Evaluation of biometric systems: a study of users' acceptance and satisfaction

El-Abed, Mohamad; Giot, Romain; Hemery, Baptiste; Rosenberger, Christophe

doi:10.1504/ijbm.2012.047644

Cited by 19 publications

(11 citation statements)

References 32 publications

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“…Second is the principle of informed consentresonating with our claims around the importance of knowing who has access to our identity data and the need for choice in opting in or out of systems, and finally the principle of truth and accuracy in business operations which reflects our discussion of the importance of competence in the effective roll out of any identity management system. Again, in the biometrics world we have seen that the perceived trust and robustness of biometrics against privacy attacks is an important factor for acceptance [El-Abed et al 2012].…”

Section: Design and Policy Implicationsmentioning

confidence: 99%

An Inclusive, Value Sensitive Design Perspective on Future Identity Technologies

Briggs

Thomas

2015

ACM Trans. Comput.-Hum. Interact.

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Identity technologies constitute one of the fastest growing areas for research and development, driven by both commercial and administrative imperatives. Crucially, they constitute the means by which we include or exclude individuals and groups in terms of access to goods, services or information-yet few developments in this space embrace an inclusive or value sensitive design philosophy. We describe a rigorous exercise in which we source scenarios that capture new research in the identity space and use these as probes in an inclusive design process. Workshops were held with 6 marginalized community groups: young people, older adults, refugees, black minority ethnic [BME] women, people with disabilities, and mental health service users. Our findings echo Herzberg's two-factor theory in that we are able to identify a set of relatively common values around sources of potential dissatisfaction [hygiene factors] as well as a set of motivators that are differentially valued across communities.

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Section: Design and Policy Implicationsmentioning

confidence: 99%

An Inclusive, Value Sensitive Design Perspective on Future Identity Technologies

Briggs

Thomas

2015

ACM Trans. Comput.-Hum. Interact.

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“…• Abed et al [40] present a modality-independent evaluation methodology to study users' acceptance and satisfaction of biometric systems. It uses a survey questionnaire for data collection, and some data mining tools for their analysis.…”

Section: Platformsmentioning

confidence: 99%

Evaluation of Biometric Systems

El-Abed¹,

Giot²,

Rosenberger³

2012

New Trends and Developments in Biometrics

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International audienceBiometrics is considered as a promising solution among traditional methods based on "what we own" (such as a key) or "what we know" (such as a password). It is based on "what we are" and "how we behave". Few people know that biometrics have been used for ages for identification or signature purposes. In 1928 for example, fingerprints were used for women clerical employees of Los Angeles police department as depicted in Figure 1. Fingerprints were also already used as a signature for commercial exchanges in Babylon (-3000 before JC). Alphonse Bertillon proposed in 1879 to use anthropometric information for police investigation. Nowadays, all police forces in the world use this kind of information to resolve crimes. The first prototypes of terminals providing an automatic processing of the voice and digital fingerprints have been defined in the middle of the years 1970. Nowadays, biometric authentication systems have many applications [1]: border control, e-commerce, etc. The main benefits of this technology are to provide a better security, and to facilitate the authentication process for a user. Also, it is usually difficult to copy the biometric characteristics of an individual than most of other authentication methods such as passwords. Despite the obvious advantages of biometric systems, their proliferation was not as much as attended. The main drawback is the uncertainty of the verification result. By contrast to password checking, the verification of biometric raw data is subject to errors and represented by a similarity percentage (100% is never reached). Others drawbacks related to vulnerabilities and usability issues exist. In addition, in order to be used in an industrial context, the quality of a biometric system must be precisely quantified. We need a reliable evaluation methodology in order to put into obviousness the benefit of a new biometric system. Moreover, many questions remain: Shall we be confident in this technology? What kind of biometric modalities can be used? What are the trends in this domain? The objective of this chapter is to answer these questions, by presenting an evaluation methodology of biometric systems

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“…The performance of an existing algorithm will be studied in a different way through the use of different iris database. This research is necessary as most users may be non-cooperative [20,7] and an accurate system would be rated low on users experience in a practical environment with large number of subjects [21]. [43] algorithm was selected based on the methods used in different phases in iris recognition and the way they addressed issues with existing algorithms.…”

Section: Introductionmentioning

confidence: 99%

Reanalyzing Li and Tao. (2014): Investigating Algorithm Recognition on Dark Irises

Omotosho¹,

Adegbola²,

Edobor³

2016

IJCA

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Iris recognition algorithms have been proposed in several works with some of these algorithms solving mainly templates identification accuracy issues. The need to test these algorithms for identification or matching speed cannot be over-emphasized as this is also important when deploying algorithms in real application. This aim of this paper is to implement and validate a selected iris recognition algorithm. Performance evaluation was performed with the sole purpose of verifying the literature reported accuracy for the selected algorithm as well as to compute its identification speed on two databases (CASIA and BuIris) containing 600 iris images each. Results obtained matched the earlier 0% false acceptance with CASIA database but 42.3% with BuIris. This paper results verifies the scope of this algorithm and the need for improvement that could increase its adoptability globally.

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Evaluation of biometric systems: a study of users' acceptance and satisfaction

Cited by 19 publications

References 32 publications

An Inclusive, Value Sensitive Design Perspective on Future Identity Technologies

An Inclusive, Value Sensitive Design Perspective on Future Identity Technologies

Evaluation of Biometric Systems

Reanalyzing Li and Tao. (2014): Investigating Algorithm Recognition on Dark Irises

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