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".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
신뢰할 수 있는 손목 착용 장치를 사용하여 지속적으로 스마트폰 사용자를 인증하는 제로 노력(Zero-Effort) 양방향 인증이 최근 도입되었습니다. 어느 손이 스마트폰을 쥐고 어느 손이 입력을 하는지 그립에 따라 손목웨어의 움직임과 스마트폰의 입력 또는 모션을 비교하여 손목웨어와 스마트폰을 모두 동일한 사람이 쥐고 있는 것으로 판단되면 스마트폰을 사용할 수 있습니다. . 불행하게도 이 계획에는 몇 가지 단점이 있습니다. 첫째, 보행으로 인해 손목의 터치 동작이 숨겨질 수 있으므로 사용자가 걷고 있을 때 제대로 작동하지 않을 수 있습니다. 둘째, 두 장치의 동작을 지속적으로 비교하므로 통신 부담이 크다. 셋째, 스마트폰이 지면과 수평을 이룬다고 가정하는 가속도 기반 그립 추론은 실제로 적용할 수 없습니다. , wristwear-assisted user authentication for smartphones in this paper. 이러한 단점을 해결하기 위해 본 논문에서는 스마트폰 손목 착용 사용자 인증인 WearAuth를 제안한다. WearAuth는 웨이블릿 기반 다중 해상도 분석을 적용하여 사용자가 정지 상태인지 이동 상태인지에 관계없이 원하는 터치별 움직임을 추출합니다. 통신 오버헤드를 줄이기 위해 이산 푸리에 변환 기반 근사 상관 관계를 사용합니다. 그립을 더 정확하게 추론하기 위해 가속도를 사용하지 않고 상대 장치 방향을 직접 계산하는 새로운 접근 방식을 취합니다. 50명의 피험자를 대상으로 한 두 번의 실험에서 WearAuth는 3.6% 이하의 위음성 비율과 1.69% 이하의 위양성 비율을 나타냈습니다. 우리는 WearAuth가 다양한 사용 사례에서 제대로 작동하고 정교한 공격에 강력하다는 결론을 내렸습니다.
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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부
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
부
@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},}
부
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 -