Sparse coding-based feature extraction for biometric remote authentication in Internet of Things

Abstract

In recent years, Internet of Things (IoT) has attracted lots of attention. However, the security related issues such as authentication remain a challenge. The heterogeneity of IoT in terms of devices and communication makes most existing authentication mechanisms inapplicable. So, there is a need for a two-factor authentication mechanism to obtain an end-to-end authentication between IoT devices/applications. In this paper, we propose a sparse coding based feature extraction for biometric remote user authentication. The proposed scheme makes use of sparse codes hash operations and overcomplete dictionary to store/retrieve the biometric data efficiently. The performance analysis proves that the proposed method is robust against noise and able to obtain the accuracy of 0.97.