|Title||A Transparent and Continuous Biometric Authentication Framework for User-Friendly Secure Mobile Environments|
|Year of Publication||2013|
|Keywords||authentication, Biometric, fuzzy crypto, gait recognition, machine learning|
Personal mobile devices (PMDs) have become ubiquitous technology. Their, steadily increasing computational and storage capabilities have enabled them to oer an increasingly large set of services. Considering their significance, it’s necessary to ensure that they aren’t misused. Unfortunately, a less effective and inconvenient PIN based authentication system is used to protect them against their misuse. Therefore, we propose a continuous and transparent multi-modal biometric authentication system for PMDs. This authentication system is based on gait, 3D-face and voice recognition. It requires minimal to no interaction from users for identity verification to maintain a transparent confidence level of identity throughout its period of use. Further, one of the more stable biometric traits will be used for extracting fuzzy crypto keys to encrypt and decrypt sensitive information stored on the internal or external memory of the PMD.