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Top1. Introduction
In many of the developed and developing countries, it is necessary to transform the medical health records ((Piliouras et al., 2015; Castiglione, 2013) from the paper based work to an electronic health records (EHR) which are managed by many different administrative and complex levels. While getting into the concept of transforming the paper based works into an electronic digital medical record, there might be some possibilities of misusing medical and sensitive information of the patients. Hence it is important and necessary to protect the sensitive and confidential information of the digital electronic medical records
Even though there are many benefits of going to digital records of information, but these benefits may be overshadowed by the threat of hackers. In the past to gain access to healthcare record of patients, you need to break into doctor’s office and rummage through the vast number of patient files to find respective file. While going into digital data, all our personal data’s will get stored in the hospital database system. In order to break through the digital information, now a day’s many hackers are finding ways to gain access to the medical records though lot of security methodologies been implemented towards securing them.
So towards securing Digital health record, biometrics seems promising approach to secure them. Now in terms of biometrics, authentication systems based on keystroke dynamics are particularly interesting for usability reasons (Idrus et al., 2013). Many researchers proposed in the last decades some algorithms to increase the efficiency of this biometric modality. In another research work, the fingerprint verification is embedded in a smart card (Isa et al., 2010). The smart card plays a data storage for storing the cardholder's fingerprint data. The card holder is required to scan fingerprint on a sensor. The scanned fingerprint image is then sent to the card for matching. Lastly there has also been research carried out in securing the digital health record stored in cloud and also remotely monitoring the health of patient using Public Key Infrastructure and so forth.
In current scenario, there has been an increase in the false rejection ratio due to a slight difference in the positioning of the finger on the biometric scanner (Kaizhi and Aquin, 2011; Cheng et al., 2013; Bifari and Elrefaei, 2014; Choi et al., 2013; Ivanov and Baras, 2011). The small wounds and scratches on the fingers may also lead to the false rejection of the legitimate user due to the continuous joint measurement of nodal points on the biometric authentication. Even if we reduce the authentication factor level of the biometric authentication system, it may have possibilities which lead to the false acceptance ratio.
So looking into drawbacks of the existing biometric system pertaining to fingerprint, we have provided some better level of authentication factors on innovative methodology of “Frame Based Biometric Authentication” (Vignesh and Suresh, 2016) where the fingerprint image has been segmented in-order to provide an enhanced authentication level to reduce an increase in the false rejection ratio and false acceptance ratio. The simulation analysis of frame based biometric authentication is compared against pixel method using Matlab in our secured hospital management system.