atm with an eye

[seminar class]

Presented by:
OWAIS NOOR TRUMBOO

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INTRODUCTION
 ATM made money transaction easy.
 Other side is enhancement of culprit’s action to get unauthentic access.
 Improved Technology is used.
 Facial Recognition is recent technology used at ATMs.
ATM with facial Recognition Mechanism
History of an ATM
 Many inventors contribute to the invention.
 Don Wetzel invented first successful and modern ATM.
 But Luther GEORGE started patenting earlier in 1939.
 A working prototype was ready in 1969 & was installed in New York.
Don Wetzel's ATM
 He got the idea while waiting in line at Dallas Bank.
 It was not in a lobby.
 It was actually in the wall of the Bank.
 Had a canopy over IT for protection.
 ATM was cash dispenser only.
 First ATM’s were off-line machines.
What is an ATM
 A Banking Terminal that accepts deposits & dispenses cash.
 It has two input devices viz ;
1. A card reader that reads magnetic strip.
2. A keypad.
 It has four output devices viz ;
1. A speaker.
2. A display screen.
3. A printer.
4. A safe & cash dispensing mechanism.
Atm machine
ATM
 Networking
ATMs are connected to interbank network enabling people to withdraw and deposit money from machines not belonging to the bank where they have their account.
 Hardware
ATMs contain secure cryptoprocessors, generally within an IBM PC compatible host computer in a secure enclosure.
 Software
ATMs are moving away from custom circuit boards and into full-fledged with commodity operating systems such as Windows 2000 and Linux .
 Reliability
ATMs are generally reliable, but if they do go wrong customers will be left without cash or giving out higher value notes.
ATM Frauds
These had two common forms.
1. In the low-tech form, the user's PIN is observed by someone watching as they use the machine.
2. By contrast, the most common high-tech modus operandi involves the installation of a magnetic card reader over the real ATM's card slot, and the use of a wireless surveillance camera to observe the user's PIN.
ATM’s in Operation
Need of Facial Recognition at ATM
 Traditionally, card & PIN is used to access account.
 ATM frauds are increasing.
 By forcing ATM to match live image with an image stored in a bank database, frauds can be minimized.
 Only when PIN & image matches, user is considered fully verified.
Where Facial Recognition Technology is used
 Used mainly in Law Enforcement Agencies & Security Surveillance.
 Also has several other uses :
1. Eliminating voter fraud.
2. Check-Cashing identity verification.
3. Computer security.
 Also used to pinpoint the face in the crowd & measure its features.
Computer Security
 Facial Recognition software can be used to lock your computer.
Used to pinpoint faces in crowd
 Facial Recognition mechanism is also used to pinpoint a face in the crowd & measure its features.
Working
 Facial Recognition analyzes Characteristics of face through digital camera.
 There are peaks & valleys on face called nodal points.
 There are around 80 nodal points on face.
 Some of them are :
1. Distance between eyes.
2. Width of nose.
3. Depth of eye sockets.
4. Cheekbones.
5. Jaw line.
6. Chin.
 These nodal points are measured to create a numerical code that represents face in database.
 This code is called face-print.
 These measurements are then used for comparison when user stands before camera.
 Does not require physical contact with image capturing device.
Identification Steps
 Take a photo of the individual & encode it.
 Match the encoding against database.
 Display the result (i.e. verified or not-verified).
Verification
Advantages
 Frauds are minimized.
 It does not require any physical contact with image capture device.
 Does not require any advance hardware.
 Convenient to use because additional security information (smart cards, pwd. etc) can be skipped.
 Usually helps in situation where certain biometric feature is not optimal. e.g. hard workers may have raw finger prints.
Disadvantages
 Face is not so unique, so its recognition reliability is slightly lower.
 To match with the database image, it requires lot of time.
Conclusion
 As ATM frauds are increasing, or the culprit’s probability to get the ‘unauthentic access’ is increasing, additional security like Facial Recognition mechanism is necessity.