The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
L'authentification bilatérale sans effort a été introduite récemment pour utiliser un bracelet de confiance afin d'authentifier en permanence un utilisateur de smartphone. Un utilisateur est autorisé à utiliser le smartphone s'il est déterminé que le bracelet et le smartphone sont tenus par la même personne en comparant le mouvement du bracelet avec la saisie ou le mouvement du smartphone, en fonction de la prise en main (quelle main tient le smartphone et quelle main fournit la saisie). . Malheureusement, ce système présente plusieurs lacunes. Premièrement, il peut ne pas fonctionner correctement lorsque l'utilisateur marche, car la démarche peut masquer les mouvements de contact du poignet. Deuxièmement, il compare en permanence les mouvements des deux appareils, ce qui entraîne une lourde charge de communication. Troisièmement, l’inférence d’adhérence basée sur l’accélération, qui suppose que le smartphone est horizontal par rapport au sol, est inapplicable en pratique. , wristwear-assisted user authentication for smartphones in this paper. Pour remédier à ces lacunes, nous proposons dans cet article WearAuth , une authentification des utilisateurs assistée par bracelet pour les smartphones. WearAuth applique une analyse multi-résolution basée sur des ondelettes pour extraire les mouvements tactiles souhaités, que l'utilisateur soit immobile ou en mouvement ; utilise une corrélation approximative basée sur une transformée de Fourier discrète pour réduire la surcharge de communication ; et adopte une nouvelle approche pour calculer directement l'orientation relative du dispositif sans utiliser l'accélération pour déduire plus précisément l'adhérence. Dans deux expériences portant sur 50 sujets, WearAuth a produit des taux de faux négatifs de 3.6 % ou moins et des taux de faux positifs de 1.69 % ou moins. Nous concluons que WearAuth fonctionne correctement dans divers cas d'utilisation et est robuste aux attaques sophistiquées.
Taeho KANG
Pohang University of Science and Technology (POSTECH)
Sangwoo JI
Pohang University of Science and Technology (POSTECH)
Hayoung JEONG
Pohang University of Science and Technology (POSTECH)
Bin ZHU
Microsoft Research Asia
Jong KIM
Pohang University of Science and Technology (POSTECH)
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Taeho KANG, Sangwoo JI, Hayoung JEONG, Bin ZHU, Jong KIM, "WearAuth: Wristwear-Assisted User Authentication for Smartphones Using Wavelet-Based Multi-Resolution Analysis" in IEICE TRANSACTIONS on Information,
vol. E102-D, no. 10, pp. 1976-1992, October 2019, doi: 10.1587/transinf.2019EDP7024.
Abstract: Zero-effort bilateral authentication was introduced recently to use a trusted wristwear to continuously authenticate a smartphone user. A user is allowed to use the smartphone if both wristwear and smartphone are determined to be held by the same person by comparing the wristwear's motion with the smartphone's input or motion, depending on the grip — which hand holds the smartphone and which hand provides the input. Unfortunately, the scheme has several shortcomings. First, it may work improperly when the user is walking since the gait can conceal the wrist's motions of making touches. Second, it continuously compares the motions of the two devices, which incurs a heavy communication burden. Third, the acceleration-based grip inference, which assumes that the smartphone is horizontal with the ground is inapplicable in practice. To address these shortcomings, we propose <I>WearAuth</I>, wristwear-assisted user authentication for smartphones in this paper. WearAuth applies wavelet-based multi-resolution analysis to extract the desired touch-specific movements regardless of whether the user is stationary or moving; uses discrete Fourier transform-based approximate correlation to reduce the communication overhead; and takes a new approach to directly compute the relative device orientation without using acceleration to infer the grip more precisely. In two experiments with 50 subjects, WearAuth produced false negative rates of 3.6% or less and false positive rates of 1.69% or less. We conclude that WearAuth operates properly under various usage cases and is robust to sophisticated attacks.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2019EDP7024/_p
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@ARTICLE{e102-d_10_1976,
author={Taeho KANG, Sangwoo JI, Hayoung JEONG, Bin ZHU, Jong KIM, },
journal={IEICE TRANSACTIONS on Information},
title={WearAuth: Wristwear-Assisted User Authentication for Smartphones Using Wavelet-Based Multi-Resolution Analysis},
year={2019},
volume={E102-D},
number={10},
pages={1976-1992},
abstract={Zero-effort bilateral authentication was introduced recently to use a trusted wristwear to continuously authenticate a smartphone user. A user is allowed to use the smartphone if both wristwear and smartphone are determined to be held by the same person by comparing the wristwear's motion with the smartphone's input or motion, depending on the grip — which hand holds the smartphone and which hand provides the input. Unfortunately, the scheme has several shortcomings. First, it may work improperly when the user is walking since the gait can conceal the wrist's motions of making touches. Second, it continuously compares the motions of the two devices, which incurs a heavy communication burden. Third, the acceleration-based grip inference, which assumes that the smartphone is horizontal with the ground is inapplicable in practice. To address these shortcomings, we propose <I>WearAuth</I>, wristwear-assisted user authentication for smartphones in this paper. WearAuth applies wavelet-based multi-resolution analysis to extract the desired touch-specific movements regardless of whether the user is stationary or moving; uses discrete Fourier transform-based approximate correlation to reduce the communication overhead; and takes a new approach to directly compute the relative device orientation without using acceleration to infer the grip more precisely. In two experiments with 50 subjects, WearAuth produced false negative rates of 3.6% or less and false positive rates of 1.69% or less. We conclude that WearAuth operates properly under various usage cases and is robust to sophisticated attacks.},
keywords={},
doi={10.1587/transinf.2019EDP7024},
ISSN={1745-1361},
month={October},}
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TY - JOUR
TI - WearAuth: Wristwear-Assisted User Authentication for Smartphones Using Wavelet-Based Multi-Resolution Analysis
T2 - IEICE TRANSACTIONS on Information
SP - 1976
EP - 1992
AU - Taeho KANG
AU - Sangwoo JI
AU - Hayoung JEONG
AU - Bin ZHU
AU - Jong KIM
PY - 2019
DO - 10.1587/transinf.2019EDP7024
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E102-D
IS - 10
JA - IEICE TRANSACTIONS on Information
Y1 - October 2019
AB - Zero-effort bilateral authentication was introduced recently to use a trusted wristwear to continuously authenticate a smartphone user. A user is allowed to use the smartphone if both wristwear and smartphone are determined to be held by the same person by comparing the wristwear's motion with the smartphone's input or motion, depending on the grip — which hand holds the smartphone and which hand provides the input. Unfortunately, the scheme has several shortcomings. First, it may work improperly when the user is walking since the gait can conceal the wrist's motions of making touches. Second, it continuously compares the motions of the two devices, which incurs a heavy communication burden. Third, the acceleration-based grip inference, which assumes that the smartphone is horizontal with the ground is inapplicable in practice. To address these shortcomings, we propose <I>WearAuth</I>, wristwear-assisted user authentication for smartphones in this paper. WearAuth applies wavelet-based multi-resolution analysis to extract the desired touch-specific movements regardless of whether the user is stationary or moving; uses discrete Fourier transform-based approximate correlation to reduce the communication overhead; and takes a new approach to directly compute the relative device orientation without using acceleration to infer the grip more precisely. In two experiments with 50 subjects, WearAuth produced false negative rates of 3.6% or less and false positive rates of 1.69% or less. We conclude that WearAuth operates properly under various usage cases and is robust to sophisticated attacks.
ER -