/sensors-20-06962-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cbd/7730920/6446c8f9c97c/sensors-20-06962-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cbd/7730920/093334747e31/sensors-20-06962-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cbd/7730920/18e41cc55504/sensors-20-06962-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cbd/7730920/88fddb72717d/sensors-20-06962-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cbd/7730920/f5bc554f852e/sensors-20-06962-g011.jpg

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