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Articles

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

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ABSTRACT

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.

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Mohammad Ubaidullah Bokhari

Mohammad Ubaidullah Bokhari is presently working as chairman in the Department of Computer Science, AMU, Aligarh, (India) and principal investigator (PI) of the ambitious project, NMEICT ERP Mission Project (Govt. of India). He has worked as an associate professor and director of studies in Australian Institute of Engineering & Technology, Victoria, Melbourne (Australia). Prof. Bokhari has a vast teaching experience of more than 25 years. Under his guidance, more than 100 students of PG level have completed projects/dissertations as well as more than 50 projects at UG level. Prof. Bokhari obtained his doctorate in the field of software reliability and master's degree in computer science from Aligarh Muslim University. His research interests include cryptography, cloud computing, smart grid, wireless sensor networks, and wireless Ad hoc networks.

E-mail: [email protected]

Qahtan Makki Shallal

Qahtan Makki Shallal is a PhD researcher at Aligarh Muslim University (AMU). He received his bachelor's degree in computer science from Basrah University in south of Iraq. He obtained his master's degree from Jamia Hamdard in New Delhi in 2008. He has worked as an assistant lecturer at Southern Technical University in Iraq for six years. His research interests include wireless networking and cloud computing security.

Corresponding author. E-mail: [email protected]

Yahya Kord Tamandani

Yahya Kord Tamandani received his BCA and MSc degrees from the Computer Science and Application Department, Punjab University, India in 2011 and 2013, respectively. He is an assistant professor at the Department of Computer Science at University of Sistan and Baluchestan, Zahedan, Iran. His research interests include networking modeling, cloud computing, and performance evaluation of wireless sensor networks for reliable, cost-effective and energy-efficient communication.

E-mail: [email protected]

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