Developing the Security for Cloud Information Via Alexnet Learning Model versus the accuracy of Artificial Neural Network

Abstract

The main objective of the study is to protect cloud from different types of attacks by using AlexNet classifier compared accuracy with Artificial Neural Network and user’s data to be stored in the cloud safely by Advanced Encryption Standard. Materials and Methods: This research examines two groups AlexNet withArtificial Neural Network. Statistical study used 1300 training and 403 testing datasets from UNSW-NB15 dataset. ClinCalc programme utilised N=10, 0.05 is alpha value, 0.8% is G-Power, and 95% confidence interval.Result and Discussion: Novel Alexnet (91.081%) has an increased precision over ANN (90.075%) with the P value is 0.012(p<0.05) from the results of Independent samples t-test. There is a statistical significant difference between these two algorithms.Conclusion: This study concludes that the Novel AlexNet classifier algorithm seems fundamentally better than the ANN in terms of increasing the accuracy of secure cloud data and holding sensitive data with the dataset of UNSW-NB15.