Keystroke dynamics refers to a user's habitual typing characteristics. These typing characteristics are believed to be unique among large populations. In this paper, we present a novel keystroke dynamic recognition system by using a fusion method. Firstly, we record the dwell time and the flight time as the feature data. We then calculate their mean and standard deviation values and stored. The test feature data will be transformed into the scores via Gaussian probability density function. On the other hand, we also propose a new technique, known as Direction Similarity Measure (DSM) to measure the differential of sign among each coupled characters in a phrase. Lastly, a weighted sum rule is applied by fusing the Gaussian scores and the DSM to enhance the final result. The best result of equal error rate 6.36% is obtained by using our home-made dataset.
With the escalating figures of tourists arriving to Malaysia, biometric technology plays a vital role to facilitate identity verification by using a self-service automated fingerprint scanner. Inbound tourists were made compulsory to use the biometric technology at Malaysia's immigration port of entry by providing their fingerprint data to be stored in the database located at the Ministry of Home Affairs. The database is linked to the police's existing Biometric Fingerprint Identification System database to grant immigration officers access to the movements of tourists with criminal records. However, the biggest foe of biometric technology is the issue of privacy. There is limited research engaging biometric technology in the tourism industry and this study becomes imperative and important. Based on the unified theory of acceptance and use of technology, this study was to investigate the constructs' effect on tourist satisfaction. Data was collected from 311 inbound tourists at Kuala Lumpur International Airport. They were tested against the research model using structural equation modelling approach. The results indicate that performance expectancy and physical privacy are not significant with regard to tourist satisfaction. We found that effort expectancy, facilitating conditions and informational privacy were all significant constructs that affect tourist satisfaction. These findings provide several important implications for researchers and designers.
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