An efficient privacy-preserving outsourced computation over public data

• Main Authors: LIU, Ximeng, QIN, Baodong, DENG, Robert H., Yingjiu LI
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2017
• Subjects: Function privacy; Data privacy; Encryption; Outsourced computation; Information Security
• Online Access: https://ink.library.smu.edu.sg/sis_research/3384; https://ink.library.smu.edu.sg/context/sis_research/article/4385/viewcontent/Efficient_privacy_preserving_outsourced_computation_2017.pdf
• Institution: Singapore Management University

In this paper, we propose a new efficient privacy preserving outsourced computation framework over public data, called EPOC. EPOC allows a user to outsource the computation of a function over multi-dimensional public data to the cloud while protecting the privacy of the function and its output. Spec...