Privacy-preserving incentive and rewarding scheme for crowd computing in social media

Abstract Internet-based social media helps one user to communicate with hundreds of or even thousands of other users. By making use of the advantages of social media, the third party can finish some special jobs more efficiently. Thus, it is important to encourage more users to make contribution to the jobs. Some necessary security problems must be solved in order to ravel out the users’ concerns. They include privacy-preservation, incentive and rewarding for crowd computing in social media. In the paper, we propose the novel concept of privacy-preserving incentive and rewarding (PPIR) for crowd computing in social media. We give the formal definition of PPIR. Then, we formalize its system model and security model. Finally, based on the bilinear pairings and group-oriented cryptography technique, we design a concrete PPIR scheme. The proposed PPIR scheme’s security is proved in the random model. From the communication cost and computation cost, we analyze its efficiency. Security analysis and efficiency analysis show that our concrete PPIR scheme is provably secure and efficient.