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Transcript

  • 1. Biometrics
  • 2. Signatures
    • How secure are handwritten signatures?
    • The probability that a forged signature will be accepted as genuine mainly depends on the amount of care taken when examining it.
  • 3. Verification by observation
    • Problem : High error rates.
  • 4. Automated verification of signature
    • Use of machine to verify signature in Banks for cheque-processing.
    • e.g. MICR
    • Problem : Error Rate
  • 5. Why?
    • Something You Know – Password ,Code
    • Something You Have – Swipe Card, Token
    • Something You are – A Biometric
  • 6. Definition
    • Automatic methods for identifying a person on the basis of some biological or behavioural characteristics of the person.
    • To identify, confirmation and security techniques that rely on measurable, individual biological characteristics.
  • 7.
    • Biometrics identify people by measuring some aspect of individual anatomy or physiology (such as your hand geometry or fingerprint), some deeply ingrained skill, or other behavioral characteristic (such as your handwritten signature), or something That is a combination of the two (such as your voice).
  • 8. Examples
    • Facial image
    • Fingerprints
    • Handprints
    • Voice pattern
    • Iris / Retina
    • Signature
  • 9. Finger Prints
  • 10. Hand Prints
  • 11. Voice Pattern
  • 12. Facial Image
  • 13.  
  • 14. Iris / Retina
  • 15. Signature
  • 16.  
  • 17. Advantages
    • Can not be lost or stolen or copied.
    • Can not be forgotten or guessed by others.
    • Very distinctive to each individual
  • 18.
    • Biometrics are like many other protection mechanisms (alarms, seals, tampersensing enclosures, ...) in that environmental conditions can cause havoc. Noise, dirt, vibration, and unreliable lighting conditions all take their toll.
    • Some systems, like speaker recognition, are vulnerable to alcohol intake and stress. Changes in environmental assumptions, such as from closed to open systems, from small systems to large
    • ones, from attended to standalone, from cooperative to recalcitrant subjects can all undermine a system’s viability.
  • 19. Every technique has some Limits
    • Facial image
    • Fingerprints
    • Handprints
    • Voice pattern
    • Iris / Retina
    • Signature
  • 20.  
  • 21. The Design
    • Identification in the form of verification or recognition.
    • Verification – authenticates a person’s claimed identity by comparing.
    • Recognition – system determines the identity of a given person from a database of persons known to it.
  • 22. System Performance
    • True Accept – Genuine individual is accepted.
    • True Reject – Imposter is rejected.
    • False Accept – Imposter is accepted.
    • False Reject - Genuine individual is rejected.
  • 23.  
  • 24. The Function
    • An ideal biometric characteristic should be Universal, Unique, Permanent and Collectable
    • Performance - Accuracy, Speed, and Cost.
    • Acceptability and Circumvention .
  • 25. Current Techniques Physical and Behavioural
    • Facial Features
    • Fingerprints
    • Hand Geometry
    • Eye, Retina and Iris Mapping
    • Signatures
    • Voice Pattern
    • Key Stroke Dynamics
  • 26. Distribution
  • 27. New Techniques
    • Ear Mapping
    • Body Odour Identification
    • Body Salinity Identification
    • EEG Fingerprint
    • Deoxyribonucleic Acid
    • Verichip
  • 28. New Dimensions
    • Research in New representations, Matching Algorithms, Database Indexing, Fusion of Biometric Modalities, Live ness Detection, Template Protection, Error Rate Estimation.
    • System Testing and Evaluation of Large Database
    • Government regulations
    • Making it Foolproof ?
    • Cost / Benefit Analysis – Quantifying Deterrence
  • 29. Issues
    • Application
    • Privacy + & -
    • Legal
    • Cost
  • 30.
    • Fingerprint recognition as a requirement for ignition of the engine. Jaguar
    • Fingerprint scanner to verify season pass holders. Disney
    • Hand Geometry for immigration. US Immigration and Naturalization services
    • Iris scanner for issue of Rifles to Olympic participants. Winter Olympics Nagano
    • Signature verification. For claiming benefits. British Employment Services
    • Signature identification for correct distribution of food . Pentonville Prison , England
    • Voice Identification to protect computer facilities .
  • 31. Summary
    • Biometric measures of one kind or another have been used to identify people since ancient times, with handwritten signatures, facial features, and fingerprints being the traditional methods.
    • Systems have been built that automate the task of recognition, using these methods and newer ones, such as hand geometry, voiceprints, and iris patterns.
  • 32.
    • These systems have different strengths and weaknesses. In automatic operation, most have error rates of the order of 1% (though iris recognition is better, hand geometry slightly better, and face recognition worse).
    • There is always a trade-off between the false accept rate (the fraud rate) and the false reject rate (the insult rate). The statistics of error rates are deceptively difficult.
  • 33.
    • If any biometric becomes very widely used, there is increased risk of forgery in unattended operation: voice synthesizers, photographs of irises, fingerprint molds, and even good old-fashioned forged signatures must all be thought of in system design.
    • These do not rule out the use of biometrics, as traditional methods such as handwritten signatures are usable in practice despite very high error rates.
  • 34.
    • Biometrics are usually more powerful in attended operation, where, with good system design, the relative strengths and weaknesses of the human guard and the machine recognition system may complement one another.
    • Finally, many biometric systems achieve most or all of their result by deterring criminals rather than being effective at identifying them.