Analysis of Encrypted Image Data with Deep Learning Models

Durmuş Özdemir, Dilek Çelik
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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.
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用深度学习模型分析加密图像数据
虽然各种加密算法都可以确保数据的安全性,但在通过深度学习确定加密数据的分析中,确定准确性、丢失值和性能状态是至关重要的。在本研究中,实际介绍了将深度学习方法应用于加密cifar10图像数据的分析步骤。使用VGG16、VGG19、ResNet50深度学习模型进行训练,尝试对数据进行估计。在此期间,尝试测量网络的性能,并以图形显示了这些计算的准确性和损失值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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