research-article

Type Me the Truth!: Detecting Deceitful Users via Keystroke Dynamics

Authors:

Merylin Monaro,

Riccardo Spolaor,

Luciano Gamberini,

Giuseppe SartoriAuthors Info & Claims

ARES '17: Proceedings of the 12th International Conference on Availability, Reliability and Security

Article No.: 60, Pages 1 - 6

https://doi.org/10.1145/3098954.3104047

Published: 29 August 2017 Publication History

Abstract

In this paper, we propose a novel method, based on keystroke dynamics, to distinguish between fake and truthful personal information written via a computer keyboard. Our method does not need any prior knowledge about the user who is providing data. To our knowledge, this is the first work that associates the typing human behavior with the production of lies regarding personal information. Via experimental analysis involving 190 subjects, we assess that this method is able to distinguish between truth and lies on specific types of autobiographical information, with an accuracy higher than 75%. Specifically, for information usually required in online registration forms (e.g., name, surname and email), the typing behavior diverged significantly between truthful or untruthful answers. According to our results, keystroke analysis could have a great potential in detecting the veracity of self-declared information, and it could be applied to a large number of practical scenarios requiring users to input personal data remotely via keyboard.

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Cited By

Sim KFortuno KChoo K(2024)Towards Understanding Emotions for Engaged Mental Health ConversationsCompanion Publication of the 2024 ACM Designing Interactive Systems Conference10.1145/3656156.3663694(176-180)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1145/3656156.3663694
Kuruvilla ADaley RKumar R(2024)Spotting Fake Profiles in Social Networks via Keystroke Dynamics2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)10.1109/CCNC51664.2024.10454821(525-533)Online publication date: 6-Jan-2024
https://doi.org/10.1109/CCNC51664.2024.10454821
Fernandes SUllah M(2022)A Comprehensive Review on Features Extraction and Features Matching Techniques for Deception DetectionIEEE Access10.1109/ACCESS.2022.315782110(28233-28246)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3157821
Show More Cited By

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cover image ACM Other conferences

ARES '17: Proceedings of the 12th International Conference on Availability, Reliability and Security

August 2017

853 pages

ISBN:9781450352574

DOI:10.1145/3098954

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 29 August 2017

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ARES '17

ARES '17: International Conference on Availability, Reliability and Security

August 29 - September 1, 2017

Reggio Calabria, Italy

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ARES '17 Paper Acceptance Rate 100 of 191 submissions, 52%;

Overall Acceptance Rate 228 of 451 submissions, 51%

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Cited By

Sim KFortuno KChoo K(2024)Towards Understanding Emotions for Engaged Mental Health ConversationsCompanion Publication of the 2024 ACM Designing Interactive Systems Conference10.1145/3656156.3663694(176-180)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1145/3656156.3663694
Kuruvilla ADaley RKumar R(2024)Spotting Fake Profiles in Social Networks via Keystroke Dynamics2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)10.1109/CCNC51664.2024.10454821(525-533)Online publication date: 6-Jan-2024
https://doi.org/10.1109/CCNC51664.2024.10454821
Fernandes SUllah M(2022)A Comprehensive Review on Features Extraction and Features Matching Techniques for Deception DetectionIEEE Access10.1109/ACCESS.2022.315782110(28233-28246)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3157821
Monaro MMaldera SScarpazza CSartori GNavarin N(2022)Detecting deception through facial expressions in a dataset of videotaped interviewsComputers in Human Behavior10.1016/j.chb.2021.107063127:COnline publication date: 9-Apr-2022
https://dl.acm.org/doi/10.1016/j.chb.2021.107063
Cardaioli MMonaro MSartori GConti M(2020)Detecting Identity Deception in Online Context: A Practical Approach Based on Keystroke DynamicsAdvances in Human Factors in Cybersecurity10.1007/978-3-030-52581-1_6(41-48)Online publication date: 4-Jul-2020
https://doi.org/10.1007/978-3-030-52581-1_6
Monaro MCapuozzo PRagucci FMaffei ACurci AScarpazza CAngrilli ASartori G(2020)Using Blink Rate to Detect Deception: A Study to Validate an Automatic Blink Detector and a New Dataset of Videos from Liars and Truth-TellersHuman-Computer Interaction. Human Values and Quality of Life10.1007/978-3-030-49065-2_35(494-509)Online publication date: 19-Jul-2020
https://dl.acm.org/doi/10.1007/978-3-030-49065-2_35
Tomas FTsimperidis IDemarchi SEl Massioui F(2020)Keyboard dynamics discrepancies between baseline and deceptive eyewitness narrativesApplied Cognitive Psychology10.1002/acp.374335:1(112-122)Online publication date: 8-Oct-2020
https://doi.org/10.1002/acp.3743
Mhenni AMigdal DCherrier ERosenberger CEssoukri Ben Amara N(2019)Vulnerability of Adaptive Strategies of Keystroke Dynamics Based Authentication Against Different Attack Types2019 International Conference on Cyberworlds (CW)10.1109/CW.2019.00052(274-278)Online publication date: Oct-2019
https://doi.org/10.1109/CW.2019.00052
Monaro MGamberini LSartori G(2018)Spotting faked identities via mouse dynamics using complex questionsProceedings of the 32nd International BCS Human Computer Interaction Conference10.14236/ewic/HCI2018.8(1-9)Online publication date: 4-Jul-2018
https://dl.acm.org/doi/10.14236/ewic/HCI2018.8
Monaro MBusinaro MSpolaor RLi QConti MGamberini LSartori G(2018)The Online Identity Detection via Keyboard DynamicsProceedings of the Future Technologies Conference (FTC) 201810.1007/978-3-030-02683-7_24(342-357)Online publication date: 20-Oct-2018
https://doi.org/10.1007/978-3-030-02683-7_24

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