15th IEEE International Conference on Machine Learning and Applications (ICMLA), California, United States Of America, 18 - 20 December 2016, pp.492-497
Biometric systems may be used to create a remote access model on devices, ensure personal data protection, personalize and facilitate the access security. Biometric systems are generally used to increase the security level in addition to the previous authentication methods and they seen as a good solution. Biometry occupies an important place between the areas of daily life of the machine learning. In this study; the techniques, methods, technologies used in biometric systems are researched, machine learning techniques used biometric aplications are investigated for the security perspective, the advantages and disadvantages that these tecniques provide are given. The studies in the literature between 2010-2016 years, used algorithms, technologies, metrics, usage areas, the machine learning techniques used for different biometric systems such as face, palm prints, iris, voice, fingerprint recognition are researched and the studies made are evaluated. The level of security provided by the use of biometric systems by developed using machine learning and disadvantages that arise in the use of these systems are stated in detail in the study. Also, impact on people of biometric methods in terms of ease of use, security and usages areas are examined.