JP2000358025A - Information processing method, information processor and recording medium storing information processing program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To prevent data from being illegally decoded by another person by providing a processor for binding a scholar feature vector from biometrics data, a processing for calculating a key to be used for cipher decoding processing, based on the feature vector, a processor for decoding data by using the key, etc. SOLUTION: A cryptograph key calculation part 4 calculates a cipher decoding key for decoding data based on the scholar feature vector called a fingerprint characteristic value bound by a fingerprint characteristic value calculation part 3. A data enciphering part 5 executes enciphering processing by using the calculated key, and the obtained cipher is stored in an enciphered data storing part 6. In decoding the stored enciphered data, a user inputs the same fingerprint to a fingerprint sensor 10 and the fingerprint characteristic value is similarly calculated. Based on the characteristic value, the part 4 calculates a key to be used for decoding and a data decoding part 7 executes decoding processing by using the stored enciphered data and this key.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an information processing method, an information processing apparatus, and a recording medium storing an information processing program for encrypting and decrypting information for concealing the contents. The present invention relates to an information processing method using measurable biometrics (biological characteristics) such as a fingerprint, an information processing apparatus, and a recording medium storing an information processing program.

[0002]

2. Description of the Related Art In an information processing apparatus, a method of encrypting data is used for concealing the contents of data to be stored. For example, in the DES method using a common secret key, an “integer key” serving as a source of encryption is determined, and the plaintext data is converted accordingly. Decryption of this encrypted data is confidential to anyone other than the authorized person, and this person can decrypt the data with this key, but without knowing the key, reverse-calculate the plaintext from the encrypted data It is not possible to use the same plaintext data to obtain different encrypted data if the key is different, thereby realizing secure confidentiality.

[0003]

If the encryption key is stored in a device that can be internally analyzed by a third party, the encryption key is read illegally and decrypted using the encryption key. Therefore, there is a possibility that the contents of the data that the user wanted to keep confidential could be decrypted by others. Therefore, this key or a secondary key for generating the key is desirably input by the user at the time of encryption and decryption. However, this key is generally more secure as the number of bits is larger, and it is not practical for the user to memorize the key and input it at the time of decryption. In addition, if the key is known by peeping at this input, others can decrypt it by the same method, so biometrics that can only be input by the person himself, that is, measurable biometric characteristics such as fingerprints are used together. It is necessary to prevent spoofing.

Conventionally, in order to realize authentication using a fingerprint,
The only function was to measure the correlation between fingerprint data or to compare features extracted from fingerprints to determine whether the input fingerprint and the previously registered fingerprint were the same finger. Therefore, when the fingerprint authentication and the encryption key concealment are linked, for example, the fingerprint feature data and the decryption key are stored in the device or the like, the fingerprint is stamped at the time of decryption, the feature is calculated, and the stored fingerprint is stored. If the key belongs to the same person as the characteristic data, a method such as reading out the key and decrypting it with the key is used. However, as long as the fingerprint characteristic data and the key that can be read only when the collation succeeds are held in the device, there is a risk that the device is stolen and misused by an unauthorized internal analysis of the device.

According to the present invention, when data is encrypted to keep the contents secret, the key used for the encryption / decryption processing is prevented from being read illegally and decrypted by unauthorized persons to prevent the data from being read. Is a device that uses biometrics such as fingerprints that cannot be spoofed by others to generate a key using the biometrics input at the time of encryption or decryption. It is an object of the present invention to provide an information processing device with high security that is unlikely to be decrypted.

[0006]

The present invention according to claim 1 is an information processing method for encrypting and decrypting data, wherein the information processing method is characterized by being invariable from input biometric data. A process of calculating a quantity, a process of calculating a key used for encryption / decryption processing based on the feature amount, a process of encrypting data using the key, and a newly input data when decrypting the data. A process for obtaining the feature amount from the biometrics data obtained, a process for calculating a key used for encryption / decryption processing based on the feature amount, and a process for decrypting data using the key. And

According to a second aspect of the present invention, in the information processing method, a random number is generated each time a key to be used for encryption / decryption processing is calculated based on the feature amount, and the encryption is performed using the random number. Calculating a key used for the decryption process.

According to a third aspect of the present invention, in the information processing method, when calculating a key to be used for encryption / decryption processing based on the feature amount, a process of reading a character string input by a user; Calculating a key to be used in the encryption / decryption process using the sequence.

According to a fourth aspect of the present invention, there is provided an information processing method for authenticating an individual, the information processing method comprising: a biometric data input process for obtaining biometric data; and an invariable data from the biometric data. An eigenvalue calculation process for obtaining a feature amount, an encryption key calculation process for obtaining an encryption key based on the feature amount, a feature extraction processing unit for extracting matching feature data from the biometric data,
A data encryption / decryption process for encrypting / decrypting the feature data using the encryption key; and a collation process for collating the decrypted feature data with the feature data extracted from the newly input biometrics data. It is characterized by the following.

The invention according to claim 5 is characterized in that the biometrics data is image data of a fingerprint of a finger.

