Method for securely calculating Nash equilibrium point in cloud computing environment

Abstract

The invention provides a method for securely calculating a Nash equilibrium point in a cloud computing environment, relates to the technical field of multimedia information security, and solves the problem of how to calculate the Nash equilibrium point more securely to obtain an optimal allocation strategy of data resources.The method starts from the problem of data resource allocation, When a user client and a data center carry out two-party game decision in order to obtain an optimal fusion strategy, the user client and the data center need to calculate a Nash equilibrium point by using a revenue matrix to obtain an optimal allocation strategy, a homomorphic encryption technology is applied to data resource allocation, and in combination with a game theory, based on a secure multiplication protocol and a secure division protocol in a cloud environment, excessive privacy does not need to be exposed to a cloud server in the calculation process, data in a ciphertext state is directly calculated, multi-party calculation is completed under the condition that private data is not leaked, a Nash equilibrium point optimal strategy is obtained, and the calculation precision can also be guaranteed based on the homomorphic encryption technology.

Description

technical field [0001] The present invention relates to the technical field of multimedia information security, and more specifically, to a method for securely calculating Nash equilibrium points in a cloud computing environment. Background technique [0002] Traditionally, when the computing center allocates data resources, the computing center collects the information of each user under the user client, and then analyzes the information of these users to obtain the Nash equilibrium point as the optimal result, and then performs data processing according to the optimal result. Resource allocation is simple and clear, but this method easily exposes the user's privacy, which is not conducive to ensuring the security and privacy of the entire data interaction process. [0003] In recent years, with the development and popularization of cloud computing, users are more and more inclined to store data on the cloud. Using the rich computing and storage resources provided by cloud ...

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Problems solved by technology

[0002] Traditionally, when the computing center allocates data resources, the computing center collects the information of each user under the user client, and then analyzes the information of these users to obtain the Nash equilibrium point as the optimal result, and then performs data processing according to the optimal result. Resource allocation is simple and clear, but this method is easy to expose the user's privacy, which is not conducive to ensuring the security and privacy of the entire data interaction process

[0003] In recent years, with the development and popularization of cloud computing, users are more and more inclined to store data on the cloud. Using the rich computing and storage resources provided by cloud servers can provide users with more efficient and professional data services. There is an inevitable risk of privacy data leaking to the cloud server. In order to solve the problem of untrustworthy cloud service providers in the cloud environment, on November 23, 2018, a Chinese patent with the publication number CN108881204A disclosed a privacy protection clustering In the data mining method, the user encrypts the data and publishes it to the cloud service provider. The cloud service provider uses the homomorphic encryption algorithm to achieve privacy protection, but the cloud service provider cannot directly access the user data to destroy the user privacy, which improves the data interactive calculation process. security, but this patent does not consider the allocation of data resources after mining. If data resource allocation is involved, when the user client and the data center make game decisions to obtain the best fusion strategy, both parties need to use the income matrix to calculate Nash equilibrium point to obtain the optimal allocation strategy, but the information of the profit matrix in the game decision-making process is also sensitive, therefore, how to calculate the Nash equilibrium point more safely in the cloud computing environment, so as to obtain the optimal allocation strategy of data resources, is Current technical challenges faced by those skilled in the art

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