期刊
IEEE INTERNET OF THINGS JOURNAL
卷 6, 期 6, 页码 9868-9879出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2019.2932775
关键词
Cloud-Internet of Things (IoT) computing; data privacy; homomorphic encryption; Internet of Battlefield Things (IoBT); K nearest neighbor (KNN) query; uncertain data
资金
- National Science Foundation of China [61871064, 61501080, 61771090, 61601214]
- Fundamental Research Funds for the Central Universities [DUT19JC08]
- Guangxi Key Laboratory of Trusted Software [kx201903]
- JSPS Kiban(B) [18H03240]
- JSPS Kiban(C) [18K11298]
- Cloud Technology Endowed Professorship
Uncertain data pervades many fields, including environmental monitoring, the monitoring of animal migrations, and urban warfare. Such uncertain data collected by field devices, such as Internet of Things (IoT) and Internet of Battlefield Things (IoBT) devices, may also be encrypted and outsourced to an untrustworthy third party for storage and data sharing such as a cloud server. However, the properties of uncertain data and the complication of operating over encrypted data make the searching schemes more ineffective. In this article, we design an efficient and safe K nearest neighbor (KNN) query scheme for uncertain data stored in semi-trusted cloud servers. We apply the modified homomorphic encryption, which requires two servers to interact and encrypt the uncertain data, and we use the authorized rank method to compute KNN. We protect the security of the data while simultaneously improving the query efficiency. Our detailed security analysis show that our scheme can realize the goal of concealing both the access and the search patterns. Comprehensive experiments are conducted to demonstrate the scheme's performance.
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