Reducing the Required Time and Power for Data Encryption and Decryption Using K-NN Machine Learning.

Cloud computing allows the users to store their data in its storage and use them whenever they need. While the data of user is traveling outside its physical infrastructure through Internet, it needs to use a very strong encryption to protect them against the hackers who attempt to steal or alter the data. Thus, the data security in transmission is so important. Most of the users send the data to cloud, but all the data do not have a high sensitivity. In this paper, K nearest neighbors algorithm is used to decide whether the data is normal sensitive or high sensitive, and then according to the level of sensitivity we proposed a framework to do data encryption. In order to ensure user authentication, we used one time password to authenticate the user, and for the data which belong to normal sensitivity level we have applied AES (advanced encryption standard)-192 algorithm. Finally, for the data which belong to high sensitivity level, AES-256 algorithm has been applied, and RSA (Rivest-Shamir-Adleman) algorithm is used to encrypt the key of AES 256, then we use hash-based massage authentication code to be attached in the end of message to ensure integrity and authenticity of message. [ABSTRACT FROM AUTHOR]