Privacy-Preserving Lightweight Data Monitoring in Internet of Things Environments
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Privacy‑Preserving Lightweight Data Monitoring in Internet of Things Environments Meng Zhao1,2 · Yong Ding1,3 · Qianhong Wu4,5 · Yujue Wang1 · Bo Qin6 · Kefeng Fan7
© Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract The fast development of Internet of Things (IoT) has shown that it becomes one of the most popular techniques. In the IoT paradigm, ubiquitous sensors and smart devices can be interconnected to collect various status data and share with others. When deployed in an environment status monitoring system, distributed sensors may be requested to periodically report real-time data. The large-scale data would make the system controller unable to process in time. In this case, a third-party server can be engaged to conduct most of monitoring work, where sensors direct report to the server to generate intermediate monitoring results for the system controller. However, the server may be curious about the contents of outsourced system standing queries, data vectors of sensors, and monitoring results. In addition, due to the limited computing resources of distributed sensors, existing cryptographic solutions are not applicable to such monitoring scenario. To address these issues, this paper proposes a lightweight server-aided data monitoring scheme (SIM). Thorough efficiency and privacy analysis confirm the practicality of the proposed SIM scheme. Moreover, this paper extends Lu et al.’s privacy-preserving cosine similarity computing protocol in the two-party setting in big data environment to support computing on any dimensional data, without incurring expensive calculations. Keywords Data monitoring · Privacy protection · Internet of Things · Delegated computing
This article is supported in part by the National Key R&D Program of China through project 2017YFB1400700, the National Natural Science Foundation of China under Projects 61862012, 61772150, 61772538, 61672083, 61862011, 61962012, 61972019, 61932011 and 91646203, the Guangxi Key R&D Program under Project AB17195025, the Guangxi Natural Science Foundation under Grants 2018GXNSFDA281054, 2018GXNSFAA281232, 2019GXNSFFA245015, 2019GXNSFGA245004 and AD19245048, the Peng Cheng Laboratory Project of Guangdong Province PCL2018KP004, the National Cryptography Development Fund through project MMJJ20170106, and the foundation of Science and Technology on Information Assurance Laboratory through project 61421120305162112006. * Yong Ding [email protected] Extended author information available on the last page of the article
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1 Introduction Internet of Things (IoT) is one of the today’s most exciting techniques. With the IoT technique, sensors and smart objects can be connected into a network of some form [1]. It provides a promising way for users to collect and infer various status data of the connected objects, as well as to issue control commands. The IoT paradigm is useful in many practical applications, for example, in industrial control systems, personalised healthcare systems and smart
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