| Title | A secure data collection strategy using mobile vehicles joint UAVs in smart city |
|---|---|
| ID_Doc | 38956 |
| Authors | Deng, QY; Huang, SB; Li, ZT; Guo, B; Xiang, LY; Ran, R |
| Title | A secure data collection strategy using mobile vehicles joint UAVs in smart city |
| Year | 2021 |
| Published | |
| Abstract | Recruiting mobile vehicles (MVs) has been proved as an effective and low-cost strategy to collect data from sensing devices (SDs) in the smart city. However, few works consider data security when using MVs as data mules. In our previous work, we have proposed a Consistent Trust Verification for MVs (CTV-MV), which builts trust through recommendation relationships, but this method was vulnerable to collusion attack, that is, multiple MVs provided consistent fake data to deceive the system. Therefore, a Cross Trust Verification for MVs joint UAVs (CTV-MVU) data collection strategy is proposed in this paper, where the Unmanned Aerial Vehicles (UAVs) are deployed to collect data from specific SDs which are used as baseline data to realize trust reasoning mechanism. Besides, the UAVs can also sense the SDs that are difficult to be collected by MVs due to their limitations of coverage, and thus improve the data collection ratio. Furthermore, a Trust Priority Recruitment (TPR) strategy for CTV-MVU is also proposed to prioritize the recruitment of high-trust MVs. Experiment results show that the proposed CTV-MVU strategy outperforms the CTV-MV one in terms of the excellent ratio, trust, data collection ratio, and robustness. |
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