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  • Küçük Resim
    Öğe
    Cloud computing integrated multi-factor authentication framework application in logistics information systems
    (Jital, 2017) Karabulut, Zeynel Erdi; Kasapbaşı, Mustafa Cem
    As new technology enables firms to perform many daily processes easier the need of authentication and authorization process is becoming an integral part of many businesses. Also mobile applications are very popular nowadays play an important role in our lives. Such demands are not only limited to Logistics Information Systems (LIS) but many field of information system as well. In this study multi-dimensional authentication which consist of online biometric face detection integrated as cloud computing software as a Service (SaaS), Near Field Communication (NFC) card authentication, location confirmation, and temporal data confirmation are gathered together to fulfill different scenarios of authentication needs of business. Microsoft Face API (Application Program Interface, SAAS (software as a service) has been used in face recognition module of developed mobile application. The face recognition module of the mobile application has been tested with Yale Face Database. Location, temporal data and NFC card information are collected and confirmed by the mobile application for authentication and authorization. These images were tested with our facial recognition module and confusion matrices were created. The accuracy of the system after the facial recognition test was found to be 100%. NFC card, location and temporal data authentication not only further increases security level but also fulfils many business authentication scenarios successfully. To the best of our knowledge there is no other authentication model other than implemented one that has a-4-factor confirmation including biometric face identification, NFC card authentication, location confirmation and temporal data confirmation.
  • Küçük Resim
    Öğe
    Mobil sistemler üzerinde, biyometrik, NFC ve konum bilgilerini kullanarak kişi tanıma
    (İstanbul Ticaret Üniversitesi Fen Bilimleri Enstitüsü, 2018) Karabulut, Zeynel Erdi; Kasapbaşı, Mustafa Cem
    Mobile applications are very popular nowadays and play an important role in daily life. In this study, cloud based mobile application for invitee control (person recognition) application is implemented. In the developed application, NFC, face recognition from biometric systems and using location information a person recognition system has been developed. The developed mobile application has 4 modules. These modules are Face recognition module, NFC module, Location module and Date and Time module. Microsoft face API (Application Programming Interface), (SAAS (software as a service)) has been used in face recognition module. In the NFC module, the loyalty card information of the user is read by the application and the person is recognized. In the location module, the user who performs the control is checked whether it is in the place where the activity is actually performed. In the Date and Time module, the effectiveness check is done at the right time and it is checked. The face recognition module of the mobile application has been tested with the Yale face database. There are 11 photographs of 15 different people in Yale face database. In this study the pictures used for testing are normal, normal and center light, normal left and right lights, normal and happy. These various images were tested with the face recognition module of the developed application and confusion matrices were calculated. The accuracy of the confusion matrix after the facial recognition module test is 100%. Other facial recognition algorithms implemented in other studies (such as Eigen Face, Fisher Face) have been compared with the face recognition module developed in this thesis. In applications developed with algorithms such as Eigen Face, Fisher Face, the accuracy rate ranges from 97% to 99% at maximum.