Biometric Authentication Using Mouse Gesture Dynamics

Sayed, Bassam; Traoré, Issa; Woungang, Isaac; Obaidat, Mohammad S.

doi:10.1109/jsyst.2012.2221932

Cited by 83 publications

(36 citation statements)

References 14 publications

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“…[28] provides a detailed description of biometrics in the context of mouse dynamics. Much of this work was modeled after one of the pioneering works in the field by [1].…”

Section: Mouse Trackingmentioning

confidence: 99%

“…Behavioral biometrics are unique to a person in how they act or think. Studies in this field include keystroke dynamics [3,12,17,20], mouse dynamics [1,16,23,24,28], voice recognition [7,32], signature verification [4,18,34], Graphical User Interface (GUI) pattern analysis [2] and touchscreen feature analysis [9,33]. Behavioral biometrics can not only be used for static verification at the beginning of a user's session, but can also be used dynamically to continuously authorize a user during a session.…”

Section: Introductionmentioning

confidence: 99%

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Biometric Authentication Using Mouseand Eye Movement Data

Rose

Liu

Awad

2017

JCSM

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Previous biometric systems have attempted to identify users solely by eye or mouse data. In this paper, we seek to find out if combining both kinds of data produces better results. In our system, mouse movement and eye movement data are gathered from each user simultaneously, a set of salient features are proposed, and a Neural Network classifier is trained on this data to uniquely identify users. After going through this process and investigating several Neural Network based classification models we conclude that combining the modalities results in a more accurate authentication decision and will become practical once the hardware is more widespread.

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“…[28] provides a detailed description of biometrics in the context of mouse dynamics. Much of this work was modeled after one of the pioneering works in the field by [1].…”

Section: Mouse Trackingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Biometric Authentication Using Mouseand Eye Movement Data

Rose

Liu

Awad

2017

JCSM

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“…Such a modular approach allows for coverage of a wide span of input methods and technologies starting with traditional mouse-based input and its enhancements with gesture dynamics [2], going through classic 2-DOF digitizers, tablets, and sign pads for 2D graphical input and their enhanced multiple-DOF versions capable to track the stylus azimuth, elevation, and applied forces [3]. We also cover current touch screen based input both for singleand multi-touch surfaces [4].…”

Section: Framework Building Blocks and Componentsmentioning

confidence: 99%

A human computer interactions framework for biometric user identification

Kanev

Maria

Bottoni

2016

Proc. 14th Int. Conf. On Global Research and Education, Inter-Academia 2015

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Computer assisted functionalities and services have saturated our world becoming such an integral part of our daily activities that we hardly notice them. In this study we are focusing on enhancements in Human-Computer Interaction (HCI) that can be achieved by natural user recognition embedded in the employed interaction models. Natural identification among humans is mostly based on biometric characteristics representing what-we-are (face, body outlook, voice, etc.) and how-we-behave (gait, gestures, posture, etc.) Following this observation, we investigate different approaches and methods for adapting existing biometric identification methods and technologies to the needs of evolving natural human computer interfaces.

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“…2) Biometrics that distinguishes: i) behavioral attributes (e.g., signature, keystroke dynamics, mouse gestures, and gait) [14]; ii) physical attributes such as fingerprint, iris and retina (e.g., see [15]), facial image and facial thermogram [16], geometrical features of the face (e.g., ear and nose), and geometrical features of the hand (incl. vein pattern) and feet; and iii) miscellaneous, such as audio-based (e.g., voice), chemical attributes (e.g., odor), and DNA.…”

Section: Introductionmentioning

confidence: 99%

Physiological Signals: The Next Generation Authentication and Identification Methods!?

Broek¹,

Spitters²

2013

2013 European Intelligence and Security Informatics Conference

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Abstract-Throughout the last 40 years, the security breach caused by human error is often disregarded. To relief the latter problem, this article introduces a new class of biometrics that is founded on processing physiological personal features, as opposed to physical and behavioral features. After an introduction on authentication, physiological signals are discussed, including their advantages, disadvantages, and initial directives for obtaining them. This new class of authentication methods can increase biometrics' robustness and enables cross validation. I close this article with a brief discussion in which a recap of the article is provided, law, privacy, and ethical issues are discussed, some suggestions for the processing pipeline of this new class of authentication methods are done, and conclusions are drawn.

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Biometric Authentication Using Mouse Gesture Dynamics

Cited by 83 publications

References 14 publications

Biometric Authentication Using Mouseand Eye Movement Data

Biometric Authentication Using Mouseand Eye Movement Data

A human computer interactions framework for biometric user identification

Physiological Signals: The Next Generation Authentication and Identification Methods!?

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