Paper Title : An enhanced security model on classifed data in cloud computing using cryptography and digital watermarking

ISSN : 2394-2231
Year of Publication : 2020

10.29126/23942231/IJCT-v7i4p1

Authors: Alpha Baba Garba, Souley Boukari

         



MLA Style: Alpha Baba Garba, Souley Boukari " An enhanced security model on classifed data in cloud computing using cryptography and digital watermarking " Volume 7 - Issue 4 July-August,2020 International Journal of Computer Techniques (IJCT) ,ISSN:2394-2231 , www.ijctjournal.org

APA Style: Alpha Baba Garba, Souley Boukari " An enhanced security model on classifed data in cloud computing using cryptography and digital watermarking " Volume 7 - Issue 4 July-August,2020 International Journal of Computer Techniques (IJCT) ,ISSN:2394-2231 , www.ijctjournal.org

Abstract
- Cloud Computing provides different services to users on request basis through the use of the internet. One major concern of the cloud is the security risks of the data; this has posed serious issues in trusting the security and integrity of data when exposed to the cloud. This work proposed an enhanced security model on classified data using different cryptographic techniques using Advanced Encryption Standard (AES), Rivest Shamir Adleman (RSA) and digital watermarking to improve the security of data stored in the cloud. The proposed system was implemented and simulated using Java programming toolkits with Netbeans IDE and cloudsim simulator. The work piloted a performance analysis of the existing system using K-NN and Improved Naïve Bayes algorithms and proposed system using improved Naïve Bayes and Modified K-NN algorithms. The results of the simulated system show that Modified K-NN algorithm performed significantly better than Improved Naïve Bayes algorithm in respect to data classification time of 665.60ms and 600.00ms and accuracy of the classified data having 97% and 98.26% respectively. Encryption time comparison of different cryptographic techniquesfor both the existing and proposed system depicts that Improved Naïve Bayes algorithm has RSA algorithm as 147462.40ms and AES algorithm with 2782.20ms. The Modified K-NN algorithm has 145692.80ms for RSA algorithm while AES algorithm has 2656.40ms. On the other hand the decryption time comparison of Improved Naïve Bayes algorithm has RSA algorithm as 36918.00ms with AES algorithm having 1070.40ms. The Modified K-NN algorithm has 36528.00ms for RSA algorithm and AES algorithm has 965.40ms. This work recommends that the proposed methodology and other machine learning algorithms be adopted by cloud service providers to improve on the classified data stored in cloud considering their security needs and sensitivity level. This will increase the confidence of their client and guaranteeing secured security in terms of data transfer and security of data store in cloud devoid of any enticing attack or mutilation on the data from malicious users.

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Keywords
Cloud computing, Data classification, Machine learning, Modified K-NN, Naïve Bayes, Cryptographic and Digital watermarking.