security scrutiny and the performance appraisal show that the proposed scheme is protected and adequate. In order to authenticate the integrity of the data stored in the cloud, many remote data integrity auditing schemes have been proposed. To reduce the computation onus on the user side, a Third Party Auditor (TPA) is introduced to systematically verify the integrity of the cloud data on favor of user. Firstly proposed a notion of Provable Data Possession (PDP) to ensure the data possession on the entrusted cloud2. In this proposed scheme, homo morphic authenticators and random sampling strategies are used to achieve blockless verification and reduce I/O costs. In order to protect the data privacy, proposed a privacy-preserving remote data integrity auditing scheme with the employment of a random masking technique utilized a different random masking technique to further construct a remote data integrity auditing scheme supporting data privacy protection2. This scheme achieves better efficiency compared with the scheme. To reduce the computation burden of signature generation on the user side, designed a remote data integrity auditing scheme based on the in distinguish ability obfuscation technique introduced a Third Party Medium (TPM) to design a light-weight remote data integrity auditing scheme. In this scheme, the data stored in the cloud can be retrieved and the integrity of these data can be ensured. Based on pseudorandom function and BLS signature, Shacham and Waters proposed a private remote data integrity auditing scheme and a public remote data integrity auditing scheme. In order to protect the data privacy, proposed a privacy-preserving remote data integrity auditing scheme with the employment of a random masking technique utilized a different random masking technique to further construct a remote data integrity auditing scheme supporting data privacy protection3. This scheme achieves better efficiency compared with the scheme. In this scheme, the TPM helps user generate signatures on the condition that data privacy can be protected. clouds should be able to communicate with each other, creating inter-cloud computing scenario. This is also important to define a model named as Proof of Retrievability (PoR) and proposed a practical scheme. In this scheme, the data stored in the cloud can be retrieved and the integrity of Retrievability(PoR) of these data can be ensured. Based on pseudorandom function 3.

3. EXISTING SYSTEM
The personal sensitive information should not be exposed to remote data integrity auditing still able to be effectively performed. During the process of sanitization, the sanitizer does not need to interact with datas in bulk, and uploads these sanitized datas to the cloud at a fixed time. Firstly, after the data blocks corresponding to the patient’s sensitive information are the sensitive information contains two parts. One is the personal sensitive information, other is the organization’s sensitive information1. Sensitive information should be replaced with wildcards when the datas are uploaded to can be ensured corresponding to the sensitive information such as name by using wildcards, which protects the datas sanitizer. And all the sensitive information should not be exposed to the cloud and the shared users needs to generate and send the information’s of user to the sanitizer for storing them in the information system. However, these Secondly, the sanitizer can facilitate the information management. It can sanitize the the sanitized. It makes the Finally, the sanitizer uploads these sanitized and their corresponding signatures to the cloud. In this way, the EHRs can be shared and used by researchers, while the sensitive information of EHRs can be hidden. Meanwhile, the integrity of these data stored in the cloud privacy blinded, the contents of
these data blocks might become messy code. The sanitizer can unify the format by using wildcards to replace the contents of these data blocks. In addition, the sanitizer also can sanitize the data blocks the sanitizer is necessary because of the Thirdly, when the medical doctor needs the data, the sanitizer as the administrator sensitive information. Generally, these data blocks are replaced with wildcards. Furthermore, the sanitizer can transform these data blocks signatures into valid ones for the sensitive information. The multi-cloud distributed storage systems help to minimize the risks of a complete data loss. The probability of a complete data loss depends directly on the quality of hard disks. The distributed storage scheme based on threshold secret sharing of RRNS is used 2. Datas usually contain the sensitive information. To preserve the privacy of patient from the sanitizer, it blinds the sensitive information of each data before sending this to the sanitizer. Then the sever generates signatures for this blinded data and sends them to the sanitizer. The sanitizer stores these messages into in00formation system. When the user needs the data, he sends a request to the sanitizer. And then the sanitizer downloads the blinded data from the information system and sends it to the medical doctor. Finally, the data recovers the original data from this blinded data3. When this data needs to be uploaded and shared in the cloud for research purpose, in order to unify the format, the sanitizer needs to sanitize the data blocks corresponding to the information cloud for research purpose. The sanitizer can be viewed as the administrator of the information system. In addition, to protect the privacy of hospital, the sanitizer needs to sanitize the data blocks corresponding to the sensitive information. Generally, these data blocks are replaced with wildcards. Furthermore, the sanitizer can transform these data blocks’ signatures into valid ones for the sensitive information hiding4.

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