A SECURE AND MANAGED CLOUD STORAGE SYSTEM USING ENCRYPTION WITH MACHINE LEARNING APPROACH

Cloud storage platform is a promising architecture provided by the Cloud Service. However, the use of these services raises many doubts and concerns about the security, confidentiality, reliability and integrity of users' data and information. Because the cloud is based on a per-user payment model, it will take longer to retrieve the required document, which raises the financial burden, and hence affects the satisfaction level of cloud users. This is the major point, where presented research comes to play. The proposed work takes advantage of multi-layered neural network architecture for secure cloud storage system along with the involvement of encryption and similarity approaches such as Cosine Similarity algorithm while encryption check engrosses AES and DSA approaches. Simulation analysis offers a secure cloud platform using cloudsim simulator. Experimentation was performed against 700 text documents to evaluate the proposed work in terms of precision, recall, f-score and accuracy with an average accuracy of 92.48%. Simulation results had demonstrated that the designed algorithm proved to offer data storage in a cloud computing environment with high-end security. In future, the authors aim to involve some deep learning approaches to improve the text mining capabilities using cloud storage without challenging data security.