Secure Fingerprint-based authentication and non-repudiation services for mobile learning systems

Most of the solutions proposed to the security and privacy issues in mobile learning systems are generally inherited from those developed in e-learning systems and network communication background. However, the implication of the mobile devices in m-learning can reveal more private data and requires far more challenges. In this paper, we exploit the richness of mobile devices in sensors to propose a fingerprint-based strategy that provides a secure authentication, communication and non-repudiation scheme for mobile learning using recent advances in cancelable biometrics. The proposed scheme covers all the learning system steps starting b y subscription, communication and assessments.