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The Internet of Thing (IoT) has been a hot topic in both research communityand industry. It is anticipated that in future IoT, an enormous number ofsensors will collect the physical information every moment to enable thecontrol center making better decisions to improve the quality of service (QoS).However, the sensors maybe faulty and thus generate inaccurate data which wouldcompromise the decision making. To guarantee the QoS, the system should be ableto detect faulty sensors so as to eliminate the damages of inaccurate data.Various faulty sensor detection mechanisms have been developed in the contextof wireless sensor network (WSN). Some of them are only fit for WSN while theothers would bring a communication burden to control center. To detect thefaulty sensors for general IoT applications and save the communication resourceat the same time, an efficient faulty sensor detection scheme is proposed inthis paper. The proposed scheme takes advantage of fog computing to save thecomputation and communication resource of control center. To preserve theprivacy of sensor data, the Paillier Cryptosystem is adopted in the fogcomputing. The batch verification technique is applied to achieve efficientauthentication. The performance analyses are presented to demonstrate that theproposed detection scheme is able to conserve the communication resource ofcontrol center and achieve a high true positive ratio while maintaining anacceptable false positive ratio. The scheme could also withstand varioussecurity attacks and preserve data privacy.

An Efficient Fog-Assisted Unstable Sensor Detection Scheme with Privacy Preserved