Proposed Methodology Chapter 3 83 Secure and Revocable Biometric Template Using Fuzzy Vault for Fingerprint, Iris and Retina CHAPTER 3 3. PROPOSED METHODOLOGY 3.1 OUTLINE OF THE PHASES OF PROPOSED METHODOLOGY 3.2 PHASE I – UNIMODAL BIOMETRIC FUZZY VAULT 3.3 PHASE II – PASSWORD HARDENED BIOMETRIC FUZZY VAULT 3.4 PHASE III – MULTIMODAL BIOMETRIC FUZZY VAULT 3.5 PHASE IV – PASSWORD HARDENED MULTIMODAL BIOMETRIC FUZZY VAULT 3.6 PHASE V– PASSWORD HARDENED TRIMODAL BIOMETRIC FUZZY VAULT FOR HIGH SECURITY APPLICATIONS 3.7 PHASE VI – COMBINED USER AND SOFT BIOMETRIC BASED PASSWORD HARDENED BIOMETRIC FUZZY VAULT 3.8 CHAPTER SUMMARY
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Proposed Methodology Chapter 3
83
Secure and Revocable Biometric Template Using Fuzzy
Vault for Fingerprint, Iris and Retina
CHAPTER 3
3. PROPOSED METHODOLOGY
3.1 OUTLINE OF THE PHASES OF PROPOSED METHODOLOGY
3.2 PHASE I – UNIMODAL BIOMETRIC FUZZY VAULT
3.3 PHASE II – PASSWORD HARDENED BIOMETRIC FUZZY VAULT
3.4 PHASE III – MULTIMODAL BIOMETRIC FUZZY VAULT
3.5 PHASE IV – PASSWORD HARDENED MULTIMODAL BIOMETRIC
• Provides Security to Fingerprint, Iris and R etinal Templates
• Overcomes the limitations of unimodal biometrics
• Overcomes the limitations of plain fuzzy vault
• Increases further the strength of the fuzzy vault
• More resistive towards spoof attacks
• Provides the merits of multimodal biometrics and password
hardening
• Provides revocability and diversity to biometric templates
• Increases further the strength of the vault
Phase V: Combined User and Soft Biometric based Password Hardened Fuzzy
Vault
• Introduces the concept of soft biometrics
• Provides the merits of multimodal biometrics, password hardening and
soft biometrics
• Provides revocability and diversity to biometric templates
• Maintains the strength of the vault
Proposed Methodology Chapter 3
87
Phase VI: Trimodal Password Hardened Fuzzy Vau lt for High Security
Applications
• Provides the merits of multimodal biometrics, password hardening and
soft biometrics
• Provides revocability and diversity to biometric templates
• Increases further the strength of the vault
• More resistive towards spoof attacks
• Provides revocability and diversity to biometric templates
• Suitable for high security applications
• In this phase, strength of the different vaults is also compared.
Proposed Methodology Chapter 3
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Figure 3.1 Phases of Proposed Methodology
Phase I Unimodal Biometric Fuzzy Vault
• Provides Security to Biometric templates
Phase II Password Hardened UniBiometric Fuzzy Vault
• Overcomes the Limitations of Plain Fuzzy Vault • More Resistive towards Attacks • Provides Revocability and Diversity • Avoids Function Creeping
Phase III Multimodal Biometric Fuzzy Vault(Bimodal)
• Overcomes the Limitations of Unibiometrics • More Resistive towards Attacks • Overcome the Limitations of Unimodal Fuzzy Vault
Phase IV Password Hardened Bimodal Biometric Fuzzy Vault
• Overcomes the Limitations of plain Fuzzy Vault • More Resistive towards Attacks • Overcomes the Limitations of Unibiometrics • Provides More Security, Revocability and Diversity • Avoids Function Creeping
Phase V Password Hardened Trimodal Biometric Fuzzy Vault
• Provides the Merits of Hardened Vault • Provides the Merits of Multibiometrics • Suitable for High Security Applications • Improves
Phase VI Combined User and Soft Biometric Based Password
Hardened Multimodal Biometric Fuzzy Vault • Introduces Soft Biometrics in Fuzzy Vault • Provides the Merits of Hardened Vault • Provides the Merits of Multibiometrics
Proposed Methodology Chapter 3
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3.2 UNIMODAL BIOMETRIC FUZZY VAULT
Fuzzy vault is a cryptographic construct proposed by Juels and Sudan
[61]. This construct is more suitable for applications where biometric
authentication and cryptography are fused to gether. Fuzzy vault framework ,
thus utilizes the goodness of both cryptography and biometrics. In fuzzy vault
framework, the secret key S is locked by G, where G is an unordered set from
the biometric sample. A polynomial P is constructed by encoding the s ecret S.
