Nowadays, location-based service (LBS) has become pervasive. Given its high utility value, LBS, however, presents serious privacy concerns for cautious users. In this paper, we investigate privacy preserving for location-based information survey application, which calculates the geographic distribution of user's information. The design objective is twofold: (i) calculate an information distribution for a pool of mobile users and (ii) protect the location and value privacy of individual user, in the presence of malicious servers and possible corrupted users. Our proposed solution leverages a mobile cloud computing paradigm, in which each mobile device is replicated with a system-level clone in cloud. The computing of distribution function is distributed among the set of cloud clones via a P2P protocol. We further enhance our basic scheme with the multiple aggregation mechanism, aiming to protect the correctness of the aggregate result from the active attacker. Compared to the approaches based on centralized server or aggregate proxy, our proposed scheme and its enhanced version are advantageous in avoiding single point of failure/attack, load balancing, and overhead reduction. Simulation results verify these advantages and the protection to the correctness of aggregate result and suggest that our proposed scheme is suitable for large-scale applications. Copyright © 2014 John Wiley & Sons, Ltd.