Hvvu: A Hash Value Verification Joint Uavs Scheme for Trust Data Collection in Smart Cities

Abstract

With the rapid development of mobile sensing technology, Mobile Crowd Sensing (MCS) platforms are playing an increasingly important role in smart cities. Billions of sensor devices generate vast amounts of data, providing strong support for the efficient functioning of smart cities. However, collecting this data in a low-cost, secure, and efficient manner presents significant challenges. Malicious Mobile Data Collectors (MDCs) may transmit false data, which can affect the quality of services. Therefore, ensuring the high quality of data collection is crucial for the security and performance of smart city applications. A Hash Value Verification joint UAVs (HVVU) Scheme is proposed for trust assessment and selection between MDCs and Internet of Things devices. This scheme aims to select MDCs that are both low-cost and highly trustworthy, thereby enhancing data quality. Firstly, an active verifiable trust evaluation framework assisted by Unmanned Aerial Vehicles (UAVs) is proposed. This framework collects sensor node data as a baseline, which is then compared with the data submitted by MDCs to calculate and update their verification scores, effectively preventing collusion attacks among MDCs.Secondly, a hash-based interactive trust evaluation scheme is proposed, where MDCs interact with neighboring MDCs during data collection and calculate the hash value of the interaction packets. This process ensures the authenticity and reliability of the data while simultaneously updating interaction scores in realtime.Thirdly, a ranking mechanism based on the overall contribution degree and a winning strategy selection method based on the ranking are proposed. These methods take into account the comprehensive scores, bids, and collection rates of MDCs, incentivizing MDCs to maintain data quality while reducing costs.Lastly, a secondary optimization path scheme based on genetic algorithms is introduced. This scheme controls the UAV flight distance and increases the number of collected sensor nodes, thereby improving collection rates and reducing energy consumption.The experimental results indicate that, compared with the CTIS scheme, HVVU scheme increases the collection rate while controlling costs, achieving an approximate identification rate of 98% for malicious MDCs, with a false identification rate controlled at around 0.02%. This demonstrates the effectiveness and practicality of the proposed scheme.

Keywords: Mobile Crowd Sensing, UAV, Hash Value Verification, trust, comprehensive scores