WO2009141759A1

WO2009141759A1 - Noise robust helper data system (hds)

Info

Publication number: WO2009141759A1
Application number: PCT/IB2009/051951
Authority: WO
Inventors: Alphons A. M. L. Bruekers; Stefan Katzenbeisser; Thomas A. M. Kevenaar; Cynthia C. S. Liem; Ilyaz H. Nasrullah
Original assignee: Koninklijke Philips Electronics N.V.
Priority date: 2008-05-19
Filing date: 2009-05-12
Publication date: 2009-11-26
Also published as: DE102009021761A1

Abstract

The present invention discloses a method for performing authentication (AUTH) of a requester in a helper data system (HDS). Initially, there is provided a first feature vector ( (X+N) ), the feature vector comprising a vector of sets, and thereafter a permutation of the first feature vector is performed resulting in a corresponding collection of permutated feature vectors ({(X+N)'}). A collection of codes ({C'}) is generated from the collection of permutated feature vectors ({(X+N)}') using helper data (W), and finally a comparison of the collection of codes ({C'}) with a reference code (C) from a corresponding enrollment to find a match. The invention also relates to a similar method for performing enrollment (ENRL) in a helper data system (HDS), the method comprising instead a permutation of the first feature vector during enrollment resulting in corresponding collection of permutated feature vectors ({X'}).The invention is advantageous for obtaining a helper data concept that may operate on features organized as a collection of feature vectors, the feature vectors comprising of sets, such as the ones used to represent short tandem repeat (STR) profiles, and cope with a limited number of errors in profiles during authentication.

Description

Noise robust helper data system (HDS)

FIELD OF THE INVENTION

The present invention relates to a method for performing authentication of a requester in a helper data system (HDS), and a corresponding method for performing enrollment in a helper data system (HDS). The present invention also relates to corresponding systems for performing authentication of a requester in a helper data system (HDS), and a corresponding system for performing enrollment. The invention also relates to a database comprising corresponding enrollment data. The present invention also relates to a computer program product for performing authentication of a requester in a helper data system (HDS), and a computer program product for performing enrollment in a helper data system (HDS).

BACKGROUND OF THE INVENTION

Identification and authentication are commonly used techniques for establishing identity. Identity could be the identity of a person or an object. Prime examples of application areas for identification and authentication are access control for buildings or information, authorization of payments and or other transactions. Identification and authentication are closely related concepts with a subtle difference.

During the process of authentication an object with an alleged identity is offered for authentication. Subsequently characteristics of the object offered for authentication are matched with those of the enrolled object with the alleged identity. If a sufficient match is found the identity of the object being authenticated is said to be the alleged identity. Authentication thus deals with matching one object being authenticated to one enrolled object based on the alleged identity.

During the process of identification of an object, the identity of a physical object is established by matching characteristics of the object with characteristics of previously enrolled objects. If a successful match is found the identity of the object being authenticated is said to be the identity of the matching object. The identification process can be seen as a repeated authentication process of an object with an enrolled object. In practical authentication systems the authentication process is generally preceded by an enrolment process. During this enrolment characteristics of the object at hand are measured and stored. Based on the measured data so-called template data is generated for the object. This template data is used during the authentication process for matching enrolled objects with the measured characteristics.

Helper Data Systems (HDS) have recently been proposed in order to solve privacy threats coupled to biometric authentication. HDS allow renewable biometric authentication, inhibit cross-matching of biometric data between several different biometric databases and help against identity theft. These systems have successfully been applied, among others, to human fingerprints and facial recognition systems.

A helper data system (HDS) provides the authentication terminal with so- called helper data W and a control value C. Both are generated during enrolment and are used instead of the actual template data. The helper data is generated using the template data, but characteristics of the template data are obfuscated in such a way that there is hardly any correlation between the template data and the helper data. The control value C is generated in parallel with the helper data W and serves as a control value for the authentication process. The helper data and control value are used during authentication. First the helper data is combined with data acquired from the physical object (e.g. biometric feature such as facial feature data). This combined data is subsequently "condensed" into a second control value C This second control value C is matched with the control value C generated during enrolment. When these control values match authentication is successful.

