Evaluating the Influence of Targets and Hand Postures on Touch-based Behavioural Biometrics

Buschek, Daniel; Luca, Alexander De; Alt, Florian

doi:10.1145/2858036.2858165

Cited by 31 publications

(10 citation statements)

References 44 publications

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“…There is, however, an additional aspect of using smartphone as compared to desktop computer: namely, the touchscreen of the smartphone can also easily be operated with thumbs instead of index fingers; which allows more mobility for the user, and which is in fact the more common and natural way for smartphone usage in general (e.g., Azenkot & Zhai, 2012;Bröhl, Mertens, & Ziefle, 2017). Several studies have shown that using index finger responses instead of thumbs can lead to different results: In particular, it has been consistently found that more accurate general input (mainly: typing) can be given using index fingers (Buschek, De Luca, & Alt, 2016;Lehmann & Kipp, 2018;Wang & Ren, 2009;Wobbrock, Myers, & Aung, 2008). However, results have been mixed regarding speed differences, which seems to depend on the particular input type and study design (Azenkot & Zhai, 2012;Goel, Jansen, Mandel, Patel, & Wobbrock, 2013;Lehmann & Kipp, 2018;Wobbrock et al, 2008).…”

Section: Discussionmentioning

confidence: 99%

“…Regarding accuracy rates, we have shown that there is a small difference, in that slightly higher probe-toirrelevant accuracy rate differences are found when using thumbs. This may be because using thumbs, as opposed to index fingers, is more sensitive to tasks requiring accuracy, and more prone to error rates in general (Buschek et al, 2016;Lehmann & Kipp, 2018;Wang & Ren, 2009;Wobbrock et al, 2008). This aspect could be explored in the future.…”

Section: Discussionmentioning

confidence: 99%

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Response Time Concealed Information Test on Smartphones

Lukács

Kleinberg

Kunzi

et al. 2020

Collabra: Psychology

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The Response Time-Based Concealed Information Test (RT-CIT) can reveal when a person recognizes a relevant (probe) item among other, irrelevant items, based on comparatively slower responding to the probe item. Thereby, if a person is concealing the knowledge about the relevance of this item (e.g., recognizing it as a murder weapon), this deception can be revealed. So far, the RT-CIT has been used only on desktop computers. In Experiment 1 (n = 72; within-subject), we compare the probe-irrelevant differences when using the conventional desktop-based CIT to using a smartphone-based CIT, demonstrating practical equivalence. In Experiment 2 (n = 116; within-subject), we demonstrate that using thumbs for responses (while holding the smartphone) leads to equally efficient CIT results as using conventional index finger responses. At the same time, this second experiment also demonstrates how smartphone-based studies may be efficiently run in large groups, using the participants' own smartphones. Finally, as an interesting addition, here for the first time we also measured keypress durations (i.e., the time durations of holding down the response keys) in the RT-CIT, which we found to be significantly shorter for probe than for irrelevant items.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Response Time Concealed Information Test on Smartphones

Lukács

Kleinberg

Kunzi

et al. 2020

Collabra: Psychology

View full text Add to dashboard Cite

show abstract

Section: Discussionmentioning

confidence: 99%

“…This may be because using thumbs, as opposed to index fingers, is more sensitive to tasks requiring accuracy, and more prone to error rates in general (Buschek et al, 2016;Lehmann RT-CIT ON SMARTPHONES 27 & Kipp, 2018;Wang & Ren, 2009;Wobbrock et al, 2008). This aspect could be explored in the future.…”

Section: Discussionmentioning

confidence: 99%

Response Time Concealed Information Test on Smartphones

Lukács¹,

Kleinberg²,

Kunzi³

et al. 2020

Preprint

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The Response Time-Based Concealed Information Test (RT-CIT) can reveal when a person recognizes a relevant (probe) item among other, irrelevant items, based on comparatively slower responding to the probe item. Thereby, if a person is concealing the knowledge about the relevance of this item (e.g., recognizing it as a murder weapon), this deception can be revealed. So far, the RT-CIT has been used only on desktop computers. In Experiment 1 (n = 72; within-subject), we compare the probe-irrelevant differences when using the conventional desktop-based CIT to using a smartphone-based CIT, demonstrating practical equivalence. In Experiment 2 (n = 116; within-subject), we demonstrate that using thumbs for responses (while holding the smartphone) leads to equally efficient CIT results as using conventional index finger responses. At the same time, this second experiment also demonstrates how smartphone-based studies may be efficiently run in large groups, using the participants’ own smartphones. Finally, as an interesting addition, here for the first time we also measured keypress durations (i.e., the time durations of holding down the response keys) in the RT-CIT, which we found to be significantly shorter for probe than for irrelevant items.

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“…It authenticates users during interaction using a fiber optic plate and a highresolution camera. Behavioral approaches analyze, e.g., fingertip locations on multi-touch displays [6], how displays are touched [53], how users type on touch-screen keyboards [33], and GUI element targeting behavior on a touch-screen [8].…”

Section: Environmental Sensingmentioning

confidence: 99%

Zensei

Sato

Puri

Olwal

et al. 2017

Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

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Figure 1. Zensei embeds implicit and uninterrupted user identification in mobile devices, furniture or the environment. Our custom, wide-spectrum multi-electrode sensing hardware allows high-speed wireless data collection of the electrical characteristics of users. A longitudinal 22-day experiment with 46 subjects experiment shows promising classification accuracy and low false acceptance rate. The miniaturized wireless Zensei sensor board (right) has a microprocessor, power management circuit, analog sensing circuit, and Bluetooth module, and is powered by a lithium polymer battery.

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Evaluating the Influence of Targets and Hand Postures on Touch-based Behavioural Biometrics

Cited by 31 publications

References 44 publications

Response Time Concealed Information Test on Smartphones

Response Time Concealed Information Test on Smartphones

Response Time Concealed Information Test on Smartphones

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