Teaba Wala  Aldeen Khairi, 
    Secure Mobile Learning System using Voice Authentication,
    Journal of Engineering and Applied Sciences,
    Volume 14,Issue 22,
    2019,
    Pages 8180-8186,
    ISSN 1816-949x,
    jeasci.2019.8180.8186,
    (https://makhillpublications.co/view-article.php?doi=jeasci.2019.8180.8186)
    Abstract: In the last decade, the demand for learning through mobile devices has been increased, however, the
security and authentication of these systems have less attention. This is because of researchers desirability
to be more famous by unauthenticated publishing of their articles. Therefore, this study presents a proposed
voice authentication for mobile learning (m-learning) system as a secure solution. In the proposed system, each
of the server and clients (learners) in the designed learning system is provided with voice features extraction
algorithm. HPSO algorithm is used for extraction the wavelet frequency domain features. These extracted
features are then matched with stored database in order to give the permission of learning system accessibility.
For (LL subband) FAR is 0.0, FRR is 0.01 and CVR is 99%. For (LL, LH, HL and HH) FAR is 0.0, FRR is 0.0 and
CVR is 100%. The voice recognition time is about 1.04 sec.
    Keywords: FAR;FRR;wavelet transform;HPSO;voice authentication;Mobile learning;CVR
INTRODUCTION