The week's pick
Random Articles
Reseach Article
An Improved Framework for Intrusion Prevention in a Host-based Biometric Identification System
| International Journal of Applied Information Systems |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 12 - Number 12 |
| Year of Publication: 2018 |
| Authors: Idris Mohammed Kolo, Salihu Alhassan, Hussain Abubakar Zubairu |
10.5120/ijais2018451751
|
Idris Mohammed Kolo, Salihu Alhassan, Hussain Abubakar Zubairu . An Improved Framework for Intrusion Prevention in a Host-based Biometric Identification System. International Journal of Applied Information Systems. 12, 12 ( Apr 2018), 15-18. DOI=10.5120/ijais2018451751
Abstract
This research work is aimed at proposing a framework for intrusion prevention on host-based biometric identification systems (BIS). Intrusive activities in biometric identification systems are mostly perpetuated before the existing prevention systems prevent its future occurrence if the same pattern is exhibited by the perpetuator. The research produced a framework that shows an inclusion of a sensor database that registered all acceptable and certified sensors by the system to capture biometric image. This framework has shown using a developed application to some great extent how it is used to minimize the issue of fake template in the database which will make compromise easy. Once a sensor is attached to the BIS its status will be immediately shown and accessed for qualification to capture image.
References
- Jain, A. K., Ross, A, and Prabhakar, S. 2004. An Introduction to Biometric Recognition. IEEE Transaction on Circuits and Systems for Video Technology, 14(1), 4–20.
- Mgabile, T., Msiza, I. S, and Dube, E. 2012. Anomaly based intrusion detection for Biometric Identification System Using neural Network. International Conference on Artificial Intelligent and Image Processing. Dubai, (December, 2012).
- Ioannis M , Yves P., Sabine D., Elsa L., Carlos R., Martin U, and Marcelino C. 2013. European Union: Biometric at the frontier.
- Jain, B. 2005. Intrusion Prevention and Vulnerability Assessment in Sachet intrusion detection. Masters Thesis. Department of Computer Science and Engineering. Indian Institue of Technology, Kanpur.
- Raymond, T. 2003. Fingerprint Image Enhancement and Minutiae Extraction. Unpublished Phd thesis submitted to School of Computer Science and Software Engineering. University of Western Australia.
- Babatunde, I. G., Charles, A.O., and Olatubosun, O. 2012. A mathematical modeling method for fingerprint ridge segmentation and normalization. International Journal of Computer Science and Information Technology & Security, 2(2), 263-267.
- Arjunwadkar, M., and Kulkarni, R.V. 2010. The rule based intrusion detection and prevention model for biometric systems. Journal of Emerging Trends in Computing and Information Science, 1(2), 117-120.
- Abdullahi M. B., Fati I. and Mohammed A. A. 2016. Performance analysis of particle swarm optimization algorithm-based parameter tuning for fingerprint image enhancement. Futures Technologies Conference. IEEE transaction. Pg: 528-536.
Index Terms
Keywords