Efficient privacy-preserving fault tolerance aggregation for people-centric sensing system

People-centric sensing (PCS) system is gaining popularity in the current technology world due to its ability to enhance the mobile device into a global mobile sensing device. But, PCS system is still suffering from security risks related to users privacy risks since the data being sensed by PCS are capable of allowing the attackers to gain privacy information related to the user. Hence, user privacy security is a main concern in the PCS system. In this paper, we propose to develop an efficient privacy-preserving fault tolerance aggregation technique for the PCS system. The proposed technique will consider registration of the involved mobile nodes and access point as an important initial step. Then, the data message being transmitted will be encrypted into reports and forwarded in a highly secure manner. Finally, the data will be decrypted and retrieved at the destination based on the homomorphic encryption and decryption mechanism. In this way, the privacy of the user is maintained secure and the process is made more tolerant toward fault in order to enhance efficient network operation. We evaluate the performance of the protocol according to the parameters like communication overhead, delay and delivery ratio.