An Accurate Bitcoin Price Prediction using logistic regression with LSTM Machine Learning model
Volume-3 | Issue-3
Design of Distribution Transformer Health Management System using IoT Sensors
Volume-3 | Issue-3
Energy Management System in the Vehicles using Three Level Neuro Fuzzy Logic
Volume-3 | Issue-3
Cloud Load Estimation with Deep Logarithmic Network for Workload and Time Series Optimization
Volume-3 | Issue-3
Design of a Food Recommendation System using ADNet algorithm on a Hybrid Data Mining Process
Volume-3 | Issue-4
Review on Data Securing Techniques for Internet of Medical Things
Volume-3 | Issue-3
Automatic Diagnosis of Alzheimer’s disease using Hybrid Model and CNN
Volume-3 | Issue-4
Population Based Meta Heuristics Algorithm for Performance Improvement of Feed Forward Neural Network
Volume-2 | Issue-1
Comparative Analysis of an Efficient Image Denoising Method for Wireless Multimedia Sensor Network Images in Transform Domain
Volume-3 | Issue-3
A Comprehensive Review on Power Efficient Fault Tolerance Models in High Performance Computation Systems
Volume-3 | Issue-3
An Integrated Approach for Crop Production Analysis from Geographic Information System Data using SqueezeNet
Volume-3 | Issue-4
An Accurate Bitcoin Price Prediction using logistic regression with LSTM Machine Learning model
Volume-3 | Issue-3
Design of Distribution Transformer Health Management System using IoT Sensors
Volume-3 | Issue-3
Design of a Food Recommendation System using ADNet algorithm on a Hybrid Data Mining Process
Volume-3 | Issue-4
Automatic Diagnosis of Alzheimer’s disease using Hybrid Model and CNN
Volume-3 | Issue-4
Effective Prediction of Online Reviews for Improvement of Customer Recommendation Services by Hybrid Classification Approach
Volume-3 | Issue-4
Acoustic Features Based Emotional Speech Signal Categorization by Advanced Linear Discriminator Analysis
Volume-3 | Issue-4
Analysis of Statistical Trends of Future Air Pollutants for Accurate Prediction
Volume-3 | Issue-4
Identification of Electricity Threat and Performance Analysis using LSTM and RUSBoost Methodology
Volume-3 | Issue-4
Review on Data Securing Techniques for Internet of Medical Things
Volume-3 | Issue-3
Volume - 2 | Issue - 1 | march 2020
Published
28 March, 2020
The technological advancements in the field of the information and communication technology led to the development of more promising cloud paradigm that allows online provision of services such as platform, software and infrastructure. The infrastructure services provided by the cloud allows the user data to be stored and accessed ubiquitously unlike the arrays that are available on the premises. However the security of the data that are being stored in the internet are still under research. This remains as major inhibitor for the adoption of cloud service in spite of its reliability, elasticity, high computational capabilities and the pay as you go possibilities. So the paper puts forth the construction of a secure storage as service in the cloud computing by utilizing the cryptography system based on Elgamal. The proposed method encrypts the data to be stored using the Elgamal that incorporates the hyper elliptic curve cryptography for twofold encryption and further utilizes the fuzzy logic to perform the integer selection that serves as the significant attribute in defining the cloud storage security. The point addition and the double based ECC is used for generating the keys for the hyper elliptic curve cryptography. The twofold security model put forth is validated using the MATLAB on the terms of efficiency observed on securing the data stored in cloud as well as the cost and the execution time endured by the proposed twofold security. The results shows that the protection offered by the twofold security is much better compared to the prevailing.
KeywordsCloud Paradigm Storage as Service Security Challenges Two Fold Security Elgamal HECC Fuzzy Logic
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