2018
DOI: 10.1007/978-3-030-01821-4_8
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On Continuous User Authentication via Hidden Free-Text Based Monitoring

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Cited by 5 publications
(5 citation statements)
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“…FAR = 0.0%, FRR = 1.19% and ERR = 0.59% [48] Iris [49][50][51] Classification accuracy higher than 99.9%. FAR = 0,00001%, FRR = 0.1% [52] Retina [53,54] The true acceptance rate 98.148% [55] Face [56,57] FAR = 0,1%, FRR = 7% [52] Keystroke dynamics [58][59][60] Classification accuracy 92.60% [61] Signature dynamics [62,63] Average FAR = 5.125%, FRR = 5.5%, AER = 5.31% [64] Speech [65][66][67] Classification accuracy up to 99%. EER = 1% [68] The analysis of the presented values of the accuracy of authentication does not allow us to speak of a single use of features, however, it makes relevant their use within multimodal authentication (for example, face + iris [69], face and vein arrangement on finger, fingerprint, and voice [70], complex parameters of fingers and palms [71,72]) and the construction of ensembles of various types [73,74].…”
Section: Biometric Characteristic Papers Resultsmentioning
confidence: 99%
“…FAR = 0.0%, FRR = 1.19% and ERR = 0.59% [48] Iris [49][50][51] Classification accuracy higher than 99.9%. FAR = 0,00001%, FRR = 0.1% [52] Retina [53,54] The true acceptance rate 98.148% [55] Face [56,57] FAR = 0,1%, FRR = 7% [52] Keystroke dynamics [58][59][60] Classification accuracy 92.60% [61] Signature dynamics [62,63] Average FAR = 5.125%, FRR = 5.5%, AER = 5.31% [64] Speech [65][66][67] Classification accuracy up to 99%. EER = 1% [68] The analysis of the presented values of the accuracy of authentication does not allow us to speak of a single use of features, however, it makes relevant their use within multimodal authentication (for example, face + iris [69], face and vein arrangement on finger, fingerprint, and voice [70], complex parameters of fingers and palms [71,72]) and the construction of ensembles of various types [73,74].…”
Section: Biometric Characteristic Papers Resultsmentioning
confidence: 99%
“…This is the study where people can be well-known for their typing style, much like handwriting. It is a software-based method [51] that can be easily integrated with an existing knowledge-based security system to make the authentication process stricter, better, and more secure without interrupting the system's own merits [52]. It also enables security during the entire session, continuously [53].…”
Section: Keystroke Dynamicsmentioning
confidence: 99%
“…In addition to the references, the table includes the classification parameter, recognition method, and performance indicators. The data were borrowed from our own studies [ 20 , 26 ] or adapted from the reviews [ 17 , 22 , 24 , 27 – 33 ].…”
Section: Keystroke Authentication and Identificationmentioning
confidence: 99%