Patent Publication Number: US-9900311-B2

Title: Method and device for protecting access to a message

Description:
RELATED APPLICATIONS 
     This application is a § 371 application from PCT/FR2014/053130 filed Dec. 2, 2014, which claims priority from French Patent Application No. 13 61933 filed Dec. 2, 2013, each of which is incorporated herein by reference in its entirety. 
     TECHNICAL FIELD OF THE INVENTION 
     The present invention concerns a method and a device for protecting access to a message. It applies, in particular, to security documents and bank cards. 
     STATE OF THE ART 
     Many ways of protecting content or a message borne on a medium are known. For example, encoding or encryption is applied to the data making up this message. However, simply knowing the decoding or decryption key makes it possible to access the message. However, these keys must be stocked on media, eg paper, plastic or electronic, or on servers. Irrespective of whether these keys are carried by the user or stored in a computer system, a malicious third party with the right tools can reach them. 
     These protections are therefore inadequate. 
     SUBJECT OF THE INVENTION 
     The present invention aims to remedy all or part of these drawbacks. 
     To this end, according to a first aspect, the present invention envisages a device for reading a message, which comprises:
         a means of reading biometric data of a holder of the medium;   a means of capturing, on a medium, an encoded message comprising elementary message units, said message having noise that consists of marking defects of the message on said medium which are random and unpredictable for each elementary message unit;   a means of reducing the noise of the captured message, based on biometric data; and   a means of decoding at least one portion of the message in which the noise has been at least partially removed.       

     Thanks to these provisions, at least one portion of the encoded message cannot be accessed when the authorized holder of the medium, whose biometric data is required, is absent. In addition, the device that is the subject of the present invention can be autonomous in respect of any remote information source, eg a server on a computer network. 
     In some embodiments, the means of decoding utilizes redundancies of the message with the noise removed to determine at least one portion of the encoded message. 
     Thanks to these provisions, the portion of the message to be decoded can be accessed without utilizing a remote information source. 
     In some embodiments, the means of reading biometric data is configured to read a fingerprint of the holder of the medium. 
     In some embodiments, the means of reading biometric data is configured to capture an image of the face or of the hand of the holder of the medium. 
     Thanks to these provisions, biometric data is captured with no contact between the holder of the medium and the device, reducing requirements for cleaning and risks of contamination. 
     In some embodiments, the means of reducing noise calculates a biometric data hash and utilizes the hash to reduce the noise in the captured message. 
     In some embodiments, the means of reducing noise utilizes a symmetrical hash. 
     For example, a symmetrical hash comes from a symmetrical key encryption. 
     In some embodiments, the means of decoding is configured to decode biometric data. 
     Thanks to these provisions, the reading device enables biometric data to be displayed, eg for visual confirmation of the identity of the holder of the medium, or an additional automatic verification of the identity of the holder of the medium. 
     In some embodiments, the means of decoding is configured to utilize an asymmetric key to access at least one portion of the message. 
     Thanks to these provisions, the reading device that is the subject of the present invention can be autonomous by having a set of keys, eg public keys from a public key infrastructure (PKI). 
     In some embodiments, the reading device that is the subject of the present invention comprises a means of inputting a secret code by the holder of the medium, the means of decoding being configured to utilize said secret code to access at least one portion of the message. 
     Thanks to these provisions, the consent of the holder for reading the message can be formalized by entering the secret code. 
     In some embodiments, the reading device that is the subject of the present invention comprises a means of storing and communicating payment information. 
     Thanks to these provisions, the payment is secured, since the identity of the holder of the medium has been verified through the use of biometric data. 
     According to a second aspect, the present invention envisages a method for reading a message, which comprises:
         a step of reading biometric data of a holder of the medium;   a step of capturing, on a medium, an encoded message comprising elementary message units, said message having noise that consists of marking defects of the message on said medium which are random and unpredictable for each elementary message unit;   a step of reducing the noise of the captured message, based on biometric data; and   a step of decoding at least one portion of the message in which the noise has been at least partially removed.       

