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Fusion: Practice and Applications
Volume 3 , Issue 2, PP: 83-99 , 2021 | Cite this article as | XML | Html |PDF


Software Defined Network Function Virtualization Framework for Securing Cloud with Data Fusion and Machine Learning Techniques

Authors Names :   Rajit Nair   1 *     Miguel Botto-Tobar   2     Premnarayan Arya   3  

1  Affiliation :  VIT Bhopal University, Bhopal, India

    Email :  rajit.nair@vitbhopal.ac.in

2  Affiliation :  Research Group in Artificial Intelligence and Information Technology, University of Guayaquil, Ecuador

    Email :  miguel.bottot@ug.edu.ec

3  Affiliation :  Department of Computer science and engineering,G.H. Raisoni Institute of Engineering and Business Management, Jalgaon, Maharashtra, India

    Email :  premnarayan.arya@raisoni.net

Doi   :   https://doi.org/10.54216/FPA.030204

Received: February 17, 2021 Accepted: May 25, 2021

Abstract :

Computing in the cloud is one of the platforms that may be used to provide distributed computing resources. Supplying and managing cloud resources most effectively is referred to as resource management. A recent development in technology known as fog computing is an example of an expanded and dispersed infrastructure. This architecture maintains application processes between end devices and the network edge to provide more dependable and efficient services. These services include remote data storage, allowing customers to access their data from a distant location. Providing remote storage service is an advantageous function offered by cloud suppliers. On the other hand, the data stored in the cloud is geographically dispersed and kept in various data centers, significantly increasing the risk to users' privacy and security. One of the problems that might arise with privacy is when many data centers store the same information. Many cloud service providers check their customers' data using a Third-Party Auditor (TPA) to address concerns about client privacy and data integrity. Currently, most trusted TPAs only have one validator, making it impossible to expand the data integrity across several data centers. The various verifiers used by TPAs have been reduced in number in response to Man in the Cloud (MiTC) attacks. As a result, they cannot check and authenticate the integrity of data stored in several data centers. A unique Peer to Peer (P2P) authentication protocol with Certificate Authority (CA) and Data Storage Protocol is presented as a solution to the problem that has been outlined above to check for and go around any issues that may arise (DSP). The efficiency of the proposed protocol is demonstrated by the incorporation of TPAs and Certificate Authorities. The proposed protocol has been tested with a single user and a single storage server, as well as multiple storage servers in ownCloud with one backup server, two storage servers, three clients, and two TPAs. The NoSQL server in an organization's cloud is set up to save data to storage servers in the appropriate format. The Amanda backup server is used to back up the mirror copy of the stored data on the storage servers. Automated Validation of Internet Security Protocols with Data Fusion and Applications, or AVISPA for short, is a technology that may be used to verify data stored in the cloud. The findings make it abundantly evident that the suggested protocol is strong enough to guarantee the authenticity of data kept in several data centers.

Keywords :

Third Party Auditor (TPA); multiple data centers.; attacks; Certificate Authority and TPA; Peer to Peer; data fusion.

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Cite this Article as :
Rajit Nair , Miguel Botto-Tobar , Premnarayan Arya, Software Defined Network Function Virtualization Framework for Securing Cloud with Data Fusion and Machine Learning Techniques, Fusion: Practice and Applications, Vol. 3 , No. 2 , (2021) : 83-99 (Doi   :  https://doi.org/10.54216/FPA.030204)