软件导刊2025，Vol.24Issue(3)：70-77,8.DOI:10.11907/rjdk.241080
群智感知下基于信任的工人选择策略研究
A Trust Based Workers Selection Strategy Research for CrowdSensing
摘要
Abstract
In the CrowdSensing(CS)networks,the presence of malicious workers who engage in deceptive practices,such as false reporting or data fabrication,to gain additional rewards is an unavoidable concern,thereby affecting the service quality of the system.To address this is-sue,a Trust Based Workers Selection Scheme(BTWS)is proposed,which adopts a proactive trust evaluation approach.This scheme leverag-es trustworthy worker-reported data as reference samples for comparing the trustworthiness of other workers and dynamically evaluating their trust levels.The primary objective is to exclude malicious workers and selectively engage reliable workers for task execution to ensure data trustworthiness,consequently enhancing application service quality.Experimental results demonstrate that compared to the Cost Minimization Scheme Based on Passive Trust Evaluation(CMPT),the proposed scheme achieves a 1.9 times improvement in trust difference,accompanied by a 9%increase in the proportion of outstanding workers and a 63.8%cost reduction.Compared to the Quality Maximization scheme based on Trust UAV-Assisted(QMUT),the proposed scheme achieves an 8.7%increase in the ratio of outstanding workers and a 63%cost reduction with the same level of trust difference.In essence,the proposed scheme ensures data credibility and achieves application service quality opti-mization with low cost.关键词
群智感知/工人选择/信任评估Key words
CrowdSensing(CS)/workers selection/trust evaluation分类
信息技术与安全科学引用本文复制引用
鄢锦玲,陈木生,刘安丰..群智感知下基于信任的工人选择策略研究[J].软件导刊,2025,24(3):70-77,8.基金项目
江西省教育厅科学研究项目(GJJ200839) （GJJ200839）
江西理工大学博士启动基金项目(205200100402) （205200100402）