     According to a third aspect, the present invention envisages a device for marking a message on a medium, which comprises:
         a means of reading biometric data of a holder of the medium;   a means of encoding at least one portion of the message;   a means of adding noise to the encoded message, based on biometric data; and   a means of marking, on a medium, the encoded message comprising elementary message units, configured so that said marking has noise that consists of marking defects of the message on said medium which are random and unpredictable for each elementary message unit.       

     According to a fourth aspect, the present invention envisages a method for marking a message on a medium, which comprises:
         a step of reading biometric data of a holder of the medium;   a step of encoding at least one portion of the message;   a step of adding noise to the encoded message, based on biometric data; and   a step of marking, on a medium, the encoded message comprising elementary message units, during which said marking has noise that consists of marking defects of the message on said medium which are random and unpredictable for each elementary message unit.       

     According to a fifth aspect, the present invention envisages a mark representative of an encoded message with noise added based on biometric data and comprising elementary message units, said mark having, in addition, noise that consists of marking defects of the message on said medium which are random and unpredictable for each elementary message unit. 
     As the particular features, advantages and aims of this reading method, this marking device, this marking method and this mark are similar to those of the reading device that is the subject of the present invention, they are not repeated here. 
    
    
     
       BRIEF DESCRIPTION OF THE FIGURES 
       Other advantages, aims and particular features of the present invention will become apparent from the description that will follow, made, as a non-limiting example, with reference to drawings included in an appendix, wherein: 
         FIG. 1  represents, schematically, a particular embodiment of the reading device that is the subject of the present invention; 
         FIG. 2  represents, in the form of a logical diagram, steps in a particular embodiment of the reading method that is the subject of the present invention; 
         FIG. 3  represents, schematically, a particular embodiment of the marking device that is the subject of the present invention; 
         FIG. 4  represents, in the form of a logical diagram, steps in a particular embodiment of the marking method that is the subject of the present invention; and 
         FIG. 5  represents, schematically, a mark that is the subject of the present invention. 
     
    
    
     DESCRIPTION OF EXAMPLES OF REALIZATION OF THE INVENTION 
     It is now noted that  FIGS. 1 and 3  are not to scale. 
       FIG. 1  shows a device  100  for reading a message  105 , which comprises:
         a means  110  of reading biometric data  115  of a holder of the medium;   a means  120  of capturing, on a medium  125 , an encoded message  130  comprising elementary message units, said message having noise that consists of marking defects of the message on said medium, said defects being random and unpredictable for each elementary message unit;   a means  135  of reducing the noise of the captured message, based on biometric data; and   a means  140  of decoding at least one portion of the message in which the noise has been at least partially removed.       

