Prediction of availability and integrity of cloud data using soft computing technique

Soft Computing(2019)

Cited 14|Views18
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Abstract
In cloud computing, data storage is the most important task. In cloud storage, security and privacy are the major issues. To avoid such issues, we proposed a new protocol called availability and integrity verification protocol (AIVP) to predict the available space in cloud and verify the integrity of the stored data. For availability verification, this protocol is used to learn the size of the available data before it starts the storing process. Based on the learning, can find available storage space, cloud service provider will allow to store the data. This reduces the latency, communication cost and computational cost. For integrity verification, we separate the public data and private data and this leads to avoid the privacy issues. Private data will be integrated by the cloud service providers and the public data will be integrated by the third-party verifier. By using this verification process, it can avoid the security issues. In simulation results, proposed AIVP has outperformed the high-efficiency and throughput and this will cut the latency, computational cost and communication cost.
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Key words
Prediction, Availability, Integrity, AIVP, Cloud computing
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