Privacy-Preserving Truth Discovery with Truth Hiding

Abstract

This chapter considers the participation of data requesters in mobile crowdsensing (MCS) data truth discovery scenarios and discusses how to achieve privacy-preserving truth discovery with truth hiding. In most MCS scenarios, the data requesters submit the sensing task to the mobile crowdsensing platform for publication, and the mobile crowdsensing platform collects the sensory data of sensing users. In this case, the data requesters want to obtain the task’s truth, but the sensory data and the outputs of truth discovery may contain sensitive information and cause serious privacy concerns. Although existing privacy-preserving truth discovery schemes adopt several effective technologies to preserve the privacy of data and weights, most schemes do not consider the truth privacy. To this end, this chapter proposes a privacy-preserving truth discovery scheme SATE with truth hiding. Specifically, we build a mobile crowdsensing platform with two non-colluding servers, adopting the public-key cryptosystem supporting distributed decryption (PCDD) and using its homomorphic properties so users do not need to participate in the iterative process of privacy-preserving truth discovery. Security analysis proves that SATE effectively preserves the privacy of sensory data, weights, and truth. Performance evaluation and analysis prove that SATE has high computing and communication efficiency.