ATM WITH AN EYE FULL REPORT
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ATM WITH AN EYE


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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.


ATM SYSTEMS

Our ATM system would only attempt to match two (and later, a few) discrete images, searching through a large database of possible matching candidates would be unnecessary. The process would effectively become an exercise in pattern matching, which would not require a great deal of time. With appropriate lighting and robust learning software, slight variations could be accounted for in most cases. Further, a positive visual match would cause the live image to be stored in the database so that future transactions would have a broader base from which to compare if the original account image fails to provide a match – thereby decreasing false negatives.
When a match is made with the PIN but not the images, the bank could limit transactions in a manner agreed upon by the customer when the account was opened, and could store the image of the user for later examination by bank officials. In regards to bank employees gaining access to customer PINs for use in fraudulent transactions, this system would likewise reduce that threat to exposure to the low limit imposed by the bank and agreed to by the customer on visually unverifiable transactions.


HARDWARE AND SOFTWARE

ATMs contain secure cryptoprocessors, generally within an IBM PC compatible host computer in a secure enclosure. The security of the machine relies mostly on the integrity of the secure cryptoprocessor: the host software often runs on a commodity operating system.In-store ATMs typically connect directly to their ATM Transaction Processor via a modem over a dedicated telephone line, although the move towards Internet connections is under way.


RELIABILITY

ATMs are generally reliable, but if they do go wrong customers will be left without cash until the following morning or whenever they can get to the bank during opening hours. Of course, not all errors are to the detriment of customers; there have been cases of machines giving out money without debiting the account, or giving out higher value notes as a result of incorrect denomination of banknote being loaded in the money cassettes. Errors that can occur may be mechanical (such as card transport mechanisms; keypads; hard disk failures); software (such as operating system; device driver; application); communications; or purely down to operator error.

SECURITY

Early ATM security focused on making the ATMs invulnerable to physical attack; they were effectively safes with dispenser mechanisms. ATMs are placed not only near banks, but also in locations such as malls, grocery stores, and restaurants. The other side of this improvement is the enhancement of the culprit’s probability to get his ‘unauthentic’ share.
ATMs are a quick and convenient way to get cash. They are also public and visible, so it pays to be careful when you're making transactions. Follow these general tips for your personal safety.


FACIAL RECOGNITION


The main issues faced in developing such a model are keeping the time elapsed in the verification process to a negligible amount, allowing for an appropriate level of variation in a customer’s face when compared to the database image, and that credit cards which can be used at ATMs to withdraw funds are generally issued by institutions that do not have in-person contact with the customer, and hence no opportunity to acquire a photo.
Because the system would only attempt to match two (and later, a few) discrete images, searching through a large database of possible matching candidates would be unnecessary. The process would effectively become an exercise in pattern matching, which would not require a great deal of time. With appropriate lighting and robust learning software, slight variations could be accounted for in most cases. Further, a positive visual match would cause the live image to be stored in the database so that future transactions would have a broader base from which to compare if the original account image fails to provide a match – thereby decreasing false negatives.



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To get information about an atm with an eye refer the links below



http://studentbank.in/report-atm-with-an...ull-report

http://studentbank.in/report-atm-with-an-eye

http://studentbank.in/report-an-atm-with...base-paper
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