KNN file classification for securing cloud infrastructure
M. Subrahmanya Sarma, Y. Srinivas, M Abhiram, M. Sahithi Prasanthi, M. Ramya · 2017
Security aspects of information in cloud storage is one of the barriers of Degree of Trust and cloud penetration. The ask from cloud user community is to ensure security and performance via quality of services (QoS). Several models were proposed [2] [3] [7] to address security concerns. Some of the concerns that still remains is to eliminate manual intervention and bring in automation for the information classification. An innovative QoS model has been developed which aids the secure wallet files to be effectively structured and classified. An extension has been suggested to the security methodology suggested in CCEM2016 [7], which uses automation to enhance the efficacy of secure cloud. The Classifier-QoS addresses few security concerns pertaining to cloud user community along with improvement in end user experience. Classifier-QoS has been developed using designs based on Machine Learning (KNN-Learning). In this paper, we also touched upon the various barriers of the degree of trust and models proposed to address the barriers. Improvement to information classification, is extended to the proposed method in [7], which ensure security and performance. Amazon EC2 cloud has been used to evaluate the proposed model and results are captured as part of this paper.