BD-VTE: A Novel Baseline Data Based Verifiable Trust Evaluation Scheme for Smart Network Systems

被引:113
作者
Huang, Shaobo [1 ]
Liu, Anfeng [1 ]
Zhang, Shaobo [2 ]
Wang, Tian [3 ]
Xiong, Neal N. [1 ]
机构
[1] Cent South Univ, Sch Informat Sci & Engineeing, Changsha 410083, Peoples R China
[2] Hunan Univ Sci & Technol, Comp Sci & Engn, Xiangtan 411201, Peoples R China
[3] Natl Huaqiao Univ, Sch Comp Sci & Technol, Tahlequah, OK 74464 USA
来源
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING | 2021年 / 8卷 / 03期
基金
中国国家自然科学基金;
关键词
Data collection; Smart cities; Security; Reliability; Internet of Things; Sensors; Smart network systems; data collection; security; baseline data based verifiable trust evaluation; mobile vehicles; unmanned aerial vehicles; WIRELESS SENSOR; UAVS; ATTACKS;
D O I
10.1109/TNSE.2020.3014455
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Billions of sensors and devices are connecting to the Internet of Thing (IoT) and generating massive data which are benefit for smart network systems. However, low-cost, secure, and efficient data collection from billions of IoT devices in smart city is a huge challenge. Recruiting mobile vehicles (MVs) has been proved to be an effective data collection scheme. However, the previous approaches rarely considered the security. In this paper, a novel Baseline Data based Verifiable Trust Evaluation (BD-VTE) scheme is proposed to guarantee security at a low cost. BD-VTE scheme includes Verifiable Trust Evaluation (VTE) mechanism, Effectiveness-based Incentive (EI) mechanism, and Secondary Path Planning (SPP) strategy, which are respectively used for reliable trust evaluation, reasonable reward, and efficient path adjustment. Among them, an active trust verification mechanism is innovatively proposed in the VTE mechanism, which evaluates the trust of MVs by sending UAVs to perceive IoT devices data as baseline data. This is a fundamental change to the previous passive and unverifiable trust mechanism. The simulation results show that BD-VTE scheme reduces the cost by at least 25.12% similar to 38.03%, improves the collection rate by 0.91% similar to 9.65% and increases the accuracy by 10.28% on average compared with the previous strategies.
引用
收藏
页码:2087 / 2105
页数:19
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