Data monitoring method, device and equipment for cloud storage server
A technology of cloud storage server and data monitoring method, which is applied to the data monitoring of cloud storage server and the field of computer-readable storage media, can solve the problems of single update method of popularity value and low data security, so as to avoid data leakage, The effect of improving safety
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Embodiment 1
[0043] The following introduces Embodiment 1 of a data monitoring method for a cloud storage server provided by the present application, see figure 1 , embodiment one includes:
[0044] Step S101: Obtain user attribute information of data to be uploaded;
[0045]In this embodiment, user attribute information refers to reference information used to measure the degree of association between users. The user attribute information may include a variety of attribute information, specifically including LAN address, age, gender, personal preferences, and other information. In this implementation The example does not limit what kind of information is specifically selected. In this embodiment, according to the degree of association between the current user and the uploading user of the copy data in the cloud storage server, it is determined how to adjust the popularity value of the data. As a specific implementation, this embodiment divides the current users into two categories accord...
Embodiment 2
[0056] see figure 2 , embodiment two specifically includes:
[0057] Step S201: initializing system parameters;
[0058] This embodiment is implemented based on a cloud storage server, and the cloud storage server mainly interacts with the client of the current user. In the actual application scenario, the current user A 0 Generate ciphertext F and query tag H, where ciphertext F is the above data to be uploaded, and send an upload request including both to the cloud storage server, and then the cloud storage server judges whether the data to be uploaded is the first uploaded data through the query tag , and when it is determined that the data to be uploaded is not uploaded for the first time, the subsequent steps of this embodiment are executed.
[0059] The above initialization process includes:
[0060] (1) Set the popularity threshold T;
[0061] (2) Define data popularity: use count(F) to represent the comprehensive count of data F to be uploaded, when count(F)
Embodiment approach
[0102] As a specific implementation manner, the update module 304 includes:
[0103] A group user updating unit: used to determine that the uploading user of the data to be uploaded is a group user when the total number exceeds a quantity threshold, and update the popularity value of the data to be uploaded according to the growth curve function model;
[0104] An individual user updating unit: when the total quantity does not exceed the quantity threshold, determine that the uploading user of the data to be uploaded is an individual user, and add one to the popularity value of the data to be uploaded.
[0105] As a specific implementation manner, the similarity determination module 302 includes:
[0106] Type setting unit: used to set corresponding similarity calculation methods for user attribute information of different information types;
[0107] Similarity calculation unit: used to determine the target similarity calculation method according to the information type of th...
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