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India's UID Project: Biometrics Vulnerabilities & Exploits
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India's UID Project: Biometrics Vulnerabilities & Exploits

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Presentation of JTD in Camaign for No UID meeting in Delhi 25th August

Presentation of JTD in Camaign for No UID meeting in Delhi 25th August

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  • 1. Biometrics Vulnerabilities & Exploits [email_address]
  • 2. INTRODUCTION
    • Old World methods of trust and authentication
      • Personal introductions, documents
      • Key role player is the authenticator
    • New World requirements
      • Annonymous, large scale, short term relationships
      • Key requirement is building up of trust
    • No defence mechanisms of older methods present in newer systems
  • 3. Authentication by Technology
    • Requires the exchange of certain FACTORS
    • Requires an authority who can verify these factors
    • Requires an authority who can provide permission to build a relationship and transact
  • 4. ...Authentication by Technology
    • Factors are classified into 3 types
    • Ownership factor like cards, badges or keys
    • Knowledge factor like user id, password and pins
    • Inheritance factor like weight, height, face shape, color of eyes/hair, birth marks etc. all nicely encoded in a photo
  • 5. Properties of different Factors
  • 6. The Inheritance Factor - Biometrics
    • The Subject of discussion for today is the Inheritance Factor – Biometrics
    • Implementation difficulties
    • Vulnerabilities
    • The authentication process and it's vulnerabilities, in brief
    • Since the UIDAI has choosen the use of finger prints and iris as a means of authentication, we will be discussing only these factors
  • 7. Finger Print Scanners
    • Many variations on these basic techniques
    • Variations are primarily to reduce cost, size and probably to overcome existing patents
    • Some claims exist about the ability to sense below the “dead skin” surface. However for our vulnerability assements, these claims are trivially overcome
    • Sensor technologies are not relevant to the scope of vulnerabilites and exploits
  • 8. Fingerprint Readers
  • 9. Iris Scanners
    • Iris scanners use a Near Infra Red light
    • Camera coupled with some autofocusing techniques (commonly used in autofocus cameras)
  • 10. Iris scan - Base Technique
  • 11. The Process
    • All id systems involve an enrollment process and an authentication process, followed by an authorization process, to enter / exit / recieve / depoist etc
  • 12. The Enrollement Process
    • Capture image
    • Process image
    • Extract Features
    • Create Template
    • Save raw data in the case of criminal records
    • Encryption
    • Transmission
    • De duplication and storage
  • 13. The Authentication process
    • Capture image
    • Process image
    • Extract Features
    • Create Template
    • Encryption
    • Transmission
    • Receive result
    • UIDAI has not specified iris for authentication*
  • 14. Threats faced by biometric systems
    • Threat agents
      • Only simple impostor, without much sophistication or resources. We shall leave out crossborder attack vectors, as pilfering state subsidies may not be their highest priority
    • Threat Vectors
      • Fake credentials and replay attacks
    • System Weaknesses
      • Extraction of digital keys, use of internal facilities of sensors
  • 15. Desired Characteristics And Limitations
    • Easy and accurate Digitization of the presented bio characteristic
    • Time Invariant
    • Environment Invariant
    • Spoof proof
  • 16. ... Limitations in enrollment / auth
    • Easy and accurate Digitization – neither easy nor accurate
    • Too many wrong methods, results in unreproduceable template
    • Guided enrollment useless for auth
    • Very difficult for occasional users
    • Manual overides = more holes
  • 17. ... Limitations in enrollment / auth
    • Time invariance – a myth
      • Ageing changes fingerprints (1)
      • Skin ailments makes auth difficult if not impossible
      • No large scale studies on heterogenous populations
      • Will require frequent re-enrollment – aka more holes
      • No (available?) studies on iris variations due to ageing
      • Errors due to unknown causes (2)
  • 18. ... Limitations in enrollment / auth
    • Environment invariance – a myth
      • Water logged hands changes fingerprints machine readbility
      • Dry skin changes fingerprints machine readbility
      • Will require frequent re-enrollment – aka more holes
      • No (available?) studies on iris variations due to harsh environments
      • Inter device variations
  • 19. ... Limitations in enrollment / auth
    • Non- Spoofability
      • Biometrics are the worst
      • Fingeprints are spoofed by gummy finger techniqe
      • Iris are spoofed by photographs
      • Iris are spoofed by patterned contacts
  • 20. Spoofing made easy - Fingerprints
    • Uses common ingredients
    • Fools all systems with greater than 60% repeatability
    • Newer mateials and techniques even more effective
  • 21. Spoofing made easy - Iris
    • Buy from the net to create fake ids for sale
    • PCB etching techniues for masqureading
    • Older technique using high res photograph with pupil holes
  • 22. Attack Vectors requiring skill
    • Template reconstruction
      • Biometric id systems store data as a templates, usually a few kilobytes in size. It has been shown that a biometric fingerprint system can be compromised by recreating the biometric using the stored template
      • Template extraction and storage a feature of systems
  • 23. ... Attack Vectors requiring skill
    • Key duplication
      • Trivial to break into the device and extract keys
      • Addition deletion of keys a feature
      • Even in locked down devices, the key can be recovered by simply copying the onboard flash to a pc and reusing the backup in a device purchased from the market
  • 24. ... Attack Vectors requiring skill
    • Replay attack at sensor pins
      • The sensor interfaces are relatively simple
      • Produce raw data (Fig 4). It is possible to record all data, and then replay that data
      • This attack requires some technical skill
      • However once developed it can be mass produced and will be undetectable
  • 25. Biometrics WORST CHARACTERISTIC
    • Cannot be withdrawn
    • Cannot be changed
    • This violates the basic requirement of any id system
  • 26. Inherent problems with Biometric Systems
    • FAR - False Acceptance Rate indicates the number of wrong matches of a presented biometric – mistakenly identyfying one person as another
    • FRR - False Rejection Rate (also called False Non Match Rate) indicates the number of wrong rejects of a presented biometric.
    • Best FAR of .00060 for fingerprints
    • Best FAR of .000120 for Iris
    • Best FRR of .0060 for fingerprints
    • Best FRR of .0012 for Iris
  • 27. ... Inherent problems with Biometric Systems
    • FAR and FRR closely linked to template size
    • Reducing FAR increase FRR
    • Reducing FRR increases FAR
  • 28. ... Inherent problems with Biometric Systems
    • Requires very good power
    • Requires very good telecommunications infrastructure
    • Both of very poor quality in many areas
    • Even in Maharshtra in the Konkan region, such infratructure is poor due to natural causes
      • Hilly terrain
      • RF shadow regions
      • Heavy rains and lightning
  • 29. Summary
    • Biometrics as a unique id in an automated system has never been tested on a large scale
    • The inherent characteristic of biometrics is it's irrevocability. This is in direct contradiction of any id / security system, where keys must be revocable and reissueable
    • Fingerprints are easily spoofable
    • Iris patterns are easily spoofable
    • Biometrics are very susceptible to the natural biological processes of growth, ageing and environment
    • Numerous technical vulnerabilities are availble for exploitation at the sensor-system interface