Set intersection method for realizing multi-party privacy

Abstract

The invention discloses a multi-party privacy set intersection method, and mainly solves the problems that: in the prior art, only hidden set size intersection under the environment of two participants is supported, and set intersection communication traffic under the environment of multiple participants is large. According to the scheme, a parameter generation mechanism generates required parameters; other participants represent respective input sets by using a Bloom filter, encrypt the input sets by using a joint public key, and send the encrypted input sets to a designated participant; the designated participant extracts ciphertexts by using the hash values of the set elements, combines the multiple ciphertexts into an aggregated ciphertext by using a cardinal number marking mode, and sends the aggregated ciphertext to other participants; and the designated participant and other participants jointly decrypt to obtain a joint plaintext, and recover a single plaintext from the joint plaintext so as to obtain an intersection. According to the method, the privacy set intersection calculation of the hidden set size under the environment of multiple participants can be supported, the communication traffic is reduced, and the method can be used for carrying out privacy protection on the input set elements and sizes of the participants in the set intersection.

Description

technical field [0001] The invention belongs to the field of security technology, and further relates to a multi-party privacy set intersection method, which can be used to protect the privacy of participants' input set elements and sizes in the set intersection. Background technique [0002] Privacy-preserving set intersection technology is a class of subproblems with wide application scenarios in the field of multi-party secure computing. In the context of the era of big data and artificial intelligence, in various applications, data is generated and utilized all the time, thereby bringing more convenient services to users. At the same time, a large amount of valuable private data is constantly being mined, so people's awareness of data protection that contains their own sensitive information continues to increase, which further creates a "trust gap", which leads to the phenomenon of "data islands" and makes data loss value. On the premise of effectively protecting the p...

AI Technical Summary

Problems solved by technology

However, this scheme uses an unpredictable function, which is limited to the representation of a single element in the set of participants. When there are multiple participants, it is difficult to achieve the function of seeking intersection at the same time. Therefore, if it is extended to multiple It is not feasible to safely complete the intersection function in the environment of the participating parties; at the same time, because this method uses a tool similar to the RSA accumulator, the amount of calculation in actual applications is too large, so it is not suitable for actual application scenarios

[0005] In their paper Secure and efficient multipartyprivate set intersection cardinality, Sumit Kumar Debnath et al. proposed a Bloom filter-based multi-party privacy set intersection protocol, which mainly uses the Bloom filter structure to input set elements to participants. Compared with most private set intersection protocols, it can save a lot of storage space, but after obtaining the ciphertext of the intersection, the designated participant needs to send the ciphertext of its set size to all other participants Decryption, so when all other participants receive the ciphertext, the set size of the specified participant can be inferred according to the number of ciphertexts, and it is impossible to hide the input set size of the participant, and the communication traffic is relatively large

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