User identity verification via mouse dynamics

Feher, Clint; Elovici, Yuval; Moskovitch, Robert; Rokach, Lior; Schclar, Alon

doi:10.1016/j.ins.2012.02.066

Cited by 119 publications

(76 citation statements)

References 31 publications

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“…More recent approaches developed biometric identification systems based on user-pc interaction characteristics, such as keystroke dynamics and mouse dynamics [5,6].…”

Section: Introductionmentioning

confidence: 99%

How Human-Mouse Interaction can Accurately Detect Faked Responses About Identity

Monaro

Fugazza

Gamberini

et al. 2017

Symbiotic Interaction

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Abstract. Identity verification is nowadays a very sensible issue. In this paper, we proposed a new tool focused on human-mouse interaction to detect fake responses about identity. Experimental results showed that this technique is able to detect fake responses about identities with an accuracy higher than 95%. In addition to a high sensitivity, the described methodology exceeds the limits of the biometric measures currently available for identity verification and the constraints of the traditional lie detection cognitive paradigms. Thanks to the many advantages offered by this technique, its application looks promising especially in field of national and global security as anti-terrorist measure. This paper represents an advancement in the knowledge of symbiotic systems demonstrating that humanmachine interaction may be well integrated into security systems.

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“…More recent approaches developed biometric identification systems based on user-pc interaction characteristics, such as keystroke dynamics and mouse dynamics [5,6].…”

Section: Introductionmentioning

confidence: 99%

How Human-Mouse Interaction can Accurately Detect Faked Responses About Identity

Monaro

Fugazza

Gamberini

et al. 2017

Symbiotic Interaction

View full text Add to dashboard Cite

show abstract

“…Clint Feher et al [1] has introduced a novel method that continuously verifies users according to characteristics of their interaction with the mouse. The work has been done in three phases: first, event acquisition, second, feature extraction and finally user verification.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The work has been done in three phases: first, event acquisition, second, feature extraction and finally user verification. Clint Feher et al [1] has proposed algorithm which outperforms current state-ofthe-art methods by achieving higher verification accuracy while reducing the response time of the system. In this paper has stated that behavioral biometric techniques can be categorized based on different types of categories such as type of learning: implicit or explicit.…”

Section: Literature Reviewmentioning

confidence: 99%

“…al. [1] has given a general idea on how mouse based authentication methods work which will be explained in following sections.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Where t1 and tn denote the time points at which the left button down and left button up events took place, respectively [1]. The m t2 ; m t3 ; .…”

Section: Basic Mouse Actions (Level 1)mentioning

confidence: 99%

See 2 more Smart Citations

A Multimodal Behavioral Biometric Technique for User Identification using Mouse and Keystroke Dynamics

Motwani¹,

Jain²,

Sondhi³

2015

IJCA

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A novel multimodal behavioral biometric technique is implemented to authenticate/identify users by the way they interact with the input devices namely mouse and keyboard. It is also shown how behavioral biometrics is more efficient and secure than physiological biometric systems and moreover the most secured system is that which uses combination of both. This paper explains how the user will first be enrolled into the system. Sufficient number of samples will ensure the accuracy of the system. During verification, the user data will be first matched with that of the database and a probability module will decide over most probable user to be authenticated. The database matching process and simple probability calculation will ensure a time efficient system.

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Introducing touchstroke: keystroke‐based authentication system for smartphones

Kambourakis

Damopoulos

Papamartzivanos

et al. 2014

Security Comm Networks

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Keystroke dynamics is a well‐investigated behavioural biometric based on the way and rhythm in which someone interacts with a keyboard or keypad when typing characters. This paper explores the potential of this modality but for touchscreen‐equipped smartphones. The main research question posed is whether ‘touchstroking’ can be effective in building the biometric profile of a user, in terms of typing pattern, for future authentication. To reach this goal, we implemented a touchstroke system in the Android platform and executed different scenarios under disparate methodologies to estimate its effectiveness in authenticating the end‐user. Apart from typical classification features used in legacy keystroke systems, we introduce two novel ones, namely, speed and distance. From the experiments, it can be argued that touchstroke dynamics can be quite competitive, at least when compared to similar results obtained from keystroke evaluation studies. As far as we are aware of, this is the first time this newly arisen behavioural trait is put into focus. Copyright © 2014 John Wiley & Sons, Ltd.

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User identity verification via mouse dynamics

Cited by 119 publications

References 31 publications

How Human-Mouse Interaction can Accurately Detect Faked Responses About Identity

How Human-Mouse Interaction can Accurately Detect Faked Responses About Identity

A Multimodal Behavioral Biometric Technique for User Identification using Mouse and Keystroke Dynamics

Introducing touchstroke: keystroke‐based authentication system for smartphones

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