Authenticating concealed private data while maintaining concealment

US 7,237,115 B1
Filed: 09/26/2001
Issued: 06/26/2007
Est. Priority Date: 09/26/2001
Status: Expired due to Fees

First Claim

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1. A method of authenticating an item, the method comprising:

a) acquiring an unencrypted reference signal, Y_ref, of an item;

where Y_refis an n-dimensional row vector {Y₁(ref), Y₂(ref), . . . , Y_n(ref)} of unencrypted reference measurements subject to measurement error;

b) applying a transformation to the unencrypted reference signal, Y_ref, to generate an encrypted reference signal, U_refof the item;

where U_refis an n-dimensional row vector {U₁(ref), U₂(ref), . . . , U_n(ref)} of encrypted reference measurements;

c) acquiring an unencrypted new signal, Y_new, of the item, where Y_newis an n-dimensional row vector {Y₁(new), Y₂(new), . . . , Y_n(new)} of unencrypted new measurements subject to measurement error;

d) applying the transformation to the unencrypted new signal, Y_new, to generate an encrypted new signal, U_new, of the item;

where U_newis an n-dimensional row vector {U₁(new), U₂(new), . . . , U_n(new)} of encrypted new measurements;

e) calculating an unencrypted Euclidean distance metric, E, between the unencrypted new and reference signals, Y_newand Y_ref;

f) calculating an encrypted Euclidean distance metric, D, between the encrypted new and reference measurements, U_newand U_ref;

g) comparing the encrypted Euclidean distance metric, D, to a critical value, D_crit,;

h) if D<

D_crit, then deciding that the item is authentic; and

i) providing the result of the decision made in step h) to an authenticator or inspector, thereby allowing the authenticator or inspector to decide if the item is authentic;

wherein the transformation has the property that the unencrypted Euclidean distance metric, E, is equal to the encrypted Euclidean distance metric, D.

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Abstract

A method of and system for authenticating concealed and statistically varying multi-dimensional data comprising: acquiring an initial measurement of an item, wherein the initial measurement is subject to measurement error; applying a transformation to the initial measurement to generate reference template data; acquiring a subsequent measurement of an item, wherein the subsequent measurement is subject to measurement error; applying the transformation to the subsequent measurement; and calculating a Euclidean distance metric between the transformed measurements; wherein the calculated Euclidean distance metric is identical to a Euclidean distance metric between the measurement prior to transformation.

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27 Claims

1. A method of authenticating an item, the method comprising:
- a) acquiring an unencrypted reference signal, Y_ref, of an item;
  
  where Y_refis an n-dimensional row vector {Y₁(ref), Y₂(ref), . . . , Y_n(ref)} of unencrypted reference measurements subject to measurement error;
  
  b) applying a transformation to the unencrypted reference signal, Y_ref, to generate an encrypted reference signal, U_refof the item;
  
  where U_refis an n-dimensional row vector {U₁(ref), U₂(ref), . . . , U_n(ref)} of encrypted reference measurements;
  
  c) acquiring an unencrypted new signal, Y_new, of the item, where Y_newis an n-dimensional row vector {Y₁(new), Y₂(new), . . . , Y_n(new)} of unencrypted new measurements subject to measurement error;
  
  d) applying the transformation to the unencrypted new signal, Y_new, to generate an encrypted new signal, U_new, of the item;
  
  where U_newis an n-dimensional row vector {U₁(new), U₂(new), . . . , U_n(new)} of encrypted new measurements;
  
  e) calculating an unencrypted Euclidean distance metric, E, between the unencrypted new and reference signals, Y_newand Y_ref;
  
  f) calculating an encrypted Euclidean distance metric, D, between the encrypted new and reference measurements, U_newand U_ref;
  
  g) comparing the encrypted Euclidean distance metric, D, to a critical value, D_crit,;
  
  h) if D<
  
  D_crit, then deciding that the item is authentic; and
  
  i) providing the result of the decision made in step h) to an authenticator or inspector, thereby allowing the authenticator or inspector to decide if the item is authentic;
  
  wherein the transformation has the property that the unencrypted Euclidean distance metric, E, is equal to the encrypted Euclidean distance metric, D.
- View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27)
- - 2. The method of claim 1, wherein applying the transformation generates encrypted data that is indistinguishable from Gaussian white noise.
  - 3. The method of claim 1, wherein applying the transformation comprises normalizing the measurements.
  - 4. The method of claim 3 wherein the normalizing step comprises centering and scale-transforming the measurements so that the mean is zero and the standard deviation is 1.
  - 5. The method of claim 1, wherein applying the transformation comprises permuting the measurements.
  - 6. The method of claim 5 wherein permuting comprises employing an item of secret information.
  - 7. The method of claim 6 wherein permuting comprises employing a passcode.
  - 8. The method of claim 7 wherein permuting additionally comprises employing the results of a harsh function of the passcode.
  - 9. The method of claim 1, wherein applying the transformation comprises employing a linear transformation.
  - 10. The method of claim 9 wherein employing a linear transformation comprises employing a n×
    - m linear transformation matrix, W, with orthonormal columns, where n≦
      
