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

TitleType Me the Truth!: Detecting Deceitful Users via Keystroke Dynamics
Publication TypeConference Paper
Year of Publication2017
AuthorsMonaro, Merylin, Spolaor, Riccardo, Li, QianQian, Conti, Mauro, Gamberini, Luciano, Sartori, Giuseppe
Conference NameProceedings of the 12th International Conference on Availability, Reliability and Security
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-5257-4
Keywordscybersecurity, fake accounts, Human Behavior, human factors, keyboard interaction, keystroke analysis, keystroke dynamics, Lie detection, Metrics, pubcrawl
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.

URLhttps://dl.acm.org/citation.cfm?doid=3098954.3104047
DOI10.1145/3098954.3104047
Citation Keymonaro_type_2017