Similar sub-image inquiring method and system for protecting privacy under cloud computing environment

Abstract

The invention provides a similar sub-image inquiring method and system for protecting privacy under a cloud computing environment. The similar sub-image inquiring method comprises the following steps: extracting characteristic sub-structures of an image shape data set; representing the quantity of each characteristic sub-structure contained in each image datum by using a characteristic vector; generating a parameter for encrypting and a random vector, and carrying out encryption calculation on the characteristic vector and the random vector of each image shape datum to generate a safety vector and establish a safety index; outsourcing the encrypted image shape data set and safety index into a cloud platform; extracting a characteristic sub-structure from an inquiry request image, and representing the quantity of each characteristic sub-structure contained in the inquiry request image by using a request characteristic vector; calculating a maximum allowable characteristic structure difference number, and generating a trap door and submitting the trap door to the cloud platform; after the cloud platform receives the trap door, calculating the difference between the request characteristic vector and the safety vector corresponding to the image shape data on the safety index to further inquire a similar sub-image. According to the similar sub-image inquiring method and system, the safety of privacy information referred in a similar sub-image inquiring process can be protected.

Description

technical field [0001] The invention relates to the field of information security, in particular to a privacy-protecting similar subgraph query method and system in a cloud computing environment. Background technique [0002] Graph data is widely used to represent complex structured data and is ubiquitous in the real world. As graph data grows in size, it becomes increasingly difficult to manage and process it locally. Cloud computing has attracted a large number of users by virtue of its powerful storage capacity, computing power, pay-as-you-go and elastic scaling. More and more individuals and enterprises hope to outsource their graph data to the cloud platform for convenient and flexible management, so as to effectively reduce local resource overhead and save costs. [0003] In order to improve the utilization rate of massive graph data in the cloud computing environment, it is necessary to query the data to obtain effective information. Since the graph data generally ...

AI Technical Summary

Problems solved by technology

[0008] Privacy during the query process: Since the similar subgraph query process is completed interactively between the client and the cloud platform, some intermediate information will be generated during the interaction process, which also involves some private information of the user. The cloud computing provider Or other users may use intermediate information to infer some content of query requests and indexes, which violates user privacy

On the other hand, during the query process, some relevant information of the index will be decrypted on the client side, some users may construct some request graph structures, analyze the index, obtain the real information of the index, and violate the privacy of the data owner

Images