Hussein, Omar2022-04-072022-04-0707/12/202110.1109/ICICIS52592.2021.9694249http://repository.msa.edu.eg/xmlui/handle/123456789/4906ScopusThis paper presents a proposed anti-spoofing third-factor authentication approach for Automated Teller Machines (ATMs). It is called Keypad Typing Rhythm Identifier (KTRID). The objective of this novel user-transparent transactions from spoofing attacks via identity theft. The main motivation to conduct this research is that in 2020 ATMs were the top compromised asset that was successfully attacked. ATM keypad typing rhythm refers to a user's unique keys hits practice that is difficult to mimic by spoofers. KTRID complements the authentication procedure currently used in ATMs in order to hinder spoofing attacks. It is based on exploiting users' unique typing rhythm behavior on the ATMs keypads. It boosts identity affirmation by exploiting the timing variances of keys hits to distinguish a legitimate bank customer from a spoofer. KTRID detects anomalies in the legitimate keypad typing rhythm outlier status of a smart card user. Such that, in case a smart card is stolen or lost, and the accompanying Personal Identification Number (PIN) is exposed or guessed, still the spoofer will not be able to carry out a successful ATM-based financial transaction. Through KTRID, the impersonator will be impinged by the unique typing rhythm behavior of the legitimate bank customer on the ATM keypad. The security evaluation demonstrated that through detecting outliers in a keypad typing rhythm, KTRID effectively prevented spoofing attacks. KTRID is a vital authentication approach, essentially for bank customers who cannot keep control of their smart cards and/or accompanying 4-digit PINs. To the best of the author's knowledge, this paper presents the first proposed approach to employ the typing rhythm behavioral-based biometrics for the purpose of securing ATM-based financial transactions. © 2021 IEEEen-USAutomated Teller MachinesBehavioral-Based BiometricsIdentity TheftKeypad Typing RhythmSpoofing AttacksArticle