Research On Resource Access Control In Cloud Network Environment

In the access control mechanism,the problem of coarse-grained and flexible multi-level access of users and files and the hierarchical authorization of newly added files(here we assume text)are studied.We propose a multi-level access control scheme based on trapdoor(MACST).It improves fine-grainedness and flexibility in multi-level control.In addition,we propose an automatic text grading scheme based on keyword similarity,aiming at automatically grading newly added texts to propose a hierarchical access control scheme for big data texts.Below we introduce these two programs.In some cases,we need hierarchical access control.Advanced users can access files of the same level or lower density;lower level users cannot access files of high density.We propose a multi-level access control scheme based on trapdoor(MACST).It improves fine-grainedness and flexibility in multi-level control.The solution consists of a combination of CP-ABE and trapdoors.The access control structure is constructed from a large access tree.Each layer of the tree is a level file,corresponding to a level of users,each level is associated by trapdoors and corresponding attributes,the higher the level.Users who meet the same level can access the same level of files.We use some algorithms to enable lower-level users(high-level users)to access upper-level files(low-level files).In contrast,upper-level users(low-level users)cannot access lower-level files(high-level files).When a high-level user accesses a low-level file,it only needs to use its own secret key to decrypt it,without having multiple keys.When the ciphertext level needs to be increased or deleted,directly join the trapdoor and the same attribute,or delete the trapdoor and corresponding attributes.When deleting a user,we need to change the parameters of the trapdoor.This is very simple,no need to re-encrypt the ciphertext.This has the advantages of fine-grained access of CP-ABE and the simple and flexible advantages of trapping the door.The text file authorization level uploaded to the cloud server is generally done by the administrator.There are some shortcomings in doing this.The first one is more cumbersome for the administrator.Secondly,because the administrator does not have a special understanding of the text file or the user,it is easy to grade incorrectly,which leads to the user accessing too many text files or text files with too few accesses.In some application environments,such as the protection of privacy rights,the protection of text data,the level is calibrated by specific keywords.We extract these keywords and put them into the dictionary.The keywords are arranged in the dictionary in a specific order by the importance of the keywords.First we classify some texts,and we assume that these ratings are correct.We use the IK tokenizer to segment new words and old text into lexicons to form a specific vector.Using the KNN principle,the k texts closest to the new text are calculated in the old text,and then the cosine of the vector of the k text and the new text is calculated by the cosine similarity principle.The text in which the similarity of the K text is greater than a certain threshold is the text we ultimately need.From the final text obtained,according to the majority voting method,most of the levels are selected as the level of the new text to perform multi-level access control.