ITCN: An Intelligent Trust Collaboration Network System in IoT

• Published in: IEEE transactions on network science and engineering Vol. 9; no. 1; pp. 203 - 218
• Main Authors: Guo, Jialin, Liu, Anfeng, Ota, Kaoru, Dong, Mianxiong, Deng, Xiaoheng, Xiong, Neal N.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Artificial intelligence; Collaboration; Data collection; Internet of Thing; Internet of Things; Monitoring; Security; Trajectory optimization; Trust Collaboration Networks; Trustworthiness; Unmanned aerial vehicles
• ISSN: 2327-4697; 2334-329X
• DOI: 10.1109/TNSE.2021.3057881

Artificial Intelligence (AI) technology has been widely applied to Internet of Thing (IoT) and one of key application is intelligence data collection from billions of IoT devices. However, many AI based data collection approaches lack security considerations leading to availability restricted. In this paper, an Intelligent Trust Collaboration Network System (ITCN) is established to collect data through collaboration with mobile vehicles and Unmanned Aerial Vehicle (UAV) for IoT. The first, a deadline-aware data collection collaboration network framework is proposed by collaboration with mobile vehicles and UAV. The second, an active and verifiable trust evaluation approach is proposed to obtain the trust of the data participants, which ensures the security and privacy of the system. The last, a trust joint AI based UAV trajectory optimization algorithm is proposed to collect as much baseline data as possible, so more trust of data participants can be accurately evaluated and the data can be collected before deadline at low cost. The simulation results show that ITCN reduces the cost by 35.08% compared with using the UAV only, saves the collection time by 58.32% and increases the accuracy by 33.34% on average compared with the previous strategies only using vehicles.