A Proposed Approach to Secure Automated Teller Machine-Based Financial Transactions

dc.AffiliationOctober University for modern sciences and Arts (MSA)
dc.contributor.authorHussein, Omar
dc.date.accessioned2022-04-07T15:16:29Z
dc.date.available2022-04-07T15:16:29Z
dc.date.issued07/12/2021
dc.descriptionScopusen_US
dc.description.abstractThis 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_US
dc.identifier.other10.1109/ICICIS52592.2021.9694249
dc.identifier.urihttp://repository.msa.edu.eg/xmlui/handle/123456789/4906
dc.language.isoen_USen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofseriesProceedings - 2021 IEEE 10th International Conference on Intelligent Computing and Information Systems, ICICIS 2021Pages 236 - 2422021 10th IEEE International Conference on Intelligent Computing and Information Systems, ICICIS;Code 177003
dc.subjectAutomated Teller Machinesen_US
dc.subjectBehavioral-Based Biometricsen_US
dc.subjectIdentity Theften_US
dc.subjectKeypad Typing Rhythmen_US
dc.subjectSpoofing Attacksen_US
dc.titleA Proposed Approach to Secure Automated Teller Machine-Based Financial Transactionsen_US
dc.typeArticleen_US

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
avatar_scholar_256.png.jpg.jpg.jpg
Size:
1.75 KB
Format:
Joint Photographic Experts Group/JPEG File Interchange Format (JFIF)
Description:

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
51 B
Format:
Item-specific license agreed upon to submission
Description: