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 timeseries data. Evaluations show that our protocols are orders of magnitude faster than existing solutions.
Li and Cao REF proposed an efficient protocol to obtain the Sum aggregation, which employs an additive homomorphic encryption and a novel key management technique to support large plaintext space. And they also extend Sum aggregation to Min aggregation.
Efficient and privacy-preserving data aggregation in mobile sensing
2012 20th IEEE International Conference on Network Protocols (ICNP)
2012 20th IEEE International Conference on Network Protocols (ICNP)
Computer Science