This study proposes a system for biometric access control utilising the improved Cultural Chicken Swarm Optimization(CCSO)technique.This approach mitigates the limitations of conventional Chicken Swarm Optimization(CS...This study proposes a system for biometric access control utilising the improved Cultural Chicken Swarm Optimization(CCSO)technique.This approach mitigates the limitations of conventional Chicken Swarm Optimization(CSO),especially in dealing with larger dimensions due to diversity loss during solution space exploration.Our experimentation involved 600 sample images encompassing facial,iris,and fingerprint data,collected from 200 students at Ladoke Akintola University of Technology(LAUTECH),Ogbomoso.The results demonstrate the remarkable effectiveness of CCSO,yielding accuracy rates of 90.42%,91.67%,and 91.25%within 54.77,27.35,and 113.92 s for facial,fingerprint,and iris biometrics,respectively.These outcomes significantly outperform those achieved by the conventional CSO technique,which produced accuracy rates of 82.92%,86.25%,and 84.58%at 92.57,63.96,and 163.94 s for the same biometric modalities.The study’s findings reveal that CCSO,through its integration of Cultural Algorithm(CA)Operators into CSO,not only enhances algorithm performance,exhibiting computational efficiency and superior accuracy,but also carries broader implications beyond biometric systems.This innovation offers practical benefits in terms of security enhancement,operational efficiency,and adaptability across diverse user populations,shaping more effective and resource-efficient access control systems with real-world applicability.展开更多
Iris recognition technology(IRT)-based authentication is a biometric financial technology(FinTech)application used to automate user recognition and verification.In addition to being a controversial technology with var...Iris recognition technology(IRT)-based authentication is a biometric financial technology(FinTech)application used to automate user recognition and verification.In addition to being a controversial technology with various facilitators and inhibitors,the adoption of IRT-based FinTech is driven by contextual factors,such as customer perceptions,deployed biometric technology,and financial transaction settings.Due to its controversial and contextual properties,analyzing IRT-based FinTech acceptance is challenging.This study uses a net valence framework to investigate the salient positive and negative factors influencing the intention to use IRT-based FinTech in automated teller machines(ATMs)in Jordan.This study is pertinent because there is a dearth of research on IRT-based FinTech in the relevant literature;most previous research has taken purely engineering and technical approaches.Furthermore,despite considerable investments by banks and other financial institutions in this FinTech,target user adoption is minimal,and only 6% of Jordan’s ATM transactions are currently IRT-enabled.This study employs mixed methods.In the first qualitative study,17 Jordanian customers were interviewed regarding the benefits and risks of IRT-based FinTech in ATMs.Content analyses determined the most important concepts or themes.The advantages include financial security,convenience,and FinTech-enabled hygiene,whereas the concerns include performance,financial,privacy,and physical risks.The research model is constructed based on the qualitative study and theoretical underpinnings,wherein 631 Jordanian bank customers with active ATM accounts were surveyed to validate the research model.The findings indicate that IRT-based FinTech usage in ATMs is proportional to its perceived value.In descending order of effect,financial security,FinTech-enabled hygiene,and convenience benefits positively impact perceived value.Privacy,financial,and physical risks have negative impacts on perceived value,whereas performance risk has no effect.This study contributes to the relatively untapped domain of biometric technology in information systems,with important theoretical and practical implications.展开更多
Most user authentication mechanisms of cloud systems depend on the credentials approach in which a user submits his/her identity through a username and password.Unfortunately,this approach has many security problems b...Most user authentication mechanisms of cloud systems depend on the credentials approach in which a user submits his/her identity through a username and password.Unfortunately,this approach has many security problems because personal data can be stolen or recognized by hackers.This paper aims to present a cloud-based biometric authentication model(CBioAM)for improving and securing cloud services.The research study presents the verification and identification processes of the proposed cloud-based biometric authentication system(CBioAS),where the biometric samples of users are saved in database servers and the authentication process is implemented without loss of the users’information.The paper presents the performance evaluation of the proposed model in terms of three main characteristics including accuracy,sensitivity,and specificity.The research study introduces a novel algorithm called“Bio_Authen_as_a_Service”for implementing and evaluating the proposed model.The proposed system performs the biometric authentication process securely and preserves the privacy of user information.The experimental result was highly promising for securing cloud services using the proposed model.The experiments showed encouraging results with a performance average of 93.94%,an accuracy average of 96.15%,a sensitivity average of 87.69%,and a specificity average of 97.99%.展开更多
基金supported by Ladoke Akintola University of Technology,Ogbomoso,Nigeria and the University of Zululand,South Africa.