This polynomial is evaluated by all the elements of the unordered set G.
A vault V is constructed by the union of unordered set G and chaff point
set C which is not in G.
V = G U C
The union of the chaff point set hides the genuine point set fr om the
attacker. Hiding the genuine point set secures the secret data S and user
biometric template T. The vault is unlocked with the query template T’. T’ is
represented by another unordered set U’. The user has to separate sufficient
number of points from the vault V by comparing U’ with V. By using error
correction method the polynomial P can be successfully reconstructed if U’
overlaps with U and secret S gets decoded. If there is not substantial
overlapping between U and U’ secret key S is not decoded . This construct is
called fuzzy because the vault will get decoded even for very close values of U
and U’ and the secret key S can be retrieved. Therefore , fuzzy vault construct
becomes more appropriate for biometric data which possess inherent fuzziness
and hence the name fuzzy vault as proposed by Sudan [ 61]. The security of the
fuzzy vault depends on the infeasibility of the polynomial reconstruction
problem. The vault performance can be improved by adding more number of
chaff points C to the vault.
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A. Fuzzy Vault Encoding
For the vault implementation, a unique point from biometric modality is
extracted. Secret message is generated as a 128 bit random stream. The 16 bit
CRC is appended to transformed key S to get 144 bit SC. The primitive
polynomial cons idered for CRC generation is
gcrc(a) = a16 + a15+ a2 + 1
In the minutiae set, the minutiae points whose Euclidian distance is less
than D are removed. A 16 bit lock/unlock unit ‘u’ is obtained by concatenating
x and y (each 8 bits) coordinates. The ‘u’ v alues are sorted and first N of them
are selected. The Secret (SC) is divided into 9 non overlapping segments of 16
bits each. Each segment is converted to its decimal equivalent to account for
the polynomial coefficients (C8, C7 …C0). All operations tak e place in Galois
Field GF (216). The projection of ‘u’ on polynomial ‘p’ is found. Now the
Genuine points set G is ((ui, P(ui)). Random chaff points are generated which
are 10 times more in number than that of the genuine points. Thus two sets
namely the Genuine set (G) and chaff set (C) are generated in the following
way.
G = [(u1,p(u1), (u2,p(u2),…….. (u l,p(ul)] C = [(c1,d1),(c2,d2) …..(cm,dm)] cj • ui ( j = 1,2,…….l, i = 1,2, …m) dj • P(ci ) ( j = 1,2,…….l, i = 1,2, …m) VS = Listscrambled (G U C)
Where ‘u’ is genuine point ‘p(u)’ is the projection of the genuine point ‘c’ is the chaffpoint which is not in genuine point set ‘d’ is the dummy value which is not in p(u) ‘m’ is the number of chaff points ‘l’ is the number of genuine points
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Both the genuine and chaff point sets are combined to construct the
vault. The vault is list scrambled. The encoding operation for fingerprint and
retina based multimodal fuzzy vault is s hown in Figure 3.2. The following
Table 3.1 shows the notations used.
Table 3.1 Notations Used
Notations Meaning S Secret Key
SC Secret Key+ Cyclic Redundancy Code (CRC ) G Genuine set C Chaff set
VS List scrambled Vault SC* SC Generated after Decoding Q Query Template
Figure 3.2 Biometric Fuzzy vault: Encoding
Polynomial (P) Construction
Polynomial Projection
Template Minutiae Feature List
Cyclic Redundancy
Check Encoding
(SC)
List Scrambling (VS)
Secure Data (D)
Chaff Point Generation (C)
Vault (V)
Proposed Methodology Chapter 3
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B. Fuzzy Vault Decoding
From the query templates, unlocking points (N in number) are extracted.
