SCNN: A Secure Convolutional Neural Network using Blockchain

Inzamam Mashood Nasir, M. A. Khan, Ammar Armghan, M. Javed
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引用次数: 6

Abstract

Real-time applications like object detection, fire detection, face recognition and cancer detection are solely or partially relying on deep learning algorithms. Any tempering in these models can cause huge damages in many ways, therefore an utter need to secure these deep learning models is critically required. Blockchain technology has gained a wide popularity in tractability and security. In this article, the properties of blockchain are applied on the CNN models to produce secure CNN models. Each layer of a CNN model relates to a block, which contains the hash keys, public and private keys of their neighbors, while there exists a ledger block, which contains the detailed information about each layer of the model. The proposed SCNN model is tested using SVGG19 and SInceptionV3 models on publicly available datasets, which provides satisfactory results.
SCNN:使用区块链的安全卷积神经网络
物体检测、火灾检测、人脸识别和癌症检测等实时应用完全或部分依赖于深度学习算法。对这些模型的任何调整都可能在许多方面造成巨大的损害,因此迫切需要确保这些深度学习模型的安全。区块链技术在可追溯性和安全性方面获得了广泛的普及。在本文中,将区块链的属性应用到CNN模型上,生成安全的CNN模型。CNN模型的每一层都与一个块相关,其中包含相邻的哈希键、公钥和私钥,同时存在一个分类账块,其中包含模型每一层的详细信息。利用SVGG19和SInceptionV3模型在公开数据集上对所提出的SCNN模型进行了测试,结果令人满意。
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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