The performance of such a HDS system depends highly on the representation of the feature vector X and the properties of the error correcting code used. If the number of differences between C and C is not larger than the error-correcting capability of the used code will exactly be the same as the original code (yielding the same hash function result). This means the helper data system (HDS) can cope with a limited number of measurement errors.

Typical Helper Data Systems (HDS) start by encoding the feature vector X as a long binary vector and use a traditional binary error correcting code (such as a Reed- Solomon code) in the construction. This usage implies that the similarity between two feature vectors is always measured in terms of their Hamming distance (counting the number of different symbols through symbol-by- symbol comparison). However, HDS for DNA profiles have to operate on vectors of features that may have no intrinsic order. Directly applying classic HDS schemes will result in systems that cannot cope with noisy DNA data. The use of for instance slightly different short tandem repeat (STR) profiles (e. g., profiles that were incorrectly reported due to the imperfection of the chemical analysis method, or profiles with mutations in the DNA parts used for sampling) will with high probability yield to a rejection in the authentication phase. Hence, an improved method for performing authentication of a requester in a helper data system (HDS), and a corresponding method for performing enrollment in a helper data system (HDS) would be advantageous, and in particular more efficient and/or reliable methods therefore would be advantageous.

SUMMARY OF THE INVENTION

Accordingly, the invention preferably seeks to mitigate, alleviate or eliminate one or more of the above mentioned disadvantages singly or in any combination. In particular, it may be seen as an object of the present invention to provide method for a performing authentication of a requester in a helper data system (HDS), and a corresponding method for performing enrollment in a helper data system (HDS) that solves the above mentioned problems of the prior art with noise in the feature vector.

This object and several other objects are obtained in a first aspect of the invention by providing a method for performing authentication of a requester in a helper data system (HDS), the method comprising: - providing a first feature vector ( (X+N) ), the feature vector comprising a vector of sets, performing at least one permutation of the first feature vector resulting in a corresponding collection of permutated feature vectors ({(X+N)'}), generating a collection of codes ({C}) from the collection of permutated feature vectors ({(X+N)} ') using helper data (W), and comparing the collection of codes ({C}) with a reference code (C) from a corresponding enrollment.

This object is alternatively or additionally obtained in a first aspect of the invention by providing a method for performing enrollment in a helper data system (HDS), the method comprising: providing a first feature vector (X) from a requester, the feature vector comprising a vector of sets, performing at least one permutation of the first feature vector resulting in corresponding collection of permutated feature vectors ({X'}), generating a collection of helper data ({W}) from the collection of permutated feature vectors ({X'}) using a reference code (C), and storing the collection of the helper data ({W}).

The invention is particularly, but not exclusively, advantageous for obtaining a helper data concept that may operate on features organized as a collection of feature vectors, the feature vectors comprising of sets, such as the ones used to represent short tandem repeat (STR) profiles, and cope with a limited number of errors in profiles during authentication. The invention may be of significant use in the protection of STR profiles derived from DNA. DNA has shown to be a reliable modality to identify persons. However, DNA sequences can reveal sensitive medical information. Therefore, if DNA would be used for authentication purposes, protection of the original profile data is desired.

It should be understand that the above methods performing authentication and enrollment in a helper data system (HDS) may advantageously be combined. Thereby, a number of permutations may be performed on the enrollment side, whereas an equivalent number of other permutations may be performed on the authentication of the helper data system (HDS). Thus, if one type of error is more likely to take place during the enrollment so error may be mitigated, alleviated or at least partly eliminated by such advantageous combination.

