DocumentCode :
713544
Title :
Expanding the human-biometric sensor interaction model to identity claim scenarios
Author :
Elliott, Stephen J. ; O´connor, Kevin ; Bartlow, Eric ; Robertson, Joshua J. ; Guest, Richard M.
Author_Institution :
Purdue Univ., West Lafayette, IN, USA
fYear :
2015
fDate :
23-25 March 2015
Firstpage :
1
Lastpage :
6
Abstract :
Biometric technologies represent a significant component of comprehensive digital identity solutions, and play an important role in crucial security tasks. These technologies support identification and authentication of individuals based on their physiological and behavioral characteristics. This has led many governmental agencies to choose biometrics as a supplement to existing identification schemes, most prominently ID cards and passports. Studies have shown that the success of biometric systems relies, in part, on how humans interact and accept such systems. In this paper, the authors build on previous work related to the Human-Biometric Sensor Interaction (HBSI) model and examine it with respect to the introduction of a token (e.g. an electronic passport or identity card) into the biometric system. The role of the imposter within an Identity Claim scenario has been integrated to expand the HBSI model into a full version, which is able to categorise potential False Claims and Attack Presentations.
Keywords :
biometrics (access control); sensors; HBSI model; ID cards; attack presentations; behavioral characteristics; biometric technologies; digital identity solutions; false claims; governmental agencies; human-biometric sensor interaction model; identity claim scenarios; individual authentication; individual identification; passports; physiological characteristics; security task; token; Adaptation models; Authentication; Biological system modeling; Fingerprint recognition; Measurement; Usability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Identity, Security and Behavior Analysis (ISBA), 2015 IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4799-1974-1
Type :
conf
DOI :
10.1109/ISBA.2015.7126362
Filename :
7126362
Link To Document :
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