      m.
  - 11. The method of claim 10 wherein employing a linear transformation comprises employing a normalized Hadamard matrix.
  - 12. The method of claim 10 wherein employing a linear transformation comprises employing a normalized matrix comprising Fourier coefficients with a cosine/sine basis.
  - 13. The method of claim 10, wherein the elements, w_ij, of the transformation matrix, W, have the following properties:
    - $\sum_{i = 1}^{n} w_{ij}^{2} = 1, \forall_{j}; w_{i1} = \frac{1}{\sqrt{n}}, \forall_{i};$ and $\sum_{i = 1}^{n} w_{ij} = 0, \forall_{j > 1} with w_{i1} = κ, \forall_{i} .$
  - 14. The method of claim 9 wherein employing a linear transformation comprises permuting the linearly transformed data.
  - 15. The method of claim 14 wherein permuting the linearly transformed data comprises employing an item of secret information.
  - 16. The method of claim 15 wherein permuting the linearly transformed data comprises employing a passcode.
  - 17. The method of claim 16 wherein permuting the linearly transformed data additionally comprises employing the results of a hash function of the passcode.
  - 18. The method of claim 1, wherein the measurements comprise biometric data.
  - 19. The method of claim 18 wherein the measurements comprise measurements selected from the group consisting of fingerprints, retinal scans, facial scans, hand geometry, spectral data, and voice data.
  - 20. The method of claim 18, additionally comprising the step of placing reference biometric data on a smart card to be carried by an individual from whom the biometric data was taken.
  - 21. The method of claim 1, wherein the measurements comprise spectral data.
  - 22. The method of claim 21 wherein the measurements comprise weapons spectra.
  - 23. The method of claim 1, additionally comprising the step of adding pseudo-dimensions to the measurements to enhance concealment.
  - 24. The method of claim 1, wherein:
    - $E = \sum_{j = 1}^{n} {(Y_{j} (new) - Y_{j} (ref))}^{2}$ and $D = \sum_{j = 1}^{m} {(U_{j} (new) - U_{j} (ref))}^{2}$ wherein m≦
      
      n.
  - 25. The method of claim 1, wherein:
    - $E = \sum_{j = 1}^{n} \frac{{(Y_{j} (new) - Y_{j} (ref))}^{2}}{Y_{j}}$ and $D = \sum_{j = 1}^{m} \frac{{(U_{j} (new) - U_{j} (ref))}^{2}}{Y_{j}}$ wherein m≦
      
      n; and
      
      the denominator can be either Y_j(new) or Y_j(ref).
  - 26. The method of claim 1, wherein:
    - $E = \sum_{j = 1}^{n} {(\sqrt{Y_{j}} (new) - \sqrt{Y_{j}} (ref))}^{2}$ and $D = \sum_{j = 1}^{m} {(\sqrt{U_{j}} (new) - \sqrt{U_{j}} (ref))}^{2}$ wherein m≦
      
      n.
  - 27. The method of claim 1, wherein applying the transformation to the unencrypted signal, Y, comprises:
    - Y→
      
      Y_π→
      
      Y_π·
      
      W→
      
      (Y_π·
      
      W)_σwherein;
      
      π
      
      is a permutation of the integers from 1;
      
      n that is unique to a particular verification class;
      
      W is an n×
      
      m transformation matrix with orthonormal columns that transforms the vector, Y, of measurements to m≦
      
      n latent variables; and
      
      σ
      
      is a permutation of the integers from 1;
      
      m that is unique to the particular verification class; and
      
      wherein the verification class comprises one or more physical units, items, or individuals.

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Current Assignee
National Technology & Engineering Solutions Of Sandia LLC (Honeywell International Inc.)
Original Assignee
Sandia Corporation (Martin Marietta Corporation)
Inventors
Thomas, Edward V., Draelos, Timothy J.
Primary Examiner(s)
Moazzami; Nasser
Assistant Examiner(s)
Cervetti; David Garcia

Application Number

US09/964,221
Time in Patent Office

2,099 Days
Field of Search

713/186, 713/176
US Class Current

713/176
CPC Class Codes

H04L 2209/08   Randomization, e.g. dummy o...

H04L 2209/34   Encoding or coding, e.g. Hu...

H04L 9/32   including means for verifyi...

H04L 9/3231   Biological data, e.g. finge...

Authenticating concealed private data while maintaining concealment

First Claim

4 Assignments

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Abstract

Citations

27 Claims

Specification

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Authenticating concealed private data while maintaining concealment

First Claim

4 Assignments

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0 Petitions

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Accused Products

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Abstract

Citations

27 Claims

Specification

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Solutions

Use Cases

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