For both methods for performing authentication and enrollment in a helper data system (HDS), the first feature vector may beneficially comprise sets of different dimensions to facilitate a variety of data to be embedded in the first feature vector. Thus, each set can have a high and different dimension. Alternatively, the first feature vector may comprise sets of equal dimensions to allow for homogenous kind of data entries in the feature vector. Preferably, the dimension of the sets may be two, and the first feature vector of sets may be in the form of:

( [xl, yl], [x2, y2] , ...[xi, yi], .... , [xN, yN] ) ,

where N is an integer, and where the elements x and y taken from a finite set A. Beneficially, the finite set A may represent a group of alleles obtained in a genetic identification process.

In one embodiment, the feature vector may be a biometric feature vector of various kind, but preferably the said biometric feature vector may comprise information obtained from a genetic identification process. Even more preferably, the said biometric feature vector may comprise a representation of alleles representing a short tandem repeat profile (STR), e.g. N=IO or 13 in the above equation, the use STR profiles being a relatively mature technology currently.

For the above authentication method, the number of permutations in the collection of permutated first feature vector ( {(X+N)'}) may advantageously be dependent on the number of allowable errors (k) in the authentication process of the helper data system (HDS). Exactly how many permutations depend on the error level or "noise" accepted in the HDS.

In one embodiment, the code is decoded into secret data (S) and a one-way mapping of secret data is performed to obtain mapped secret data (h(S') ). Moreover, the authentication may be based on a comparison between the mapped secret data (h(S') ) and reference mapped secret data ( h(S) ) obtained from a corresponding enrollment process to facilitate reliable and efficient authentication.

For the above enrollment method, the generated helper data may comprises a collection of helper data ({W}), the number of entries in the collection of helper data ({W}) being dependent on the number of permutations of the first feature vector, which is, in turn, dependent on the number of allowable errors (k) during a corresponding authentication. Thereby, the accepted number of errors can be easily controlled.

In one embodiment, the code (C) is encoded from a secret data (S), and a oneway mapping (h) of the secret data (S) is performed to obtain mapped secret data ( h(S) ). Moreover, the collection of helper data ({W}) may be retrievable together with corresponding mapped secret data ( h(S) ) in an authentication process to facilitate a reliable and efficient helper data system (HDS).

Additionally, the above enrollment method may be supplemented with a method for authentication in a helper data system (HDS) corresponding to the said enrollment method. Thus, this method of authentication comprises providing a first feature vector ( (X+N) ), the feature vector comprising a vector of sets, generating a collection of codes ({C}) from feature vectors ( (X+N) ) using the collection of helper data ({W}) obtained from the above enrollment method, and comparing the collection of codes ({C}) with a reference code (C) from the corresponding enrollment.

In a second aspect, the invention relates to a computer program product being adapted to enable a computer system comprising at least one computer having data storage means associated therewith to control a helper data system (HDS) according to the first aspect of the invention. This aspect of the invention is particularly, but not exclusively, advantageous in that the present invention may be implemented by a computer program product enabling a computer system to perform the operations of the second aspect of the invention. Thus, it is contemplated that some known helper data system (HDS) may be changed to operate according to the present invention by installing a computer program product on a computer system controlling the said optical recording apparatus. Such a computer program product may be provided on any kind of computer readable medium, e.g. magnetically or optically based medium, or through a computer based network, e.g. the Internet.

In a third aspect, the present invention relates to a helper data system (HDS) adapted to perform authentication (AUTH) of a requester, the system comprising: a permutator (P) for performing at least one permutation of a first feature vector, the first feature vector ( (X+N) ) comprising a vector of sets, resulting in a corresponding collection of permutated feature vectors ({(X+N)'}), a generator for generating a collection of codes ({C}) from the collection of permutated feature vectors ({(X+N)} ') using helper data (W), and a processor for comparing the collection of codes ({C}) with a reference code (C) from a corresponding enrollment.

