Author(s):
1. Tiyani Christopher Hlongwane:
Department of Information Technology, Tshwane University of Technology, South Africa
2. Topside E. Mathonsi:
Department of Information Technology, Tshwane University of Technology, South Africa
3. Deon Du Plessis:
Department of Information Technology, Tshwane University of Technology, South Africa
4. Tonderai Muchenje:
Department of Information Technology, Tshwane University of Technology, South Africa
Abstract:
The global expansion of e-business applications has introduced novel challenges, with an escalating number of security issues linked to online transactions, such as phishing attacks and identity theft. E-business involves conducting buying and selling activities online, facilitated by the Internet. The application of biometrics has been proposed as a solution to mitigate security concerns in ebusiness transactions. Biometric recognition involves the use of automated techniques to validate an individual's identity based on both physiological and behavioural characteristics. This research focuses specifically on implementing a multimodal biometric recognition system that incorporates face and fingerprint data to enhance the security of e-business transactions. In contrast to unimodal systems relying on a single biometric modality, this approach addresses limitations such as noise, universality, and variations in both interclass and intraclass scenarios. The study emphasizes the advantages of multimodal biometric systems while shedding light on vulnerabilities in biometrics within the ebusiness context. This in-depth analysis serves as a valuable resource for those exploring the intersection of e-business and biometrics, providing insights into the strengths, challenges, and best practices for stakeholders in this domain. Finally, the paper concludes with a summary and outlines potential avenues for future research.
Page(s):
263-279
DOI:
DOI not available
Published:
Journal: International Journal of Communication Networks and Information Security, Volume: 15, Issue: 4, Year: 2023
Keywords:
Multimodal
,
face
,
Phishing
,
Fingerprint
,
Ebusiness
,
Biometric
,
Identity Theft
,
Unimodal
References:
References are not available for this document.
Citations
Citations are not available for this document.