A Framework for Verification in Contactless Secure Physical Access Control and Authentication Systems
DOI:
https://doi.org/10.24203/ijcit.v11i1.202Keywords:
Authentication, Biometrics, Contactless, Integrity, SecurityAbstract
Biometrics is one of the very popular techniques in user identification for accessing institutions and logging into attendance systems. Currently, some of the existing biometric techniques such as the use of fingerprints are unpopular due to COVID-19 challenges. This paper identifies the components of a framework for secure contactless access authentication. The researcher selected 50 journals from Google scholar which were used to analyze the various components used in a secure contactless access authentication framework. The methodology used for research was based on the scientific approach of research methodology that mainly includes data collection from the 50 selected journals, analysis of the data and assessment of results. The following components were identified: database, sensor camera, feature extraction methods, matching and decision algorithm. Out of the considered journals the most used is CASIA database at 40%, CCD Sensor camera with 56%, Gabor feature extraction method at 44%, Hamming distance for matching at 100% and PCA at 100% was used for decision making. These findings will assist the researcher in providing a guide on the best suitable components. Various researchers have proposed an improvement in the current security systems due to integrity and security problems.
References
Budzak, D. (2016). Information security – The people issue. Business Information Review, 32, 2, 85–89
Bulgurcu, B., Cavusoglu, H., & Benbasat, I. (2010). Information Security Compliance: An empirical study of rationalitybased beliefs and information security awareness. MIS Qauarterly, 34, 3, 523-527.
Karim, N. A., & Shukur, Z. (2016). Proposed features of an online examination interface design and its optimal values.Computers in Human Behavior, 64, 414–422. https://doi.org/10.1016/j.chb.2016.07.013
Karim, N. A., & Shukur, Z. (2015). Review of user authentication methods in online examination. Asian Journal of Information Technology, 14(5), 166–175
Alexandre, B., Reynaud, E., Osiurak, F., & Navarro, J. (2018). Acceptance and acceptability criteria: A literature review. Cognition, Technology & Work, 20(2), 165–177. https://doi.org/10.1007/s10111-018-0459-1
Edwards, C., Holmes, W., Whitelock, D., & Okada, A. (2018). Student trust in e-authentication. In Proceedings of the Fifth
Annual ACM Conference on Learning at Scale, UK, Article No.: 42, 1–4. https://doi.org/10.1145/3231644.3231700
Bogere Ayub, Faruque A. Haolader, Mohammad Mahbubur Rahman.(2013). The Influence of ICT Security to Academic Environment at Universities, Case Study Uganda; International Journal of Innovative Research in Science, Engineering and Technology
Jain, A. K., Ross, A., & Prabhakar, S. (2004). An introduction to biometric recognition. IEEE Transactions on Circuits and Systems for Video Technology, 14(1), 4–20. https://doi.org/10.1109/TCSVT.2003.818349
Okada, A., Whitelock, D., Holmes, W., & Edwards, C. (2019). E-authentication for online assessment: A mixed-method study.
British Journal of Educational Technology, 50(2), 861–875. https://doi.org/10.1111/bjet.12608.
Commission for University Education. (2017, September 20). News Updates. Retrieved from News and Events: http://www.cue.or.ke/index.php/news-and-events
Raghavendra TVS, Arudhra N, Amaranath K, Raviteja B, and Sreekar G (2014). Humanitarian supply chain model for flood relief-a case study analysis. International Journal of Engineering Research and Technology, 3(1): 3538-3547
Ali MMH and Gaikwad (2016). Multimodal biometrics enhancement recognition system based on fusion of fingerprint and palmprint: A review. Global Journal of Computer Science and Technology, 16(2): 1-15
Mahto D and Yadav DK (2013). Network security using ECC with Biometric. In the International Conference on Heterogeneous
Networking for Quality, Reliability, Security and Robustness, Springer, Greader Noida, India: 842-853
Kumar A and Prathyusha KV (2009). Personal authentication using hand vein triangulation and knuckle shape. IEEE Transactions on Image Processing, 18(9): 2127-2136.
Nie W, Zhang B, and Zhao S.(2019). Discriminative local feature for hyperspectral hand biometrics by adjusting image acutance. Applied Sciences, 9(19): 4178
George A, Karthick G, and Harikumar R (2014). An efficient system for palm print recognition using ridges. In the International Conference on Intelligent Computing Applications, IEEE, and Coimbatore, India: 249-253.
Moini, A., & Madni, A. M. (2009). Leveraging biometrics for user authentication in online learning: A systems perspective.
IEEE Systems Journal, 3(4), 469–476. https://doi.org/10.1109/JSYST.2009.2038957
Drevin, L., Kruger, H. A., & Steyn, T. (2007). Value-focused assessment of ICT security awareness in an academic environment. Computers & Security, 26, 1, 36-43
Miura N, Nagasaka A, and Miyatake T (2007). Extraction of fingervein patterns using maximum curvature points in image profiles. IEICE Transactions on Information and Systems, 90(8): 1185-1194.
Adel Ismail Al-Alawi, Sulaiman M.H. Al-Kandari and Refaat Hassan Abdel-Razek.(2016). Evaluation of information system security awareness
Albuquerque Junior & Santos.(2016). Adoption of information security measures in public research institutes.
