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DeepRing: Protecting deep neural network with blockchain
A. Goel, A. Agarwal, , , N. Ratha
Published in IEEE Computer Society
2019
Volume: 2019-June
   
Pages: 2821 - 2828
Abstract
Several computer vision applications such as object detection and face recognition have started to completely rely on deep learning based architectures. These architectures, when paired with appropriate loss functions and optimizers, produce state-of-the-art results in a myriad of problems. On the other hand, with the advent of 'blockchain', the cybersecurity industry has developed a new sense of trust which was earlier missing from both the technical and commercial perspectives. Employment of cryptographic hash as well as symmetric/asymmetric encryption and decryption algorithms ensure security without any human intervention (i.e., centralized authority). In this research, we present the synergy between the best of both these worlds. We first propose a model which uses the learned parameters of a typical deep neural network and is secured from external adversaries by cryptography and blockchain technology. As the second contribution of the proposed research, a new parameter tampering attack is proposed to properly justify the role of blockchain in machine learning. © 2019 IEEE.
About the journal
JournalData powered by TypesetIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
PublisherData powered by TypesetIEEE Computer Society
ISSN21607508