Cloud-based two-value vector distance computing method and device and cloud server

Abstract

The invention discloses a cloud-based two-value vector distance computing method and device and a cloud server. The method and device and the server can solve the problem that existing cloud-based two-value vector distance computing cannot protect the privacy of users. The method includes the steps that a predetermined public key (PK) encrypted through Paillier, a secret key (SK) encrypted through Paillier, a random seed s, an encrypted secret key K<0>, an encrypted secret key K<1>, the encryption result HE.E (0) and the encryption result HE.E (1) are obtained, wherein the public key (PK) encrypted through Paillier, the secret key (SK) encrypted through Paillier, the random seed s, the encrypted secret key K<0> and the encrypted secret key K<1> correspond to a user to which a two-value vector belongs, distance computing is about to be conducted on the two-value vector and a two-value vector of a current user, the encrypted secret key K<0> and the encrypted secret key K<1> are symmetrical, and the encryption result HE.E (0) and encryption result HE.E (1) conducts encryption on 0 and 1 through the PK respectively; all possible input of scrambling code circuits of all bits of is obtained from the cloud server; all the bits of are coded to determine input of the scrambling code circuits of the corresponding bits of , and the input of the scrambling code circuits of all the bits of is sent to the cloud server; the encryption result obtained by conducting encryption on the distance between and through the PK and sent by the cloud server is received; decoding is conducted on the encryption result through the SK, and the distance between and is determined.

Description

Technical field [0001] The invention relates to the fields of privacy protection and cloud computing, and in particular to a cloud-based binary vector distance calculation method, device and server. Background technique [0002] As the number of mobile device users continues to grow, more and more applications involving binary vector-based distance calculation based on mobile devices adopt the cloud computing framework, and provide users with a wealth of applications with the help of powerful computing centers. [0003] Although hosting computing in the cloud has brought great convenience to mobile users, untrusted clouds also pose a great threat to personal privacy in data (such as friend relations, location information, activity information, etc.). For example, some distance calculation methods based on Fourier transform binary vectors hide the sensitive information of the data while keeping the Euclidean distance between the data approximately. This method is very effective for...

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is that the existing cloud-based binary vector distance calculation cannot protect user privacy

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