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Private set intersection (PSI) is a secure multi-party computation technique that allows several parties,who each hold a set of private items,to compute the intersection of those private sets without revealing additional information.PSI has been widely used in the field of artificial intelligence security and data mining security.With the advent of the multi-source data sharing era,most PSI protocols mainly solve the problem of two-party privacy set intersection,which can not be directly extended to multi-party privacy intersection computing scenarios.This paper designs a multi-party privacy intersection protocol with the help of cloud servers,which can outsource a part of the computation and communication to untrusted cloud server without disclosing any privacy data.This paper makes the protocol more efficient by using the methods of oblivious pseudo-random functions,secret sharing and key-value pair packing.It proves that the PSI protocol can be secure in the semi-honest model and all participants and cloud servers can not obtain the additional data.Compared with the existing scheme,the proposed protocol has the merit of less restricted and more applicable in application scenarios.

At present, most of the traditional change detection methods from high-resolution remote sensing image are based on a feature information, the information of multi-feature information cannot be extracted, so it is difficult to detect the complete information. In order to solve this problem, a change detection algorithm of high-resolution remote sensing image based on multiview spectral embedding is proposed in the present paper. Firstly, change image is obtained using traditional difference change detection method, and multi-feature information is extracted. The feature vector information is fused by a MSE model and the complete change information can be obtained. The experimental results show that the detection accuracy of the proposed method is better than the accuracy of traditional methods, and its stability is outstanding.