Blockchain-Enabled Lightweight Fine-Grained Searchable Knowledge Sharing for Intelligent IoT

作     者：Wang, Jing Lin, Xi Wu, Yulei Wu, Jun 

作者机构：Shanghai Jiao Tong Univ Collaborat Innovat Ctr Shanghai Ind Internet Sch Elect Informat & Elect Engn Shanghai Key Lab Integrated Adm Technol Informat S Shanghai 200240 Peoples R China Univ Exeter Fac Environm Sci & Econ Dept Comp Sci Exeter EX4 4RN England Waseda Univ Grad Sch Informat Prod & Syst Fukuoka 8080135 Japan 

出 版 物：《IEEE INTERNET OF THINGS JOURNAL》 (IEEE Internet Things J.)

年 卷 期：2023年第10卷第24期

页      面：21566-21579页

核心收录：

学科分类：0810[工学-信息与通信工程] 0808[工学-电气工程] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Natural Science Foundation of China 

主　　题：Data management and analytics secure communications security and privacy smart environment 

摘      要：With the rapid development of the Internet of Things (IoT), millions of IoT devices are constantly generating massive amounts of data. The development of artificial intelligence (AI) and edge computing makes it possible to conduct data analysis and knowledge mining efficiently among IoT edge devices. Knowledge, including intermediate results and training models obtained by large amounts of redundant data, is the core and foundation of edge intelligence. However, the sharing and utilization of knowledge still face a series of security and privacy issues, such as illegal knowledge access, knowledge tampering, and privacy leakage. To address these issues, in this article, we propose a blockchain-based knowledge storage and sharing architecture that enables secure knowledge management in intelligent IoT. We first design a permissioned blockchain-based decentralized and trusted knowledge storage scheme, which includes the on-chain encrypted knowledge storage and an improved Delegated Proof of Stake (DPoS) consensus protocol. Besides, we propose a lightweight attribute-based searchable encrypted knowledge-sharing mechanism, in which fine-grained and privacy-preserving knowledge collaboration is achieved through smart contracts and keyword search. Moreover, we reduce the computing overhead of edge devices through the design of partial outsourcing decryption. Finally, we analyze the security performance of our system as well as verify its practicality and ability to reject dishonest servers by simulation.