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• W2038761746 abstract "The proliferation and ever-increasing capabilities of mobile devices such as smart phones give rise to a variety of mobile sensing applications. This paper studies how an untrusted aggregator in mobile sensing can periodically obtain desired statistics over the data contributed by multiple mobile users, without compromising the privacy of each user. Although there are some existing works in this area, they either require bidirectional communications between the aggregator and mobile users in every aggregation period, or has high computation overhead and cannot support large plaintext spaces. Also, they do not consider the Min aggregate which is quite useful in mobile sensing. To address these problems, we propose an efficient protocol to obtain the Sum aggregate, which employs an additive homomorphic encryption and a novel key management technique to support large plaintext space. We also extend the sum aggregation protocol to obtain the Min aggregate of time-series data. Evaluations show that our protocols are orders of magnitude faster than existing solutions." @default.
• W2038761746 created "2016-06-24" @default.
• W2038761746 creator A5034663296 @default.
• W2038761746 creator A5061264042 @default.
• W2038761746 date "2012-10-01" @default.
• W2038761746 modified "2023-09-24" @default.
• W2038761746 title "Efficient and privacy-preserving data aggregation in mobile sensing" @default.
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• W2038761746 doi "https://doi.org/10.1109/icnp.2012.6459985" @default.
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