According to a sixth aspect of the present invention, there is provided an information processing apparatus for encrypting and decrypting data, the information processing apparatus comprising: a biometrics data input unit for inputting biometrics data; An eigenvalue calculator for obtaining an invariant feature amount from data, an encryption key calculator for obtaining an encryption key based on the feature amount, and a data encryption / decryption unit for decrypting the data using the encryption key. It is characterized by the following.

[0012] The invention according to claim 7 is characterized in that the information processing apparatus further comprises a random number generation unit for generating a random number used for obtaining an encryption key by calculation each time encryption is performed.

In the invention described in claim 8, the encryption key calculation unit reads an arbitrary character string input by a user when calculating the encryption key by calculation, and uses the character string and the feature amount to generate an encryption key. Is obtained.

[0014] According to a ninth aspect of the present invention, there is provided a biometrics data input unit for acquiring biometrics data,
An eigenvalue calculation unit for obtaining an invariant feature amount from the biometric data, an encryption key calculation unit for obtaining an encryption key based on the feature amount, a feature extraction unit for extracting matching feature data from the biometric data, A data encryption / decryption unit that encrypts / decrypts the feature data using an encryption key, and a collation unit that collates the decrypted feature data with feature data extracted from newly input biometrics data. Features.

According to a tenth aspect of the present invention, there is provided a computer-readable recording medium having recorded thereon an information processing program for encrypting and decrypting data, wherein the information processing program is configured to convert input biometrics data. In the process of obtaining an invariant feature amount, the process of calculating a key used for encryption / decryption processing based on the feature amount, the process of encrypting data using the key, A computer performs a process of obtaining the feature amount from the newly input biometrics data, a process of calculating a key used for encryption / decryption processing based on the feature amount, and a process of decrypting data using the key. Is performed.

An invention according to claim 11 is a computer-readable recording medium recording an information processing program for performing personal authentication, wherein the information processing program is a biometric data input process for acquiring biometric data. And an eigenvalue calculation process for obtaining an invariant feature amount from the biometric data; an encryption key calculation process for obtaining an encryption key based on the feature amount; and a feature extraction processing unit for extracting matching feature data from the biometric data. And, using the encryption key, a data encryption / decryption process of encrypting / decrypting the feature data, and a matching process of matching the decrypted feature data with feature data extracted from the newly input biometrics data. Is performed by a computer.

[0017]

DESCRIPTION OF THE PREFERRED EMBODIMENTS An information processing apparatus according to one embodiment of the present invention will be described below with reference to the drawings. <First Embodiment> FIG. 1 is a block diagram showing the configuration of the first embodiment. In this figure, reference numeral 1 denotes an information processing device, which is a fingerprint sensor 10 for inputting a fingerprint image of a user, a fingerprint unique value calculation unit 3, an encryption key calculation unit 4, a data encryption unit 5, an encrypted data storage unit 6. , And a data decoding unit 7. Further, the fingerprint eigenvalue calculation unit 3 is configured to include a ridge extraction unit 11, a singular point detection unit 12, a nodal line extraction unit 13, a main pattern determination unit 14, and a feature calculation unit 15.

The fingerprint sensor 10 captures a fingerprint image when a user's finger touches it, converts the image data into digital image data so that the fingerprint eigenvalue calculator 3 can process it, and outputs the digital image data. As a configuration method of the fingerprint sensor, for example, LE
The light emitted in D is reflected by the prism, and at this time, the reflected light is different between the ridge and the valley according to the ridge of the finger placed outside the reflection surface. An optical system that captures a fingerprint image by converting it into a digital image can be used.

The fingerprint eigenvalue calculator 3 receives the fingerprint image obtained from the fingerprint sensor 10 and executes a process of calculating a scalar feature value called a fingerprint eigenvalue which is a source of a key used for data encryption from the fingerprint image. . The fingerprint unique value is a value unique to each individual and each finger, and has a property that, when the same fingerprint of the same person is input, the same unique value is output with a high probability. The method for calculating the fingerprint unique value will be described later.

The encryption key calculation unit 4 calculates an encryption / decryption key for performing data encryption / decryption based on the scalar feature amount called a fingerprint unique value obtained by the fingerprint unique value calculation unit 3. The data encryption unit 5 performs an encryption process on the input data plaintext such as the data file using the calculated key, and stores the obtained encrypted text in the encrypted data storage unit 6.
Is stored.

When decrypting the stored encrypted data,
The user inputs the same fingerprint to the fingerprint sensor 10, and the fingerprint unique value is calculated as in the case of encryption. The fingerprint unique value stably gives the same scalar amount as a unique value for a plurality of impressions for the same fingerprint. A key used for decryption is calculated by the encryption key calculation unit 4 based on the unique value, and a decryption process is performed by the data decryption unit 7 using the stored encrypted data and this key. As a result, the unique value should be equal to the value at the time of encryption,
The contents of the original plaintext data can be correctly obtained.

