PROJECT TITLE :
Privacy-Preserving Data Encryption Strategy for Big Data in Mobile Cloud Computing - 2017
Privacy has become a considerable issue when the applications of huge data are dramatically growing in cloud computing. The benefits of the implementation for these emerging technologies have improved or modified service models and improve application performances in various views. However, the remarkably growing volume of data sizes has also resulted in many challenges in practice. The execution time of the info encryption is one of the intense problems throughout the data processing and transmissions. Several current applications abandon information encryptions so as to reach an adoptive performance level companioning with privacy considerations. In this paper, we tend to concentrate on privacy and propose a completely unique information encryption approach, which is called Dynamic Knowledge Encryption Strategy (D2ES). Our proposed approach aims to selectively encrypt knowledge and use privacy classification ways underneath timing constraints. This approach is meant to maximise the privacy protection scope by employing a selective encryption strategy within the required execution time needs. The performance of D2ES has been evaluated in our experiments, that provides the proof of the privacy enhancement.
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