19-08-2014, 11:46 AM
AN ATM WITH AN EYE SEMINAR REPORT
AN ATM WITH AN EYE.pdf (Size: 20.35 KB / Downloads: 9)
ABSTRACT
There is an urgent need for improving security in banking region. With the advent of
ATM though banking became a lot easier it even became a lot vulnerable. The
chances of misuse of this much hyped ‘insecure’ baby product (ATM) are manifold
due to the exponential growth of ‘intelligent’ criminals day by day. ATM systems
today use no more than an access card and PIN for identity verification. This
situation is unfortunate since tremendous progress has been made in biometric
identification techniques, including finger printing, retina scanning, and facial
recognition. This paper proposes the development of a system that integrates facial
recognition technology into the identity verification process used in ATMs. The
development of such a system would serve to protect consumers and financial
institutions alike from fraud and other breaches of securit
INTRODUCTION
The rise of technology in India has brought into force many types of equipment
that aim at more customer satisfaction. ATM is one such machine which made
money transactions easy for customers to bank. The other side of this improvement
is the enhancement of the culprit’s probability to get his ‘unauthentic’ share.
Traditionally, security is handled by requiring the combination of a physical access
card and a PIN or other password in order to access a customer’s account. This
model invites fraudulent attempts through stolen cards, badly-chosen or
automatically assigned PINs, cards with little or no encryption schemes, employees
with access to non-encrypted customer account information and other points of
failure.
Our paper proposes an automatic teller machine security model that would
combine a physical access card, a PIN, and electronic facial recognition. By forcing
the ATM to match a live image of a customer’s face with an image stored in a bank
. LITERATURE REVIEW
For most of the past ten years, the majority of ATMs used worldwide ran under
IBM’s now-defunct OS/2. However, IBM hasn’t issued a major update to the
operating system in over six years. Movement in the banking world is now going in two directions: Windows and Linux. NCR, a leading world-wide ATM manufacturer,
recently announced an agreement to use Windows XP Embedded in its next
generation of personalized ATMs (crmdaily.com.) Windows XP Embedded allows
OEMs to pick and choose from the thousands of components that make up Windows
XP Professional, including integrated multimedia, networking and database
management functionality. This makes the use of off-the-shelf facial recognition
code more desirable because it could easily be compiled for the Windows XP
environment and the networking and database tools will already be in place.
For less powerful ATMs, KAL, a software development company based in
Scotland, provides Kalignite CE, which is a modification of the Windows CE platform.
This allows developers that target older machines to more easily develop complex
user-interaction systems . Many financial institutions are relying on a third choice,
Windows NT, because of its stability and maturity as a platform.
On an alternative front, the largest bank in the south of Brazil, Banrisul, has
installed a custom version of Linux in its set of two thousand ATMs, replacing legacy
MS-DOS systems. The ATMs send database requests to bank servers which do the
bulk of transaction processing (linux.org.) This model would also work well for the
proposed system if the ATMs processors were not powerful enough to quickly
perform the facial recognition algorithms
OUR METHODOLOGY
The first and most important step of this project will be to locate a powerful
open-source facial recognition program that uses local feature analysis and that is
targeted at facial verification. This program should be compilable on multiple
systems, including Linux and Windows variants, and should be customizable to the
extent of allowing for variations in processing power of the machines onto which it
would be deployed.
We will then need to familiarize ourselves with the internal workings of the
program so that we can learn its strengths and limitations. Simple testing of this
program will also need to occur so that we could evaluate its effectiveness. Several
sample images will be taken of several individuals to be used as test cases – one
each for “account” images, and several each for “live” images, each of which would
vary pose, lighting conditions, and expressions.
Once a final program is chosen, we will develop a simple ATM black box
program. This program will server as the theoretical ATM with which the facial
recognition software will interact. It will take in a name and password, and then
look in a folder for an image that is associated with that name. It will then take in an
image from a separate folder of “live” images and use the facial recognition program
to generate a match level between the two. Finally it will use the match level to
decide whether or not to allow “access”, at which point it will terminate. All of this
will be necessary, of course, because we will not have access to an actual ATM or its
software
CONCLUSION
We thus develop an ATM model that is more reliable in providing security by using
facial recognition software. By keeping the time elapsed in the verification process
to a negligible amount we even try to maintain the efficiency of this ATM system to a
greater degree.