Comparison between Different key sizes of AES on cloud computing

Authors: Nitin Rajput, M.Tech Scholar

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Abstract

Cloud security term refers to a broad field that has to do with the protection of data and cloud systems. Cloud security has historical roots that include ciphers, subterfuge, and other practices whose goals were to protect the confidentiality of written messages. In our era, cloud security is generally understood to involve domains that are involved in the security of IT systems as well as with the non-IT processes that are in interaction with IT systems. The objective of cloud security is to protect data as well as cloud systems from unauthorized access, use, disclosure, disruption, modification, or destruction. We will create public cloud using openshift cloud then apply Advanced Encryption Standard algorithm on file, which will store on cloud storage and also calculate encryption and decryption time. Keywords: Public Cloud, Cloud Security, AES, Open Shift.

Introduction

We define the concept of cloud computing and cloud services, and we introduce layers and types of cloud computing. We discuss the difference between cloud computing and cloud services. New technologies that enabled cloud computing are presented next. We also discuss cloud computing features, standards, and security issues. We introduce the key cloud computing platforms, their vendors, and their offerings. We discuss cloud computing Challenges and the future of cloud computing.

Conclusion

This paper presenting an algorithm for generating hybrid dimensional association rules mining as a generalization of inter-dimension and Intradimensional rule. The algorithm is based on the concept that the larger number of values/categories in a dimension/attribute means the lower degree of association among the items in the transaction. Moreover, to generalize inter-dimension association and intra-dimensional rules. we measured the following factors for creating our new idea, which are the time and the no of iteration, these factors, are affected by the approach for finding the frequent itemsets. Work has been done to develop an algorithm, which is an improvement over Apriori with using an approach of improved Apriori algorithm for a transactional database.