In a third aspect the present invention relates alternatively or additionally to a helper data system (HDS) adapted to perform enrollment (ENRL), the system comprising: - a permutator (P) for performing at least one permutation of a first feature vector from a requester, the first feature vector (X) comprising a vector of sets, resulting in corresponding collection of permutated feature vectors ({X'}), a generator for generating a collection of helper data ({W}) from the collection of permutated feature vectors ({X'}) using a reference code (C), and - storage means for storing the collection of the helper data ({W}).

In a fourth aspect, the present invention relates to a database for cooperating with a helper data system (HDS), the database comprising a collection of the helper data ({W}), the collection of helper data ({W}) being generated from a collection of permutated feature vectors ({X'}) using a reference code (C), the first feature vector (X) from a requester comprising a vector of sets, wherein at least one permutation of the first feature vector results in a corresponding collection of said permutated feature vectors ({X'}).

The database may be typically further comprise a reference of unpermutated helper data (W) for reference. In one embodiment, the database may comprise data values for only one requester, e.g. one person, and the database may be portable in a convinient format, e.g. a smart-card. Together with the requester's feature vector, e.g the STR profile of the requester, this may provide a quite reliable and efficient identification tool and/or access tool. The first, second, third and fourth aspect of the present invention may each be combined with any of the other aspects. These and other aspects of the invention will be apparent from and elucidated with reference to the embodiments described hereinafter.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention will now be explained, by way of example only, with reference to the accompanying Figures, where Figure 1 is a schematic diagram of a helper data system (HDS),

Figure 2 is a simplified diagram of an authentication in a helper data system (HDS) according to the present invention,

Figure 3 is a more detailed diagram of an authentication in helper data system (HDS) according to the present invention, Figure 4 is a simplified diagram of an enrollment in a helper data system

(HDS) according to the present invention,

Figure 5 is a more detailed diagram of an enrollment in helper data system (HDS) according to the present invention, and

Figure 6 is flow-charts of an authentication and enrollment method according to the present invention.

DETAILED DESCRIPTION OF AN EMBODIMENT

Figure 1 is a schematic diagram of a helper data system HDS. As shown in Figure 1, in a HDS two phases are distinguished: an enrollment phase ENRL to the left and an authentication phase AUTH to the right.

The purpose of the enrollment phase ENRL is to generate a database 2 with protected biometric entries; in the authentication phase AUTH, the biometric data of a person is matched against a protected database entry stored in the database 2.

Database entries for users are created during the enrollment phase ENRL. In this phase, the sensitive user biometrics, expressed as a fixed-length feature vector X, is combined with an encoded secret C in order to form a helper data entry W. The secret itself is a vector S of uniform random symbols (thus being completely independent of the information in X). S is encoded using an error-correcting block code (ECC). This could for instance include that parity symbols are added to S, resulting in a vector C. The helper data is then formed by adding X to C. Further, a one-way cryptographic hash function is applied to S; the result h(S) is stored in the database as well.

During authentication, an unknown user claims to have a helper data entry in the database; to support this claim, he will provide his noisy feature vector (biometrics) X + N to the system. X + N is subtracted from the helper data entry. This will result in a vector C that differs from the originally used codeword C at as many symbols as X differs from X + N. Subsequently, C is decoded into a secret S'. Then, the one-way cryptographic hash function is applied to S' and the resulting h(S') is compared to h(S); if they are exactly the same, the unknown user will be authenticated. The performance of the system depends highly on the representation of X and the properties of the error correcting code used. If the number of differences between C and C is not larger than the error-correcting capability of the used code, S' will exactly be the same as the original S (yielding the same hash function result). This means the helper data system can cope with a limited number of measurement errors. Figure 2 is a simplified diagram of an authentication process in a helper data system HDS according to the present invention. The authentication AUTH of the requester (not shown) in a helper data system HDS comprises providing a first feature vector (X+N), the feature vector comprising a vector of sets, the feature vector preferably being a genetic identification feature vector based on short tandem repeats (STR) or similar sequences. Thereafter, there is performed at least one permutation P of the first feature vector resulting in a corresponding collection of permutated feature vectors (X+N)'_l, (X+N)'_2, (X+N)'_3, etc. common called {(X+N)'}, the annotation "{... }" of curly brackets indicating a collection i.e. at least one member.

