查看文章

Mobile sensing is becoming a popular paradigm to collect information from and outsource tasks to mobile users. These applications deal with lot of personal information, e.g., identity and location. Therefore, we need to pay a deeper attention to privacy and anonymity. However, the knowledge of the data source is desired to evaluate the trustworthiness of the sensing data. Anonymity and trust become two conflicting objectives in mobile sensing. In this paper, we propose ARTSense , a framework to solve the problem of “trust without identity” in mobile sensing. Our solution consists of a privacy-preserving provenance model, a data trust assessment scheme and an anonymous reputation management protocol. In contrast to other recent solutions, our scheme does not require a trusted third party and both positive and negative reputation updates can be enforced. In the trust assessment, we consider contextual factors …