Enhancing the Security of Data Stored in the Cloud using customized Data Visualization Patterns

Abstract

Cloud Computing is getting popularized with the invention of latest technologies like Big Data, Artificial Intelligence, Data Science etc. The biggest challenge faced by researchers is efficient ways of accessing the data and acquiring the required results. The efficiency of the system will help the researchers to go one step further in the field of cloud computing. Alongside of storing the data in an optimal way, one biggest challenge faced by the researchers is security. How best security can be enhanced for this data in order to protect the end system from data thefts and illegal attacks. In this paper the proposed research concentrates on customized data visualization techniques that have been developed in order to store the data and also enhance the data security. These visualization patterns are dynamic in nature and can be further extended based on the need and level of the security required by the application. The proposed research in this paper will help researchers to implement the data visualization techniques with enhanced security in the real time data stored in the cloud from unauthorized access and various attacks like Malware etc. and these data patterns are dynamic in nature which will be selected based on the number of fragments need to be stored pertaining to particular cluster or region. The patterns will be selected based on two factors basically, one is the number of fragments and another important factor is how many nodes are available in the pattern. This proposed research will give an additional strength to the Cloud Computing Platforms like AWS and Google Cloud where the customers can feel that their data is in safe hands. Today when we are living in the data world, the need of this system is very much essential as it enhances the security of the data