Further there is generated a collection of codes Cl ', C2', C3', etc., commonly abbreviated {C}, from the collection of permutated feature vectors {(X+N)'} using the helper data W as it will be known from a helper data system HDS, the difference being that each feature vector in the collection of the permutated feature vectors {(X+N)'} will result in a corresponding code.

Finally, there is performed a comparison, indicated by the double arrow with question mark "?", of the collection of codes {C} with a reference code C from a corresponding enrollment of a helper data system HDS. If a match is found within the collection of codes {C}, authentication is said to be positive. If no match is found, authentication is said to be negative. Figure 3 is a more detailed diagram of an authentication in helper data system HDS according to the present invention. In order to permutating the first feature vector X + N during the authentication phase AUTH, a permutation block P will be added to the system as displayed in top of Figure 3. This block P will produce a collection {(X+N) '} of the relevant permutations of (X + N) .

Reduction of the number of relevant permutations can also take place in block P in case that the first feature vector (X + N) contains some sets with identical elements or sets that are known to be noise-free. This will be further explained below.

The permutations in {(X+N) '} are subtracted from the helper data W, resulting in a collection of code words (CJ. These code words are all decoded in block 31; the hash function is then applied to all elements in the resulting set of possible secrets (S 'J in the box 32, thereby producing a set of hashed values (h(S')j. Subsequently, the original h(S) will be compared to all elements in (h(S')J in the decision box 33 i.e. processing means arranged to perform a comparison , yielding a set of 'y^es' ^and 'no' answers. If this collection contains a 'yes' answer, an access control block 34 will grant access to the user. Otherwise, the user is rejected by the system.

The number of permutations in the collection of first feature vector of sets {(X+N)'} is, in general, dependent on the number of allowable errors (e) in the authentication process of the helper data system HDS. Exactly, how many permutations depends on the error level that is accepted in the HDS.

A simple example may further illustrate this. LetXbe the feature vector [ [a b] [a b] [a b] ] and X + Nbc a noisy variant of the feature vector: [ [b a] [b a] [c b] ], i.e. where the last set has "a" replaced by "c" due to e.g. a measurement error in the STR process. By imposing an order on these vectors (in this case a lexicographical order), X stays [ [a b] [a b] [a b] ] and X + TV becomes [ [a b] [a b] [b e] ]. Treating these as vectors, this will result in (a b a b a b) and (a b a b b c). If these vectors are directly used in a traditional HDS that allows coping with one symbol error, one will obtain a rejection, as the Hamming distance is two. However, an accept response is desired, because X and X + N only differ only in one element, the number of acceptable errors being zero or one. By applying the present invention, in the enrollment phase we treat the feature vector [ [a b] [a b] [a b] ] as vector (a b a b a b). In the authentication phase however, we apply all relevant permutations to the feature vector [ [b a] [b a] [c b] ], see Table 1 below. The number of relevant permutations depends on the number of errors the HDS should tolerate. For one error, it suffices to permute the two elements of exactly one subset of the feature vector. The scheme can be extended in a straightforward manner in case k errors should be tolerated: the set of relevant permutations consists of all permutations of the measured feature vector where the two elements of k or less sets are permuted. This can be given mathematically as the number of alternatives, A, that are to be presented during the authentication, for at the most k number of acceptable errors e, are

for two elements in each set, e.g. [a b]. It should be mentioned that when the feature vector X comprises p equal pair, N should be replaced with N-p in the above equation. For one error however, one thus end up with JV relevant permutations.

