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Data storage lock algorithm with cryptographic techniques Anitha K L; T.R. Gopalakrishnan Nair
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 5: October 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (466.134 KB) | DOI: 10.11591/ijece.v9i5.pp3843-3849

Abstract

The cloud computing had its impact far and wide, and Enterprise solutions are getting migrated to different types of clouds. The services are delivered from the data centers which are located all over the world. As the data is roaming with less control in any data centers, data security issues in cloud are very challenging. Therefore we need multi-level authentication, data integrity, privacy and above all encryption to safeguard our data which is stored on to the cloud. The data and applications cannot be relocated to a virtual server without much degree of security concern as there can be much confidential data or mission-critical applications. In this paper, we propose Data Storage Lock Algorithm (DSLA) to store confidential data thereby provides secure data storage in cloud computing based on cryptographic standards.
Online cloud performance testing in social networks at peak demand scenarios Anitha K L; T.R. Gopalakrishnan Nair
Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 1: January 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v17.i1.pp372-378

Abstract

Cloud computing assures to deliver reliable services through advanced data centers built on virtualized compute and storage technologies. Users demanding more cloud services will be able to access applications and data from a Cloud anywhere in the world in a pay-as-you-go model. In this paper, we focus on cloud-based performance testing for the applications. We use Load Storm testing tool to configure and test plans to measure the performance of web applications in online social networks. The experimental observations designed to assess the performance fluctuations of social networks on maximum consumer demand days have given specific data pointers which could be utilized for further studies of web service enhancements.