Amanpreet Singh, Dr. Manju Bala, Supreet Kaur


Cloud computing is a new class of network based computing that provides the customers with computing resources as a service over a network on their demand. Cloud computing offers scalability, availability and different services as important benefits. Privacy-preserving information in cloud permits an information owner to send its encrypted information to a cloud server. Hence, security and privacy of knowledge is that the major concern within the cloud computing. To overcome this, various security aspects has been analyzed and then a framework to mitigate security issues at the level authentication and storage level in cloud computing is proposed. Encryption is a security technique which is widely used for data security. Also, a data classification approach based on data confidentiality is proposed. and implemented. Confidentiality, Integrity and Availability are the three main concepts which are taken into consideration while proposing the work. So, basically the main aim of this research work is to enhance the authentication security, to classify the data using machine learning algorithm, To Increase the confidentiality and security of the cloud computing and at last comparing the proposed ensemble learning scheme with KNN on the basis of Classification Accuracy, Precision, Recall, Data Encryption time, Data Decryption time.


Cloud Computing; security issues, privacy preserving, Integrity, confidentiality, availability, graphical passwords, Data classification, Machine Learning

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