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Fengyan Han

dblp:86/10208 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
0000-0001-5761-2524ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
1 paper
Authentication and access control · 100%
Human-computer interaction and pervasive computing
1 paper
Interaction techniques and input · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Authentication and access control › mobile authentication
smartphone authentication
0.712023
Squeez'In: Private Authentication on Smartphones based on Squeezing Gestures · CHI 2023
Authentication and access control
privacy-preserving authentication
0.212023
Squeez'In: Private Authentication on Smartphones based on Squeezing Gestures · CHI 2023

Methods — techniques the papers use, named apart from their topics

user study · 1.3gesture recognition · 1.3SVM · 1.3GBDT · 1.3
YearPublicationVenuePosition
2023 Squeez'In: Private Authentication on Smartphones based on Squeezing Gestures
abstract
In this paper, we proposed Squeez’In, a technique on smartphones that enabled private authentication by holding and squeezing the phone with a unique pattern. We first explored the design space of practical squeezing gestures for authentication by analyzing the participants’ self-designed gestures and squeezing behavior. Results showed that varying-length gestures with two levels of touch pressure and duration were the most natural and unambiguous. We then implemented Squeez’In on an off-the-shelf capacitive sensing smartphone, and employed an SVM-GBDT model for recognizing gestures and user-specific behavioral patterns, achieving 99.3% accuracy and 0.93 F1-score when tested on 21 users. A following 14-day study validated the memorability and long-term stability of Squeez’In. During usability evaluation, compared with gesture and pin code, Squeez’In achieved significantly faster authentication speed and higher user preference in terms of privacy and security.
Xin Yi 0001, Louisa Shi, Fengyan Han, Yan Kong, Hewu Li, Yuanchun Shi
CHI5