Intelligent human-centred mobile authentication system based on palmprints

Biometrics, as an intelligent and secure authentication method, has recently become increasingly popular. Modern society uses fingerprints, iris and face recognition on a daily basis, even on a large scale; for example, in biometric passports. However, there are still other biometric traits that may provide sufficiently high accuracy but have not been widely implemented so far, e.g. palmprints. In this article, we propose a novel human-centred method of palmprint-based user verification. The proposed method is dedicated to the mobile devices and provides the accuracy reaching 94.5%. Moreover, the method is time-computing efficient and gives the response in less than 0.2 s. All the experiments described in the article were performed using the benchmark PolyU database and three widely available mobile phones.

Privacy-Preserving Graph Operations for Mobile Authentication

Along with the fast development of wireless technologies, smart devices have become an integral part of our daily life. Authentication is one of the most common and effective methods for these smart devices to prevent unauthorized access. Moreover, smart devices tend to have limited computing power, and they may possess sensitive data. In this paper, we investigate performing graph operations in a privacy-preserving manner, which can be used for anonymous authentication for smart devices. We propose two protocols that allow two parties to jointly compute the intersection and union of their private graphs. Our protocols utilize homomorphic encryption to prevent information leakage during the process, and we provide security proofs of the protocols in the semihonest setting. At last, we implement and evaluate the efficiency of our protocols through experiments on real-world graph data.