25-09-2013, 02:30 PM
Improving ATM Security via Facial Recognition
Security via Facial Recognition.ppt (Size: 617 KB / Downloads: 99)
Proposal
Cameras in use at automatic teller machines should take still images of users
A facial recognition scheme should be added to the software used to verify users at ATMs
This scheme should match a picture of the user at the ATM with a picture of the account holder in the bank’s database
Reasoning
ATM fraud costs U.S. banks an average of $15,000 each year… hundreds of millions in total
This cost is borne by bank customers
Current ATM validation schemes are limited to access cards and PINs
Card theft, PIN theft and cracking, stealing of account information by bank employees all contribute to fraud schemes
Algorithm
Take customer’s picture(s) when account is opened and allow user to set non-verified transaction limits
At ATM, use access card and PIN to pre-verify user
Take user’s picture, attempt to match it to database image(s)
If match is successful, allow transaction
If match is unsuccessful, limit available transactions
Is Facial Recognition Reliable?
Matching a user image with any image in a database… facial evaluation… is still problematic – digital airport screenings, public surveillance cameras, etc. have high error rates
But this isn’t a problem here!
We must only match a user image with one known image from a database… facial verification… this technique has low error rates under good conditions (3% - 10%)
Summary
Access card / PIN provides insufficient ATM security
Adding facial verification to the process can greatly decrease fraudulent transactions
Current ATMs have the power to perform verification locally given a software change
I will create a simulated system using a custom ATM black box and an open-source LFA recognition program