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Storage of data security has emerged as a basic necessity for both large- and small-scale industries. Cloud computing is internet-based computing technology in which people can work with their application with a high level of security in Internet of Things (IoT) enhanced devices. Cloud computing also provides privilege to store data that are collected from the devices in server side. Confidentiality and integrity of data play a major issue in cloud computing while preserving the IoT data. In this paper, the security of data is achieved by performing clustering and further applying cryptographic technique to the clustered data gathered from the devices that connected to the internet. Security of data can be improved by using a prominent cryptographic technique Attribute Based Encryption (ABE). Initially, the documents are clustered using the EM algorithm and clustered results are stored in various parts of the cloud. These documents are secured and can be accessed by the user who satisfies the attributes. In some cases, if the users’ attributes are not satisfied with the documents, it cannot be accessed by the corresponding user. Thus, the data from various devices are encrypted and maintained by the owner securely.

In embedded multicore shared memory systems, processing elements (PEs) are mutually untrusted since they carry different computing tasks independently. Therefore, the sharing of secret constants (SCs) between PEs, which is applied in the existing confidentiality protection schemes, will lead to the leakage of nonshared data. Besides, for integrity protection, tree construction checking over the whole counter space leads to the increase of both memory occupation and the average delay of verification. In this paper, we propose a ciphertext sharing confidentiality protection scheme based on certificateless proxy re-encryption and an integrity protection scheme based on a multigranularity scalable hash tree for secure data sharing between untrusted processing elements (SDSUP). With our schemes, the SC does not need to be shared and the scale of the checking tree is reduced, thus solving the leakage of nonshared data and reducing the high cost in integrity check. The results from the Rice Simulator for ILP Multiprocessors (RSIM) multicore simulator show that compared with the unprotected system, the performance degradation from applying the confidentiality protection scheme is 17.3% on average. Moreover, the performance degradation of the integrity protection scheme is 12.89%, which is superior to 35.36% for the bonsai Merkle tree (BMT), 29.49% for the multigrained hash tree (MGT) and 21.82% for the multigranularity incremental hash tree (MIT).