A Secure Blockchain-based Reputation Scheme for Data Offloading in Edge Computing

Qian Yang, Jiankai Wang, Kai Chen, Hongjia Li, Haihua Gao, Zhen Xu

Abstract: As an extension of cloud computing, edge computing provides storage and computing services at the network edge. Due to resource limitation of edge nodes, collaborative data offloading is usually utilized to offload overloaded data in the current node to adjacent nodes to ensure quality of service. In this case, the reputation mechanism is a crucial tool to select a reliable one from adjacent nodes to provide data storage service. However, existing works usually adopt the single source-based evaluation method, which is vulnerable to malicious manipulation and lacks objectivity. Meanwhile, the reputation of malicious nodes can be rapidly recovered, leading to a reduction in evaluation accuracy. To address these issues, we propose a secure blockchain-based edge nodes reputation scheme, combined with subjective evaluation result and objective monitoring values to provide a credible reputation. Specifically, to increase the malicious attack cost and limit reputation recovery speed, we design an Amplifying-based Reputation Calculation (ARC) mechanism to amplify the impact of malicious behaviors on reputation. In addition, we propose a Dynamic Miner Selection (DMS) algorithm to resist bookkeeping right attack from malicious infrastructure providers. Detailed analysis proves the security of our scheme and experiment results testify the effectiveness and efficiency.

External IDs:dblp:conf/cscwd/YangWCLG024