Privacy-preserving edge-assisted image retrieval
and classification in IoT
Xuan LI;Jin LI;Siuming YIU;Chongzhi GAO;Jinbo XIONG
【期刊名称】《中国高等学校学术文摘·计算机科学》 【年(卷),期】2019(013)005
【摘要】Internet of Things (IoT) has drawn much attention in recent years.However,the image data captured by IoT terminal devices are closely related to users' personal information,which are sensitive and should be protected.Though traditional privacy-preserving outsourced computing solutions such as homomorphic cryptographic primitives can support privacy-preserving computing,they consume a significant amount of computation and storage resources.Thus,it becomes a heavy burden on IoT terminal devices with limited resources.In order to reduce the resource consumption of terminal device,we propose an edge-assisted privacy-preserving outsourced computing framework for image processing,including image retrieval and classification.The edge nodes cooperate with the terminal device to protect data and support privacy-preserving computing on the semitrusted cloud server.Under this framework,edge-assisted privacy-preserving image retrieval and classification schemes are proposed in this paper.The security analysis and performance evaluation show that the proposed schemes greatly reduce the computational,communication and storage burden of IoT
Privacy-preserving edge-assisted image retrieval and classification in IoT
