计算机科学
重复数据消除
加密
拥挤感测
移动设备
计算机网络
密码学
信息隐私
移动计算
分布式计算
计算机安全
操作系统
作者
Yuanyuan Zhang,C.L.Philip Chen
出处
期刊:IEEE Transactions on Industrial Informatics
[Institute of Electrical and Electronics Engineers]
日期:2022-04-01
卷期号:18 (4): 2849-2857
被引量:13
标识
DOI:10.1109/tii.2021.3099210
摘要
Mobile crowdsensing provides the data collection and sharing for the 5G-enabled industrial Internet of Things. However, the redundant and duplicated heterogeneous sensing data bring unnecessary heavy storage and communication overhead. In this article, we propose a secure heterogeneous data deduplication scheme, which introduces the privacy-preserving cosine similarity computing to eliminate the replicate sensing data without privacy leakage in mobile crowdsensing. Specifically, we use the proxy re-encryption algorithm to realize secure and accurate task assignment via fog-assisted mobile crowdsensing. Based on lightweight two-party random masking and polynomial aggregation techniques, we achieve the privacy-preserving cosine similarity computing protocol. Finally, we conduct the privacy analysis, and experimental results on real-world datasets show that our approach is practical and effective.
科研通智能强力驱动
Strongly Powered by AbleSci AI