文摘This study proposes a system for biometric access control utilising the improved Cultural Chicken Swarm Optimization(CCSO)technique.This approach mitigates the limitations of conventional Chicken Swarm Optimization(CSO),especially in dealing with larger dimensions due to diversity loss during solution space exploration.Our experimentation involved 600 sample images encompassing facial,iris,and fingerprint data,collected from 200 students at Ladoke Akintola University of Technology(LAUTECH),Ogbomoso.The results demonstrate the remarkable effectiveness of CCSO,yielding accuracy rates of 90.42%,91.67%,and 91.25%within 54.77,27.35,and 113.92 s for facial,fingerprint,and iris biometrics,respectively.These outcomes significantly outperform those achieved by the conventional CSO technique,which produced accuracy rates of 82.92%,86.25%,and 84.58%at 92.57,63.96,and 163.94 s for the same biometric modalities.The study’s findings reveal that CCSO,through its integration of Cultural Algorithm(CA)Operators into CSO,not only enhances algorithm performance,exhibiting computational efficiency and superior accuracy,but also carries broader implications beyond biometric systems.This innovation offers practical benefits in terms of security enhancement,operational efficiency,and adaptability across diverse user populations,shaping more effective and resource-efficient access control systems with real-world applicability.
文摘Iris recognition technology(IRT)-based authentication is a biometric financial technology(FinTech)application used to automate user recognition and verification.In addition to being a controversial technology with various facilitators and inhibitors,the adoption of IRT-based FinTech is driven by contextual factors,such as customer perceptions,deployed biometric technology,and financial transaction settings.Due to its controversial and contextual properties,analyzing IRT-based FinTech acceptance is challenging.This study uses a net valence framework to investigate the salient positive and negative factors influencing the intention to use IRT-based FinTech in automated teller machines(ATMs)in Jordan.This study is pertinent because there is a dearth of research on IRT-based FinTech in the relevant literature;most previous research has taken purely engineering and technical approaches.Furthermore,despite considerable investments by banks and other financial institutions in this FinTech,target user adoption is minimal,and only 6% of Jordan’s ATM transactions are currently IRT-enabled.This study employs mixed methods.In the first qualitative study,17 Jordanian customers were interviewed regarding the benefits and risks of IRT-based FinTech in ATMs.Content analyses determined the most important concepts or themes.The advantages include financial security,convenience,and FinTech-enabled hygiene,whereas the concerns include performance,financial,privacy,and physical risks.The research model is constructed based on the qualitative study and theoretical underpinnings,wherein 631 Jordanian bank customers with active ATM accounts were surveyed to validate the research model.The findings indicate that IRT-based FinTech usage in ATMs is proportional to its perceived value.In descending order of effect,financial security,FinTech-enabled hygiene,and convenience benefits positively impact perceived value.Privacy,financial,and physical risks have negative impacts on perceived value,whereas performance risk has no effect.This study contributes to the relatively untapped domain of biometric technology in information systems,with important theoretical and practical implications.
基金funding for this study from King Khalid University,Grant Number(GRP-35–40/2019).
文摘Most user authentication mechanisms of cloud systems depend on the credentials approach in which a user submits his/her identity through a username and password.Unfortunately,this approach has many security problems because personal data can be stolen or recognized by hackers.This paper aims to present a cloud-based biometric authentication model(CBioAM)for improving and securing cloud services.The research study presents the verification and identification processes of the proposed cloud-based biometric authentication system(CBioAS),where the biometric samples of users are saved in database servers and the authentication process is implemented without loss of the users’information.The paper presents the performance evaluation of the proposed model in terms of three main characteristics including accuracy,sensitivity,and specificity.The research study introduces a novel algorithm called“Bio_Authen_as_a_Service”for implementing and evaluating the proposed model.The proposed system performs the biometric authentication process securely and preserves the privacy of user information.The experimental result was highly promising for securing cloud services using the proposed model.The experiments showed encouraging results with a performance average of 93.94%,an accuracy average of 96.15%,a sensitivity average of 87.69%,and a specificity average of 97.99%.
