Privacy protection big data processing method and system supporting flexible access control

Abstract

The invention belongs to the technical field of cloud computing data processing, and discloses a privacy protection big data division analysis processing method and system supporting flexible access control. The privacy protection big data division analysis processing method includes the steps that: a DP calls an encryption algorithm EncTK to encrypt molecules and denominators and then uploads theencrypted molecules and denominators to a cloud server; a DSP selects a random number to execute a preprocessing operation to hide the original data, calls a PDec1 decryption algorithm to partially decrypt and sends another obtained encrypted data packet to a CP; after receiving the data packet, the CP calls a PDec2 algorithm to decrypt and calculate to obtain an intermediate result, encrypts theintermediate result by using a public key generated by a data requester or an ABE algorithm and sends the intermediate result to the DSP; the DSP removes random disturbance added to the ciphertext byusing an addition homomorphic property to obtain a final ciphertext result; and a DR decrypts access data. According to the privacy protection big data division analysis processing method, division operation can be directly executed without operation conversion, so that the calculation efficiency is ensured; and, four different data processing schemes are designed to adapt to more application scenarios, and fine-grained access control of the user on a processing result is achieved.

Description

Technical field [0001] The invention belongs to the technical field of cloud computing data processing, and in particular relates to a privacy protection big data processing method and system supporting flexible access control. Background technique [0002] At present, the closest existing technology: cloud computing can use a large number of resources and powerful computing capabilities in the network to provide cloud users with a variety of services (for example, data storage and massive data analysis), while outsourcing computing is used as cloud computing One of the service modes of, which greatly facilitates users and devices with limited local resources. However, outsourcing personal data to cloud servers makes cloud users lose complete control over the data, and cloud servers, as an incompletely trusted entity, may threaten users' data privacy and security. Therefore, cloud users tend to encrypt private data before uploading to the cloud server for calculation processing ...

AI Technical Summary

Problems solved by technology

[0008] (1) Difficulty in division of encrypted data in the prior art: Outsourcing of encrypted data can prevent privacy data from leaking, but at the same time it also complicates data processing and analysis; existing homomorphic encryption algorithms used for outsourcing of private data have modulo operations Increased the difficulty of implementing privacy-preserving division operations

Although fully homomorphic encryption supports division operations on ciphertexts, it introduces high computational and communication overhead

In addition, the existing division operation schemes that implement safe division through operation conversion or bit decomposition lead to excessive interaction and calculation overhead between the two entities

[0009] (2) The problem of fine-grained access control of the result of the division operation in the prior art: flexible access control to the result of the ciphertext calculation can enhance data security and privacy

The previous scheme solved the seven basic operation problems of encrypted data and flexible access control, but it still cannot provide a method for flexible access control of the division ciphertext calculation result of large integers

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