Preventing identity theft using biometrics based authentication system

Lamjed Zahrouni, Dayton Blackwood, Syed Rizvi, Joseph Gualdoni, Muder Almiani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Identity Theft is a growing problem in this modern world due to the continued reliance on computers and technology. It continues to grow everyday as technology advances. The best way to stop Identity Theft is for the users to be aware of dangerous activities that can increase their chances of having their identity stolen. Today, most identity theft protection businesses simply offer identity prevention programs as security measure. However, such preventive measures do not help stop the problem since they usually act after the Identity is stolen and an attempt of using it happened. In this paper we are offering an Identity theft protection system based on the use of the biometric Identifications of the users. Banks and credit card companies could use the proposed protection system. Our primary research goal is to create a software which could also be used as an app for a user's mobile devices that acts as an additional 'door' to the bank accounts, this will allow users to control how much money can be spent at one time, where it can be spent, and even what stores it can be spent at. To show the practicality of our proposed scheme, we present a case study that covers multiple threat scenarios, attackers' goals and motives, and our security defense.

Original languageEnglish (US)
Title of host publication2017 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies, AEECT 2017
EditorsIbrahim Al-Oqily
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781509059690
DOIs
StatePublished - Jul 1 2017
Event2017 IEEE Smart Grid Conference, SGC 2017 - Tehran, Iran, Islamic Republic of
Duration: Dec 20 2017Dec 21 2017

Publication series

Name2017 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies, AEECT 2017
Volume2018-January

Other

Other2017 IEEE Smart Grid Conference, SGC 2017
CountryIran, Islamic Republic of
CityTehran
Period12/20/1712/21/17

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All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Instrumentation
  • Computer Networks and Communications
  • Computer Science Applications

Cite this

Zahrouni, L., Blackwood, D., Rizvi, S., Gualdoni, J., & Almiani, M. (2017). Preventing identity theft using biometrics based authentication system. In I. Al-Oqily (Ed.), 2017 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies, AEECT 2017 (pp. 1-6). (2017 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies, AEECT 2017; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AEECT.2017.8257767