Table I . Relevant permutations

In the authentication phase, all permuted feature vectors are matched with the template stored in the database 2. Table 2 shows the Hamming distances between the encoded, permuted feature vectors and the vector that was used to form the template. As it can be seen from Table 2, there exists one permutation, which results only in one symbol (Hamming) error, which the underlying HDS system is able to correct. Thus, a match is obtained.

Permutation of X + N Encoded permutations Hamming distance to X

X = [ [a b] [a b] [a b] ] encoded as (a b a b a b)

[ [a b] [a b] [b c] ] (a b a b b c) 2

[ [b a] [a b] [b c] ] (b a a b b c) 4

[ [a b] [b a] [b c] ] (a b b a b c) 4

[ [a b] [a b] [c b] ] (a b a b c b) I Table 2. Relevant permutations of X + N with Hamming distances, It should be noticed with respect to Figure 3, that the enrollment process ENRL shown to the left of Figure 3 may be a enrollment process now in the prior art.

The present invention is particularly suited for applying biometric feature vector X based on the genetic identification e.g. STR . These short sequences (e.g. length 4 or 5) of nucleotides repeat a number of times and the number of repetitions varies largely over the population. Although the number of repetitions differs, the subsequences in front and after the repetition are constant. This phenomenon is called a Short Tandem Repeat (STR) and is ideal for identification. By selecting STR-loci on different chromosomes the statistics per STR are independent. In Europe the SGM-plus method is used that finds 10 STR loci and a gender indication area. STR markers with detailed information can be found at the STR Base: www.cstl.nist.gov/biotech/strbase/index.htm

In a preferred embodiment, the STR-markers used with the system of the invention comprise at least one STR marker selected from the group consisting of: CSFlPO, TPOX, D5S818, D7S820, D13S317, D3S1358, VWA, D16S539, D2S1338, A (gender marker Amelogenin), D8S1179, D21S11, D18S51, D19S433, THOl and FGA.

In another embodiment, the number of STR-markers used with the system is selected from the group consisting of least 2 markers, at least 3 markers, at least 4 markers, at least 5 markers, at least 6 markers, at least 7 markers, at least 8 markers, at least 9 markers, at least 10 markers, at least 11 markers, at least 12 markers, at least 13 markers, at least 14 markers, at least 15 markers, at least 16 markers selected from the group consisting of: CSFlPO, TPOX, VWA, D5S818, D7S820, D13S317, D3S1358, D16S539, D2S1338, A (gender marker Amelogenin), D8S1179, D21S11, D18S51, D19S433, THOl and FGA.

In another embodiment, wherein the STR markers comprise at least the group consisting of CSFlPO, FGA, THOl, TPOX, VWA, D3S1358, D5S818, D7S820, D8S1179, D13S317, D16S539, D18S51 and D21Sl l or at least the group consisting of D3 S 1358,

VWA, D16S539, D2S1338, A (gender marker Amelogenin), D8S1179, D21S11, D18S51, D19S433, TH01 and FGA.

Figure 4 is a simplified diagram of an enrollment process in a helper data system (HDS) according to the present invention. The enrollment in a helper data system (HDS) method comprises providing a first feature vector (X) from a requester, i.e. a physical object, the feature vector X comprising a vector of sets.

There is then performed at least one permutation P of the first feature vector X resulting in corresponding collection of permutated feature vectors X l ', X_2', X_3', etc., commonly called {X'}. Further there is generated a collection of helper data; Wl, W2, W3, etc, commonly called {W}, from the collection of permutated feature vectors {X'} using a reference code C from the HDS. Finally, the step of storing the collection of the helper data {W} in database 2 is performed. The generated helper data comprises a set of helper data {W}, where the number of entries in the collection of helper data {W} is dependent on the number of permutations of the first feature vector. It can be shown similarly to example given above for the corresponding authentication process that the number of entries EN that are to be generated during the enrollment, for at the most £ number of acceptable errors e, are

for two elements in each set, e.g. [a b]. It should also here be mentioned that when the feature vector X comprises p equal pair, N should be replaced with N-p in the above equation