Johnson, J., Lincke, S. J., Imhof, R., & Lim, C. (2014). A comparison of international information security regulations R. Nicole, “Title of paper with only first word capitalized,” J. Name Stand. Abbrev., in press.
Margaret Rouse.(2016). Managing information security amid new threats: A guide for CIOs; http://searchsecurity.techtarget.com/definition/infor mation security-infosec
Parsons, K., McCormac, A., Pattinson, M., Butavicius, M., & Jerram, C. (2014). A study of information security awareness in Australian government organizations. Information Management & Computer Security, 22, 4, 334-345
Laybats, C., & Tredinnick, L. (2016). Information Security. Business Information Review, 33, 2, 76-80
Jung, S., & Park, J. Y. (2020). The Effect of Security Awareness Training on the Use of Biometric Authentication: Focusing on the Protection Motivational Behaviors. Journal of Information Technology Applications and Management, 27(2), 1-21.
Soh, S. C., Ibrahim, M. Z., & Yakno, M. (2018). A review: Personal identification based on palm vein infrared pattern. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 10(1-4), 175-180.
Wu, W., Elliott, S. J., Lin, S., Sun, S., & Tang, Y. (2019). Review of palm vein recognition. IET Biometrics, 9(1), 1-10.
Gurunathan, V., Bharathi, S., & Sudhakar, R. (2015, January). Image enhancement techniques for palm vein images. In 2015 International Conference on Advanced Computing and Communication Systems (pp. 1-5). IEEE.
Awate I and Dixit BA.(2015). Palm print based person identification. In the International Conference on Computing Communication Control and Automation, IEEE, Pune, India: 781-785
Athale, S. S., Patil, D., Deshpande, P., & Dandawate, Y. H.(2015). Hardware implementation of palm vein biometric modality for access control in multilayered security system. Procedia Computer Science, 58, 492-498.
Barra, S., De Marsico, M., Nappi, M., Narducci, F., & Riccio, D. (2019). A hand-based biometric system in visible light for mobile environments. Information Sciences, 479, 472-485.
Malathi, R. (2016). An integrated approach of physical biometric authentication system. Procedia Computer Science, 85, 820-826.
Michael, G. K. O., Connie, T., & Teoh, A. B. J. (2011). A contactless biometric system using palm print and palm vein features. Advanced Biometric Technologies, 155-177.
Patil, P. A., & Ajmire, P. E. (2018). Survey: Human Identification Using Palm Vein Images. Int J Emerging Technologies in Engineering Research, 6(3).
Tome, P., & Marcel, S. (2015, September). Palm vein database and experimental framework for reproducible research. In 2015 International Conference of the Biometrics Special Interest Group (BIOSIG) (pp. 1-7). IEEE.
Shah, G., Shirke, S., Sawant, S., & Dandawate, Y. H. (2015). Palm vein pattern-based biometric recognition system. International Journal of Computer Applications in Technology, 51(2), 105-111.
Wu, W., Elliott, S. J., Lin, S., Sun, S., & Tang, Y. (2020). Review of palm vein recognition. IET Biometrics, 9(1), 1-10.
Wu, W., Elliott, S. J., Lin, S., & Yuan, W. (2019). Low-cost biometric recognition system based on NIR palm vein image. IET Biometrics, 8(3), 206-214.
Shende, P., & Dandawate, Y. (2020). Convolutional neural network-based feature extraction using multimodal for high security application. Evolutionary Intelligence, 1-11.
Soh, S. C., Ibrahim, M. Z., & Yakno, M. (2018). A review: Personal identification based on palm vein infrared pattern. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 10(1-4), 175-180.
Gayathri, S., K. Gerard Joe Nigel, and S. Prabakar.(2013)"Low cost hand vein authentication system on embedded linux platform." Int J Innovative Technol Exploring Eng 2, no. 4 138-141.
Kulkarni, S., & Pandit, M. (2016). Biometric recognition system based on dorsal hand veins. Int J Innov Res Sci Eng Technol, 5(9), 18899-18905.
Al-Juboori, A. M., Bu, W., Wu, X., & Zhao, Q. (2014). Palm vein verification using multiple features and locality preserving projections. The Scientific World Journal, 2014.
Dr. A. A. Gurjar, M. S. N. D. (2017). Identification of Human using Palm-Vein Images: A new trend in biometrics. International Journal of Engineering and Computer Science, 6(1).
Min pieng.(2016), ‘‘Template Matching Based on Geometric Invariance in Deep Neural Network
Shriram D.(2016).Statistical Analysis of Resulting Palm vein Image through Enhancement Operations‖, International Journal of Information Engineering and Electronics Business
Hao, Y., Sun, Z., Tan, T., & Ren, C. (2008, October). Multispectral palm image fusion for accurate contact-free palmprint recognition. In 2008 15th IEEE International Conference on Image Processing (pp. 281-284). IEEE.
Zhang, D., Guo, Z., Lu, G., Zhang, L., & Zuo, W. (2009). An online system of multispectral palmprint verification. IEEE transactions on instrumentation and measurement, 59(2), 480-490
Hernández-García, R., Barrientos, R. J., Rojas, C., & Mora, M. (2019). Individuals identification based on palm vein matching under a parallel environment. Applied Sciences, 9(14), 2805.
Downloads
Published
Issue
Section
License
Copyright (c) 2022 Boniface Mwangi
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
The articles published in International Journal of Computer and Information Technology (IJCIT) is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
