scispace - formally typeset
Open AccessPosted Content

TouchIn: Sightless Two-factor Authentication on Multi-touch Mobile Devices

TLDR
This paper focuses on designing, implementing, and evaluating TouchIn, a two-factor authentication system on multi-touch mobile devices that allows the user to draw on arbitrary regions on the touchscreen without looking at it.
Abstract
Mobile authentication is indispensable for preventing unauthorized access to multi-touch mobile devices. Existing mobile authentication techniques are often cumbersome to use and also vulnerable to shoulder-surfing and smudge attacks. This paper focuses on designing, implementing, and evaluating TouchIn, a two-factor authentication system on multi-touch mobile devices. TouchIn works by letting a user draw on the touchscreen with one or multiple fingers to unlock his mobile device, and the user is authenticated based on the geometric properties of his drawn curves as well as his behavioral and physiological characteristics. TouchIn allows the user to draw on arbitrary regions on the touchscreen without looking at it. This nice sightless feature makes TouchIn very easy to use and also robust to shoulder-surfing and smudge attacks. Comprehensive experiments on Android devices confirm the high security and usability of TouchIn.

read more

Citations
More filters
Journal ArticleDOI

Surveying the Development of Biometric User Authentication on Mobile Phones

TL;DR: This paper surveys the development of existing biometric authentication techniques on mobile phones, particularly on touch-enabled devices, with reference to 11 biometric approaches and proposes a framework for establishing a reliable authentication mechanism through implementing a multimodal biometric user authentication in an appropriate way.
Proceedings Article

Towards Continuous and Passive Authentication via Touch Biometrics: An Experimental Study on Smartphones

TL;DR: This work adopts a continuous and passive authentication mechanism based on a user’s touch operations on the touchscreen that is suitable for smartphones, as it requires no extra hardware or intrusive user interface.
Journal ArticleDOI

Multi-factor authentication: A survey

TL;DR: The already available and emerging sensors (factor providers) that allow for authenticating a user with the system directly or by involving the cloud are surveyed and a framework for qualifying the missing factors by authenticating the user without disclosing sensitive biometric data to the verification entity is proposed.
Proceedings ArticleDOI

Hold and Sign: A Novel Behavioral Biometrics for Smartphone User Authentication

TL;DR: A new, bi-modal behavioral biometric solution for user authentication that takes into account micro-movements of a phone and movements of the user's finger during writing or signing on the touchscreen.
Journal ArticleDOI

Draw-a-pin

TL;DR: Draw-A-PIN could offer better security by utilizing drawing traits or behavioral biometrics as an additional authentication factor beyond just the secrecy of the PIN.
References
More filters
Book

Convex Optimization

TL;DR: In this article, the focus is on recognizing convex optimization problems and then finding the most appropriate technique for solving them, and a comprehensive introduction to the subject is given. But the focus of this book is not on the optimization problem itself, but on the problem of finding the appropriate technique to solve it.
Journal ArticleDOI

Dynamic programming algorithm optimization for spoken word recognition

TL;DR: This paper reports on an optimum dynamic progxamming (DP) based time-normalization algorithm for spoken word recognition, in which the warping function slope is restricted so as to improve discrimination between words in different categories.
Proceedings ArticleDOI

uWave: Accelerometer-based personalized gesture recognition and its applications

TL;DR: This work evaluates uWave using a large gesture library with over 4000 samples collected from eight users over an elongated period of time for a gesture vocabulary with eight gesture patterns identified by a Nokia research and shows that uWave achieves 98.6% accuracy, competitive with statistical methods that require significantly more training samples.

Smudge attacks on smartphone touch screens

TL;DR: This paper examines the feasibility of smudge attacks on touch screens for smartphones, and focuses on the Android password pattern, and provides a preliminary analysis of applying the information learned in a smudge attack to guessing an Android passwordpattern.
Proceedings ArticleDOI

Touch me once and i know it's you!: implicit authentication based on touch screen patterns

TL;DR: In this article, an implicit authentication approach that enhances password patterns with an additional security layer, transparent to the user, is introduced, where users are not only authenticated by the shape they input but also by the way they perform the input.
Related Papers (5)