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Traffic congestion and accidents are increasing exponentially worldwide. More vehicles are sold every year which leads to more traffic fatalities and congestion. There have been several efforts worldwide for mobile Cyber Physical Systems (CPS) to address a range of problems including traffic congestion, accidents, unnecessary time spent in traffic jams, and overall infotainment by using onboard communicating and computing technologies. However, when we use peer-to-peer network-based communication for mobile CPS, malicious users/vehicles could mislead the mobile CPS by not reporting their true periodic status data to their neighbors on the road. In this paper, we study a data validation and correction approach for resiliency in mobile CPS that uses a diverse set of data for reducing false information. Numerical results obtained from Monte Carlo simulation are used to evaluate the proposed approach. Results show that the proposed approach minimizes the false data in the mobile CPS to enhance the resiliency.