     The means  110  of reading biometric data is, for example, a reader of at least one fingerprint of the holder of the medium, or a camera configured to capture a profile of one hand or of the head of the holder of the medium. The means  110  of reading biometric data provides data characteristic of the body part of the holder of the medium that is analyzed, eg the characteristic points of a fingerprint, the lengths and shapes of the fingers of the hand, or the respective dimensions and positions of the components of the face. In some embodiments, the means of reading biometric data  110  captures the user&#39;s voice. 
     The medium  125  can be, for example, an identity or payment card, a sheet of paper, a label. The effect of marking the message on the medium is to modify locally at least one physical characteristic of the medium, on the surface or within the thickness. For example, the marking is printed, with or without ink. The encoded message  130  comprises elementary message units, said message having noise that consists of marking defects of the message on said medium, said defects being random and unpredictable for each elementary message unit. The error rate caused by the marking noise is preferably greater than five percent, ie at least five percent of the marking&#39;s elementary units are modified in sufficiently random manner such that they are incorrectly read by the means of capture. 
     The means  120  of capturing the message  130  is for example a matrix image sensor or a scanner. 
     The means  135  of reducing the noise of the captured message based on biometric data is configured to calculate a biometric data hash and to utilize said hash to reduce the noise of the captured message. 
     It can be seen here that even though the biometric data is different, between adding noise and reducing noise, because they correspond with two captures made at different times and under different conditions, their processing, which extracts characteristics, eg by frequency analysis, frequency transformation or hash extraction, provides data with low but not null variation. By applying these characteristics, with noise since they are variable, to the message, the noise affecting this message is increased or decreased. 
     For example, starting from a digital trace whose dimensions and angles have been normalized, singular points (including minutiae) that are also normalized are extracted. By applying an “exclusive OR” function to an image of this trace or of these singular points or to a hash of these images, noise is added or removed from the message. 
     It is recalled here that a fingerprint or dactylogram is the result of placing a finger on a medium after the latter has been inked. The design formed on the medium consists of dermatoglyphs. Fingerprints are unique and characteristic of each individual. 
     A “digital trace”, a broader term, is the result of a contact between a finger and a medium, fingerprints being an example of a digital trace. 
     Papillary traces (or their imprints) group digital traces (or their imprints, in which automatic identification software reference 150 to 200 characteristic points) and palm traces (traces of the palms of the hand, referenced by 1,500 to 2,000 characteristic points). 
     This is analogous to a voiceprint authenticated by speaker recognition techniques. 
     The digital trace can be:
         visible (or direct): it is called positive when material is affixed and it is called negative when material is removed;   latent (invisible to the naked eye): the trace come from deposited sweat (secretions from the sweat glands: 99% water that by evaporating leaves behind salts and amino-acids) and/or sebum deposits (sebaceous glands); and/or   molded: the trace comes from a finger coming in contact with a malleable surface (wax, putty, etc).       

     Fingerprints can be broken down into three major design types: arches (including tented arches), left-handed/right-handed loops, and whorls (including coils and swirls). These three types of print fit 95% of human fingers: 60% for loops, 30% for whorls and 5% for arches. Each print belongs to a type class: no-delta, two-delta, three-delta (rare). One-delta fingerprints are divided into subgroups: normals, externals, composites; similarly for two-delta fingerprints: concentric whorls, Z-shaped whorls. 
     “Singularities” on the loops, arches or whorls are used to differentiate the patterns from one another:
         global singularities: core or center: where the ridges converge;   delta: where the ridges diverge;   local singularities (AKA minutiae): irregular areas at the locations of capillary lines (ending ridges, bifurcations, short ridges assimilated to two ending ridges, enclosures).       

     It is estimated that two identical prints have over one hundred convergence points. French law requires 12 points (called minutiae), 18 collected without constraint to authenticate a suspect&#39;s print. From 8 to 10 points a strong presumption can be made thanks to algorithms. In Switzerland, a probabilistic system is used for comparisons: the drawing&#39;s probability is calculated based on the statistics of various minutiae appearing: short ridges, forks. 
     The probability of two persons having the same fingerprint is 1 in 10 14 , which is very small on the scale of human population. In addition, its random nature oversteps risks of similarities between individuals who share a genetic makeup: monozygotic individuals such as twins or quadruplets for example will each have a set of fingerprints that is their own and different from that of the other individuals from a single set of siblings, the same applying to the slightly different fingerprints of the left and right hands. This is explained by the fact that genes are responsible for the general architecture of the fingerprints (the three major patterns), whereas embryonic development and the intra-uterine living environment have an influence on the singularities. 
     Preferably, increasing and decreasing noise (means or steps) utilize a symmetrical hash. This principle is relatively easy to implement with biometric data, such as the iris, because it is, by its very nature, an imprint that remains stable over time. By analogy, this biometric data work, for reading, like a barcode. 
     Among the biometric data that can be utilized for increasing and decreasing noise, the following can be mentioned:
         the image of the iris of the eye;   each fingerprint;   data coming from processing an image of the face, eg coming from facial recognition;   data coming from processing an image of the hand, eg coming from recognition of the profile of the hand pressed against a flat surface;   data coming from processing voice capture, eg coming from voice recognition; and   data coming from processing a succession of positions, eg coming from gesture recognition, for example gestures of the hand when signing, body movements, eye movements.       