Figure 5 is a more detailed diagram of an enrollment in helper data system HDS according to the present invention. The choice is now made to permute X during enrollment which means a helper data entry will be stored for each permutation. A permutation block P will be added to the system as displayed in the left part of Figure 5, which represent an enrollment process ENRL. The block P has the same functionality as the previously described permutation block P of Figure 3. In this case however, the permutation P will produce a collection of relevant permutations of the feature vector (X'j during the enrollment. The addition step known from Figure 1 is now performed for each permutation in (X'j resulting in a collection of helper data entries (Wj. During authentication on the right, the feature vector X + N is subtracted from each element in { Wj, resulting in a collection of possible code words (Cj. Subsequently, the same steps will be performed as previously described for the case of permuting X + N as described in connection with Figures 1 and 3.

Figure 6 is flow-charts of an authentication (left) and enrollment (right) method according to the present invention:

The method for performing authentication AUTH of a requester in a helper data system (HDS) comprises:

Sl providing a first feature vector (X+N), the feature vector comprising a vector of sets, 52 performing at least one permutation of the first feature vector resulting in a corresponding collection of permutated feature vectors {(X+N)'},

53 generating a collection of codes {C} from the collection of permutated feature vectors {(X+N)} ' using helper data W, and - S4 comparing the collection of codes {C} with a reference code C from a corresponding enrollment.

The method for performing enrollment ENRL in a helper data system (HDS) comprises:

51 providing a first feature vector X from a requester, the feature vector comprising a vector of sets,

52 performing at least one permutation of the first feature vector resulting in corresponding collection of permutated feature vectors {X'},

53 generating a collection of helper data {W} from the collection of permutated feature vectors {X'} using a reference code C, and - S4 storing the collection of the helper data {W}.

The invention can be implemented in any suitable form including hardware, software, firmware or any combination of these. The invention or some features of the invention can be implemented as computer software running on one or more data processors and/or digital signal processors. The elements and components of an embodiment of the invention may be physically, functionally and logically implemented in any suitable way.

Indeed, the functionality may be implemented in a single unit, in a plurality of units or as part of other functional units. As such, the invention may be implemented in a single unit, or may be physically and functionally distributed between different units and processors.

Although the present invention has been described in connection with the specified embodiments, it is not intended to be limited to the specific form set forth herein. Rather, the scope of the present invention is limited only by the accompanying claims. In the claims, the term "comprising" does not exclude the presence of other elements or steps. Additionally, although individual features may be included in different claims, these may possibly be advantageously combined, and the inclusion in different claims does not imply that a combination of features is not feasible and/or advantageous. In addition, singular references do not exclude a plurality. Thus, references to "a", "an", "first", "second" etc. do not preclude a plurality. Furthermore, reference signs in the claims shall not be construed as limiting the scope.

Claims

CLAIMS:

1. A method for performing authentication (AUTH) of a requester in a helper data system (HDS), the method comprising: providing a first feature vector ( (X+N) ), the feature vector comprising a vector of sets, - performing at least one permutation of the first feature vector resulting in a corresponding collection of permutated feature vectors ({(X+N)'}), generating a collection of codes ({C}) from the collection of permutated feature vectors ({(X+N)}') using helper data (W), and comparing the collection of codes ({C}) with a reference code (C) from a corresponding enrollment.

2. A method for performing enrollment (ENRL) in a helper data system (HDS), the method comprising: providing a first feature vector (X) from a requester, the feature vector comprising a vector of sets, performing at least one permutation of the first feature vector resulting in corresponding collection of permutated feature vectors ({X'}), generating a collection of helper data ({W}) from the collection of permutated feature vectors ({X'}) using a reference code (C), and - storing the collection of the helper data ({W}).