The unlocking set is found as in encoding. This set is compared with the vau lt
to separate the genuine point set for polynomial reconstruction. From this set,
all combinations are tried to decode the polynomial. Lagrangian interpolation is
used for polynomial reconstruction. For a specific combination of feature
points the polynomial gets decoded. In order to decode the polynomial of
degree 8, a minimum of at least 9 points are required. If the combination set
contains less then 9 points, polynomial cannot be reconstructed. Now the
coefficients and CRC are appended to arrive at SC* . Then SC* is divided by
the CRC primitive polynomial.
If the remainder is not zero, query image does not match template image
and the secret data cannot be extracted. If the remainder is zero, query image
matches with the template image and the correct se cret data can be extracted.
In this case SC* is divided into two parts as the 128 bit secret data and 16 bit
CRC code. The decoding operation of fuzzy vault is shown in Fig ure 3.3.
End
Lagrange Interpolation
Secret S’ Extraction
Combination Sets
Determination
Candidate Point Identification
Query Minutiae Feature List
Vault (V)
CRC Decoding
Figure 3.3 Biometric Fuzzy vault: Decoding
Negative
Positive
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C. Security Analysis of Fuzzy Vault
The security of the fuzzy vault depends on the infeasibility of the
polynomial reconstruction and the number of chaff points. Using th is construct
128 bit secret data like Advanced Encryption Standard (AES) key can also be
protected. The security of the proposed fuzzy vault is measured by min-entropy
which is expressed in terms of security bits. According to NandaKumar [ 86]
the min-entropy of the minutiae template MT given the vault V can be
calculated as
Where
r = number of genuine points in the vault
c = number of chaff points in the vault
t = the total number of points in the vault (r + c)
In the above fuzzy vau lt an adversary has to guess (n+1) points
combinations simultaneously to decode the vault. Polynomial with lesser
degrees can be easily reconstructed by the attacker and the vault gets decoded.
Polynomials with larger degrees require a lot of computational effort. The
security of the fuzzy vault increases as the degree of the polynomial increases.
However it requires a lot of computation for higher degree polynomials which
make the system slow. The security increases as the number of chaff points in
the vault increases but at the cost of increased memory consumption. Number
of chaff points added is 10 times more than that of the genuine points to have
larger combinations for achieving higher security. Moreover, it is observed that
the process consumes more memory and makes the system slow but they are
hard to reconstruct. If the adversary stages a brute force attack, to decode a
polynomial of degree n, he has to try total of (t, n+ 1) combinations of n+1
Proposed Methodology Chapter 3
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element each. Out of this, only (r, n+1) combinations are required to decode the
vault. Hence, for an attacker to decode the vault it takes C(t, n+1) / C(r, n+1)
evaluations.
D. Merits of Fuzzy Vault Scheme
Fuzzy vault, being a crypto biometric based key binding mechanism for
template protection has the following merits;
• Fuzzy vault is a proven technology f or biometric template security
• Fuzzy vault framework thus utilizes the goodness of bo th cryptography
and biometrics
• Fuzzy vault is more suitable for applications where biometric
authentication and cryptograph y are fused together
• Fuzzy vault eliminates the key management problem as compared t o
other practical cryptosystems
• The security of the fuzzy vault depends on the infeasibility of the
polynomial reconstruction
• This construct is called fuzzy because the va ult will get decoded even
for very close values of U and the secret key S can be retrieved.
Therefore fuzzy vault construct become more appropriate for biometric
data which possesses inherent fuzziness
E. Limitation of Fuzzy Vault Scheme
Fuzzy vault being a proven scheme has its own limitati ons which are
listed as follows;
• The same biometric data cannot be used to construct a n ew vault when it is
compromised
• Fuzzy vault suffers from non -revocability, cross -matching and lack of
diversity
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• It is possible to attack the vault by performing statistic al analysis on the
vault points
• The attacker can substitute few points from his own biometric feature as
chaff points. Now the vault authenticates for the legal user as well as the
imposter for the same biometric template
• The imposter can glean the original template when it is exposed temporarily
• Fuzzy vault scheme is vulnerable to specific attacks like attack via record