     The means  140  of decoding at least a portion of the message that has had at least part of the noise removed utilizes redundancies in the message with the noise removed to determine at least one portion of the encoded message. For example, the means  140  knows the positions of the redundant elementary message units or the redundancy generation code, so as to use these redundancies, detect and correct errors making up the noise. For example, the redundancies are in the form of cyclic redundancy check codes (or CRC). 
     The means of decoding  140  is, in some embodiments, configured to decode biometric data. In some embodiments, the device  100  comprises a means of displaying the biometric data read in the message. A third party can thus visually check the identity of the holder of the medium. In some embodiments, the device  100  comprises a means of automatically checking that the holder of the medium matches the biometric data read in the message. 
     In some embodiments, the means of decoding  140  utilizes an asymmetric key to access at least one portion of the message. 
     In the embodiment illustrated in  FIG. 1 , the device  100  also comprises a means  145  of inputting a secret code by the holder of the medium. For example, the means  145  is a keyboard. The means of decoding  140  is then configured to utilize the secret code to access at least one portion of the message. For example, this secret code is part of a decryption key of the message. 
     In the embodiment illustrated in  FIG. 1 , the device  100  comprises a means of storing and communicating payment information. For example, the device  100  sends, using means of communication  155  to a server of the holder of the medium&#39;s bank, data coming from a store cash register  150 . 
     As a variant, questioning the user about the transaction is added (a procedure known as “challenge-response”) to secure the acquisition of the biometric data by the hardware. In this way, a data signature is introduced to render ineffectual the attack presenting data already collected and possibly intercepted. 
       FIG. 2  shows a method for reading a message  200 , which comprises:
         a step  205  of reading biometric data of a holder of the medium;   a step  210  of capturing, on a medium, an encoded message comprising elementary message units, said message having noise that consists of marking defects of the message on said medium which are random and unpredictable for each elementary message unit;   a step  215  of reducing the noise of the captured message, based on biometric data; and   a step  220  of decoding at least one portion of the message in which the noise has been at least partially removed.       

       FIG. 3  shows a device  300  for marking a message on a medium, which comprises:
         a means  305  of reading biometric data of a holder of the medium;   a means  310  of adding noise to an encoded message, based on biometric data;   a means  315  of encoding at least one portion of the message; and   a means  320  of marking, on a medium, the encoded message comprising elementary message units, configured so that said marking has noise that consists of marking defects of the message on said medium which are random and unpredictable for each elementary message unit.       

     In the case where the present invention is utilized to sign an action performed by the holder of the medium bearing the mark representative of the message, the medium serves to authenticate the holder. In the case where the present invention is utilized to sign a document, in addition to authenticating the holder, the content of the document is authenticated. For example, the device  300  serves, when signing a contract, to associate the signatories&#39; identities with a trace, eg a hash of the full content of the contract. 
     Remember signing before a notary. 
       FIG. 4  shows a method  400  for marking a message on a medium, which comprises:
         a step  405  of reading biometric data of a holder of the medium;   a step  410  of encoding at least one portion of the message;   a step  415  of adding noise to the encoded message, based on biometric data; and   a step  420  of marking, on a medium, the encoded message comprising elementary message units, during which said marking has noise that consists of marking defects of the message on said medium which are random and unpredictable for each elementary message unit.       

       FIG. 5  shows a mark  500 , which represents an encoded message with noise added according to biometric data and which comprises elementary message units  505 . The mark  500  has noise that consists of marking defects of the message on said medium, which are random and unpredictable for each elementary message unit.