| Title | Analysis of Encrypted Image Data with Deep Learning Models |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Özdemir, Durmuş, Çelik, Dilek |
| Conference Name | 2021 International Conference on Information Security and Cryptology (ISCTURKEY) |
| Keywords | Analytical models, Collaboration, composability, compositionality, cryptography, cryptology, Data security, Deep Learning, Information security, Knowledge discovery, Loss measurement, Metrics, Neural networks, policy governance, pubcrawl, resilience, Resiliency, Training |
| Abstract | While various encryption algorithms ensure data security, it is essential to determine the accuracy and loss values and performance status in the analyzes made to determine encrypted data by deep learning. In this research, the analysis steps made by applying deep learning methods to encrypted cifar10 picture data are presented practically. The data was tried to be estimated by training with VGG16, VGG19, ResNet50 deep learning models. During this period, the network's performance was tried to be measured, and the accuracy and loss values in these calculations were shown graphically. |
| DOI | 10.1109/ISCTURKEY53027.2021.9654326 |
| Citation Key | ozdemir_analysis_2021 |
Analysis of Encrypted Image Data with Deep Learning Models