Biometric security technology

More and more these days, airport security is having to adapt to a greater number of passengers while keeping within finer margins of precision when it comes to clearing passengers for security clearance. Therefore, analyzing potential upgrades in the security process and adopting them in a way that does not impact passenger experience has become a key activity for airport managers. One viable technological solution that is not only effective but also efficient is biometric security. This technology allows for passengers to safely clear security based on their unique biometric features. Despite its promise, airports and passengers alike are slow to adopt its use. Additionally, there were few studies that revealed insights into passengers’ intentions toward repeat use of biometric security. Hence, in our novel attempts to uncover the underlying reasons, we implemented a study on passengers’ initial and repeat usage intention based on perceived benefits and risks of biometric security technology. Based on 327 survey responses, we employed the use of SEM to extract first- and second-order constructs before evaluating our hypotheses on a finally accepted model. To be aligned with the novel attempt of this research, the results showed that both the perceived benefits and risks have a significant impact on passenger’s initial and repeat use intention of biometric security. Therefore, for all practitioners engaged in sustainable airport management, strong consideration from this research should help in creating value for passengers while mitigating the risks of adopting biometric security within airport security settings.

Download Full-text

Biometric Security Technology

Encyclopedia of Artificial Intelligence ◽

10.4018/978-1-59904-849-9.ch041 ◽

2011 ◽

pp. 262-269 ◽

Cited By ~ 4

Author(s):

Marcos Faundez-Zanuy

Keyword(s):

Statistical Analysis ◽

Biological Characteristics ◽

Nice Property ◽

Biometric Recognition ◽

Short Term ◽

Security Technology ◽

Identity Verification ◽

Security Applications ◽

Biometric Security ◽

Do So

The word biometrics comes from the Greek words “bios” (life) and “metrikos” (measure). Strictly speaking, it refers to a science involving the statistical analysis of biological characteristics. Thus, we should refer to biometric recognition of people, as those security applications that analyze human characteristics for identity verification or identification. However, we will use the short term “biometrics” to refer to “biometric recognition of people”. Biometric recognition offers a promising approach for security applications, with some advantages over the classical methods, which depend on something you have (key, card, etc.), or something you know (password, PIN, etc.). A nice property of biometric traits is that they are based on something you are or something you do, so you do not need to remember anything neither to hold any token.

Download Full-text

A practical guide to biometric security technology

IT Professional ◽

10.1109/6294.899930 ◽

2001 ◽

Vol 3 (1) ◽

pp. 27-32 ◽

Cited By ~ 119

Author(s):

S. Liu ◽

M. Silverman

Keyword(s):

Security Technology ◽

Biometric Security ◽

Practical Guide

Download Full-text

Current Trend of The Standardization for Security Technology

IEEJ Transactions on Electronics Information and Systems ◽

10.1541/ieejeiss1987.107.9_798 ◽

1987 ◽

Vol 107 (9) ◽

pp. 798-803

Author(s):

Tetsuji Kobayashi

Keyword(s):

Current Trend ◽

Security Technology

Download Full-text

Evaluation of the effectiveness of different image skeletonization methods in biometric security systems

International Journal of Sensors Wireless Communications and Control ◽

10.2174/2210327910666201210151809 ◽

2020 ◽

Vol 10 ◽

Author(s):

Mariya Nazarkevych ◽

Serhii Dmytruk ◽

Volodymyr Hrytsyk ◽

Olha Vozna ◽

Anzhela Kuza ◽

...

Keyword(s):

Experimental Studies ◽

Fingerprint Recognition ◽

Good Time ◽

Gabor Filtering ◽

Security Systems ◽

Thinning Algorithm ◽

Biometric Security ◽

Recognition Quality ◽

Control And Management ◽

The Internet Of Things

Background: Systems of the Internet of Things are actively implementing biometric systems. For fast and high-quality recognition in sensory biometric control and management systems, skeletonization methods are used at the stage of fingerprint recognition. The analysis of the known skeletonization methods of Zhang-Suen, Hilditch, Ateb-Gabor with the wave skeletonization method has been carried out and it shows a good time and qualitative recognition results. Methods: The methods of Zhang-Suen, Hildich and thinning algorithm based on Ateb-Gabor filtration, which form the skeletons of biometric fingerprint images, are considered. The proposed thinning algorithm based on Ateb-Gabor filtration showed better efficiency because it is based on the best type of filtering, which is both a combination of the classic Gabor function and the harmonic Ateb function. The combination of this type of filtration makes it possible to more accurately form the surroundings where the skeleton is formed. Results: Along with the known ones, a new Ateb-Gabor filtering algorithm with the wave skeletonization method has been developed, the recognition results of which have better quality, which allows to increase the recognition quality from 3 to 10%. Conclusion: The Zhang-Suen algorithm is a 2-way algorithm, so for each iteration, it performs two sets of checks during which pixels are removed from the image. Zhang-Suen's algorithm works on a plot of black pixels with eight neighbors. This means that the pixels found along the edges of the image are not analyzed. Hilditch thinning algorithm occurs in several passages, where the algorithm checks all pixels and decides whether to replace a pixel from black to white if certain conditions are satisfied. This Ateb-Gabor filtering will provide better performance, as it allows to obtain more hollow shapes, organize a larger range of curves. Numerous experimental studies confirm the effectiveness of the proposed method.

Download Full-text