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Improved Scheme for Data Aggregation of Distributed Oracle for Intelligent Internet of Things.
Gao, Ruiyang; Xue, Yongtao; Wang, Wei; Lu, Yin; Gui, Guan; Xu, Shimin.
Afiliación
  • Gao R; Bell Honors School, Nanjing University of Posts and Telecommunications, Nanjing 210003, China.
  • Xue Y; School of Communication and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China.
  • Wang W; School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210003, China.
  • Lu Y; School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210003, China.
  • Gui G; School of Communication and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China.
  • Xu S; Zhongdian Zhiheng Information Technology Service Co., Ltd., Nanjing 210006, China.
Sensors (Basel) ; 24(17)2024 Aug 30.
Article en En | MEDLINE | ID: mdl-39275535
ABSTRACT
Oracle is a data supply mechanism that provides real-world data for blockchain. It serves as a bridge between blockchain and the IoT world, playing a crucial role in solving problems such as data sharing and device management in the IoT field. The main challenge at this stage is determining how to achieve data privacy protection in distributed Oracle machines to safeguard the value hidden in data on the blockchain. In this paper, we propose an improved scheme for distributed Oracle data aggregation based on Paillier encryption algorithm, which achieves end-to-end data privacy protection from devices to users. To address the issue of dishonest distributed Oracle machines running out of funds, we have designed an algorithm called PICA (Paillier-based InChain Aggregation). Based on the aggregation on the Chainlink chain and the Paillier encryption algorithm, random numbers are introduced to avoid the problem of dishonest Oracle machines running out of funds. We use the traffic coverage method to solve the problem of exposed request paths in distributed Oracle machines. Simulation and experimental results show that in small and medium-sized IoT application scenarios with 10,000 data nodes, each additional false request in a single request will result in a delay of about 2 s in data acquisition and can achieve a request response time of 20 s. The proposed method can achieve user data privacy protection.
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Texto completo: 1 Banco de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2024 Tipo del documento: Article País de afiliación: China