3. The method according to claim 1 or 2, wherein the first feature vector comprising sets of different dimensions.

4. The method according to claim 1 or 2, wherein the first feature vector comprising sets of equal dimensions.

5. The method according to claim 4, wherein the dimension of the sets is two, and the first feature vector of sets is in the form of: ( [xl, yl], [x2, y2] , ...[xi, yi], .... , [xN, yN] ) where N is an integer, and where the elements x and y taken from a finite set A.

6. The method according to claim 5, wherein the finite set A represents a group of alleles obtained in a genetic identification process.

7. The method according to claim 1 or 2, wherein the feature vector is a biometric feature vector.

8. The method according to claim 7, wherein the said biometric feature vector comprises information obtained from a genetic identification process.

9. The method according to claim 8, wherein the said biometric feature vector comprises a representation of alleles representing a short tandem repeat profile (STR).

10. The method according to claim 1, wherein the number of permutations in the collection of permutated first feature vector ( {(X+N)'}) is dependent on the number of allowable errors (k) in the authentication process of the helper data system.

11. The method according to claim 1 , wherein the code is decoded into secret data

(S) and a one-way mapping of secret data is performed to obtain mapped secret data (h(S') ).

12. The method according to claim 11, wherein the authentication is based on a comparison between the mapped secret data (h(S') ) and reference mapped secret data ( h(S) ) obtained from a corresponding enrollment process.

13. The method according to claim 2, wherein the generated helper data comprises a collection of helper data ({W}), the number of entries in the collection of helper data ({W}) being dependent on the number of permutations of the first feature vector, which is dependent on the number of allowable errors (k) during a corresponding authentication.

14. The method according to clam 13, wherein the code (C) is encoded from a secret data (S), and a one-way mapping (h) of the secret data (S) is performed to obtain mapped secret data ( h(S) ).

15. The method according to clams 14, wherein the collection of helper data

({W}) is retrievable together with corresponding mapped secret data ( h(S) ) in an authentication process.

16. A method for authentication in a helper data system (HDS) corresponding to the enrollment method of claim 2, the method of authentication comprising providing a first feature vector ( (X+N) ), the feature vector comprising a vector of sets, generating a collection of codes ({C }) from feature vectors ( (X+N) ) using the collection of helper data ({W}) according to claim 2, and - comparing the collection of codes ({C}) with a reference code (C) from the corresponding enrollment.

17. A computer program product being adapted to enable a computer system comprising at least one computer having data storage means associated therewith to control an helper data system (HDS) according to claim 1 or claim 2.

18. A helper data system (HDS) adapted to perform authentication (AUTH) of a requester, the system comprising: a permutator (P) for performing at least one permutation of a first feature vector, the first feature vector ( (X+N) ) comprising a vector of sets, resulting in a corresponding collection of permutated feature vectors ({(X+N)'}), a generator (30) for generating a collection of codes ({C}) from the collection of permutated feature vectors ({(X+N)} ') using helper data (W), and a processor (31, 32, 33) for comparing the collection of codes ({C}) with a reference code (C) from a corresponding enrollment.

19. A helper data system (HDS) adapted to perform enrollment (ENRL), the system comprising: a permutator (P) for performing at least one permutation of a first feature vector from a requester, the first feature vector (X) comprising a vector of sets, resulting in corresponding collection of permutated feature vectors ({X'}), a generator (50) for generating a collection of helper data ({W}) from the collection of permutated feature vectors ({X'}) using a reference code (C), and storage means (2) for storing the collection of the helper data ({W}).

20. A database (2) for cooperating with a helper data system (HDS), the database comprising a collection of the helper data ({W}), the collection of helper data ({W}) being generated from a collection of permutated feature vectors ({X'}) using a reference code (C), the first feature vector (X) from a requester comprising a vector of sets, wherein at least one permutation of the first feature vector results in a corresponding collection of said permutated feature vectors ({X'}).