Securing CNN Model and Biometric Template using Blockchain
This work addresses security vulnerabilities in biometric systems for applications like authentication, but it is incremental as it applies existing blockchain concepts to a specific domain.
The paper tackles securing biometric recognition systems by integrating blockchain to protect both the CNN model and biometric templates, demonstrating experimentally that the approach provides security across different biometric modalities.
Blockchain has emerged as a leading technology that ensures security in a distributed framework. Recently, it has been shown that blockchain can be used to convert traditional blocks of any deep learning models into secure systems. In this research, we model a trained biometric recognition system in an architecture which leverages the blockchain technology to provide fault tolerant access in a distributed environment. The advantage of the proposed approach is that tampering in one particular component alerts the whole system and helps in easy identification of `any' possible alteration. Experimentally, with different biometric modalities, we have shown that the proposed approach provides security to both deep learning model and the biometric template.