Privacy protection task recommendation method for high-dimensional data in spatial crowdsourcing environment

• Main Authors: XIONG LIZHI, FU ZHANGJIE, YUAN CHENGSHENG, SONG FUYUAN, ZHANG XIANG, GAO LILI, JIANG QIN
• Format: Patent
• Language: Chinese; English
• Published: 03.11.2023
• Subjects: CALCULATING; COMPUTING; COUNTING; ELECTRIC DIGITAL DATA PROCESSING; PHYSICS

The invention discloses a privacy protection task recommendation method for high-dimensional data in a spatial crowdsourcing environment, and belongs to the field of task recommendation. The recommendation method comprises the steps that a trusted mechanism generates a master key, and generates a key of a worker, a key of a data requester and a re-encryption key of a cloud server based on the master key; constructing a numerical value filtering tree by a worker, and encrypting the numerical value filtering tree by using a secret key of the worker to obtain an encrypted numerical value filtering tree; the cloud server re-encrypts the encrypted numerical value filtering tree by using the re-encryption key; the data requester encrypts the encoded query range by using the key to obtain a numerical intersection test trap door and a range intersection test trap door; the cloud server performs ciphertext conversion on the numerical intersection test trap door and the range intersection test trap door by using the re