Abstract
A large number of Internet of Things (IoT) devices such as sensor nodes are deployed in various urban infrastructures to monitor surrounding information. However, it is still a challenging issue to collect data in a low‐cost, high‐quality, and reliable manner through IoT technique. Although the recruitment of mobile vehicles (MVs) to collect urban data has proved to be an effective method, most existing data collection systems lack a trust detection mechanism for malicious terminal nodes and malicious vehicles, which should lead to security vulnerabilities in practice. This paper proposes a novel data collection strategy based on a layered trust mechanism (DC‐LTM). The strategy recruits MVs as data collectors of the sensor nodes based on the data value in the city, evaluates the trustworthiness of the data reported by the nodes, and records the results to the cloud data center. Furthermore, in order to make the data collection system more efficient and trust mechanism more reliable, we introduce unmanned aerial vehicles (UAVs) dispatched by data centers to actively verify the core sensor node data and use the core sensor data as baseline data to evaluate the credibility of the vehicles and the trust value of the whole network sensor nodes. Different from the previous strategies, UAVs adopts the DC‐LTM method to obtain the node data while actively obtaining the trust value of MVs and nodes, which effectively improves the quality of data acquisition. Simulation results show that the mechanism effectively distinguishes malicious vehicles that provide false data in exchange for payment and reduces the total cost of system recruitment payments. At the same time, the proposed incentive mechanism encourages vehicle to complete the evaluation task and improves the accuracy of node trust evaluation. The recognition rates of false data attacks and flooding attacks as well as the recognition error rate of normal nodes are 100%, 98.9%, and 3.9%, respectively, which improves the quality of system data collection as a whole.
Highlights
With the development of Internet of Things (IoT) technology, new network systems such as the Internet of Vehicles, Smart Medical, and Smart City have developed rapidly [1,2,3]
∑j∈mobile vehicles (MVs) Rnumj + Wnumi ∙zj where Rnumjrepresents the number of MVsjcorrectly reported trust evaluation values of sensing nodes, and Wnumi represents the number of MVsj incorrectly reported trust evaluation values of sensing nodes
Based on the results reported by MVs and unmanned aerial vehicles (UAVs), the cloud data center implements the result summary and comparison mechanism to obtain the final trust evaluation of each sensor and MVs, and at the same time, it obtains the sensor collection information
Summary
With the development of IoT technology, new network systems such as the Internet of Vehicles, Smart Medical, and Smart City have developed rapidly [1,2,3]. This paper designs a layered trust mechanism, which recruits MVs to provide trust evaluation for terminal nodes, and uses UAVs to actively verify the credibility of data collectors and to inhibit malicious data collectors from participating in data collection. The UAV is dispatched at the right time to compare the data sensed by UAV with the data reported by vehicle and to judge the reliability of the vehicle, which changes the shortcomings of previous passive trust acquisition strategy (iii) The proposed recruitment mechanism encourages MVs to upload node information accurately. The mechanism considers the value of the collected sensor data and avoids the situation that no vehicle is willing to collect nodes far away from the data center It is a reasonable incentive mechanism (iv) Simulation results show that the proposed layer trust evaluation mechanism reduces the cost of recruitment payments and improves the accuracy of trust evaluation.
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