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    A MODEL FOR AN INTEGRATED AND SECURE PERSONAL IDENTIFICATION SYSTEM (ISPIS)

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    JOEL KIMELI CHERUS.pdf (3.620Mb)
    Date
    2014-10
    Author
    CHERUS, JOEL KIMELI
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    Abstract
    Personal Identification Systems are implemented to assist in identifying, authenticating and authorizing the right persons to the right entitlements. Criminals have however discovered ways of by-passing them in order to perpetrate identity fraud. As a result, the problem of identity fraud has become one of the fastest growing crimes in the world today, and a key facilitator of terrorism, money laundering and trafficking (of people, drugs, weapons and illicit material). In this study, an innovative model of a personal identification system that incorporates state of the art technologies is proposed to combat identity fraud. The system encompasses a secure integration of new and existing identification systems to provide for a real-time identity validation and verification. It can be accessed through ubiquitous devices such as smartphones and therefore can be used in a wide range of scenarios where identity checks are routinely done. Additionally, it is easy to use and free of typing-errors since users are presented with limited manual intervention. Its security architecture ensures confidentiality, integrity, availability and privacy of identity data. This design was informed by a review of literature on similar systems and the results of a survey that established the methods used by criminals to perpetrate identity fraud and the challenges facing Kenya’s primary registration and identification systems. A prototype of the system was constructed and evaluated using a set of identity fraud scenarios developed from the survey results. The outcome of the evaluation demonstrated that the model is able to withstand many types of identity fraud. It is therefore recommended that countries that experience incidences of identity-related crimes such as Kenya should consider implementing the model as an alternative tool for curbing identity fraud. Future work may focus on refining the model and scaling it to a global level.
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    http://10.1.130.140:8080/xmlui/handle/123456789/230
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