Method for encrypting summary ciphertext by using public key in block chain application system

Abstract

The invention relates to a method for encrypting a summary ciphertext by using a public key in a block chain application system. The method comprises the steps that data collection and summarization processes of an application system need to be publicly verifiable. The system is established on a block chain; the application system has high-cardinal-number class data, and a summary data structure is used for representing the data; a user contributes data to the application system in a private mode, a summary is encrypted through the public key, and summary ciphertext validity proof based on zero-knowledge proof is attached to the summary; a summing node inputs a proof to an intelligent verification contract, and pays verification operation and storage cost; and the summing node sums all the effective summary ciphertexts and then decrypts the effective summary ciphertexts, and publishes a summing summary result on the block chain. Transparent property can be added to the application system, and data collection and summarization processes are open and verifiable; the summary data structure of the sub-linear storage space represents the data, so that the storage and communication overhead is reduced; the effectiveness of the summary ciphertext can be ensured, and the data pollution attack of a malicious user to the system is prevented; the method can be widely applied to a transparent system which needs to express high-cardinal-number class data in a summary mode.

Description

technical field [0001] The invention belongs to the field of cryptography, and specifically relates to a zero-knowledge proof-based method for encrypting summary ciphertext with a public key in a block chain application system. Background technique [0002] In the application system, it is often necessary to summarize and count a large amount of data, and then publish the statistical results for data users to use. For example, the statistics of user video viewing data in the video recommendation system, the statistics of user traffic data in the network monitoring system, etc. These data are classified data with high cardinality. If one-hot encoding (One-HotEncoding) whose size has a linear relationship with the cardinality is used to represent the data, storage and communication overhead will be increased. In addition, data users are concerned about the correctness of statistics and require that the data collection and aggregation process be open and verifiable. [0003] ...

AI Technical Summary

Problems solved by technology

[0005] However, if the user constructs an invalid profile (no data can be mapped to this profile) and uploads it encrypted, the system will cause data pollution when summarizing the ciphertext of this profile

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