In the fingerprint eigenvalue calculator 3, ridges are first extracted from the input fingerprint image by the ridge extractor 11,
From the obtained ridge pattern information, the singular point detection unit 12, the nodal line extraction unit 13, the main pattern determination unit 14, the feature calculation unit 1
In 5, feature values are calculated, and the feature value integration unit 14 integrates them to calculate a fingerprint unique value.

The ridge extracting unit 11 tracks ridges existing on the input fingerprint image and outputs the description. Singularity detection unit 1
Numeral 2 detects the positions of the core singularity and the delta singularity from the ridge description obtained by the ridge extracting unit 11, and determines their coordinate values. The main pattern determining unit 14 determines a pattern (main classification) based on the ridge information and the singular point information obtained from the ridge extracting unit 11 and the singular point detecting unit 12. The nodal line extraction unit 13 detects and determines the position and direction of a first joint line (hereinafter, a nodal line) included in the input fingerprint image. These parts are
For example, since it can be realized using the technology of the ridge extraction unit, the singular point detection unit, the main pattern judgment unit and the knot line extraction unit described in Japanese Patent No. 2827994 “Fingerprint feature extraction device”,
Detailed description is omitted.

In the feature calculation unit 15, the singularity detection unit 12,
Based on the information on the singular point, the main pattern, and the position of the nodal line input from the main pattern determining unit 14 and the nodal line extracting unit 13, between the singular points and the nodal line according to the pattern determined by the main pattern determining unit. Are calculated from the positional relationship between them, and they are combined and output as a fingerprint unique value.

The eigenvalue calculation method used here has an advantage that a constant eigenvalue can be stably calculated at high speed even if there is a displacement or distortion between the imprinted fingerprints.

Next, the operation will be described with reference to FIG.
Here, the description will be made on the assumption that the data stored on a personal computer (hereinafter, referred to as a PC) is encrypted so that only the user himself / herself can decrypt the data whose secrecy is desired.

When a user wants to encrypt a data file or the like on a PC, first, the fingerprint sensor 10
Inputs the fingerprint of the user's own finger. Subsequently, the fingerprint sensor 10 outputs the input fingerprint image to the fingerprint unique value calculator 3. The ridge extracting unit 11 reads this fingerprint image,
Extract the ridge pattern and output the result. Next, the singularity detection unit 12 detects the positions of the core singularity and the delta singularity from the ridge information obtained by the ridge extraction unit 11,
Determine the coordinate values. Subsequently, the main pattern determining unit 14
Based on the ridge information and the singularity information obtained from the ridge extraction unit 11 and the singularity detection unit 12, a pattern pattern (main classification)
To determine. The node extraction unit 13 detects and determines the position and direction of the first joint line (hereinafter, node) included in the input fingerprint image.

Next, the feature calculator 15 calculates the singular point, the main pattern, and the nodal line position information input from the singular point detecting unit 12, the main pattern determining unit 14, and the nodal line extracting unit 13 based on the information.
The feature amounts calculated from the positional relationship between the singular points and the nodal lines according to the pattern pattern determined by the main pattern determining unit 14 are calculated, and the following eigenvalues are calculated by combining them.

As a specific example, first, the judgment result of the main pattern is 1
Considering the case of a hoofprint having one core and one delta, the core C and the delta D
, The number of core-delta intersecting ridges, that is, the number of line segments connecting two points and the number of fingerprint ridges intersecting in that section are determined. This is obtained by counting the number of intersections from the ridge description obtained from the ridge extraction unit 13 and the above described line segment. Similarly, the number of core-node intersecting ridges and the number of delta-node intersecting ridges are determined from node line position information.

The main pattern-like determination result, the number of core-delta crossing ridges, the number of core-node crossing ridges, and the number of delta-node crossing ridges obtained as above are used as individual features. More specifically, independent bit fields are given to the plurality of features, and the calculated feature amounts are coded and embedded, whereby the eigenvalue of the fingerprint is calculated from the input fingerprint, and the calculation by the fingerprint eigenvalue calculation unit 3 is performed. Output as result.

In the above description, the case where the judgment result of the main pattern is a hoof-shaped print is described. In the case of a spiral print, there are a maximum of two cores and two deltas. In this case, the above feature amounts can be calculated for all or some of the six combinations of the four points. . In the case of an arcuate pattern, for example, the number of intersecting ridges crossing a perpendicular drawn from the point of maximum curvature to the terminal line is used.

When the same finger is imprinted a plurality of times, the number of intersecting ridges between the main pattern, the singular point and the nodal line is unchanged, and the judgment result of the main pattern shows that the intersecting ridge between the singular point and the nodal line is not changed. The calculation results of the number of lines can be observed and calculated stably. Therefore, the unique value is also unchanged and can be a value unique to the fingerprint.

On the other hand, since these values are widely distributed in the natural world and the probability of being exactly the same is very small, different eigenvalues are calculated for different fingerprints.
Therefore, it can be said that it is almost impossible to calculate the same eigenvalue by inputting a fingerprint other than that of the user.

The encryption key calculation unit 4 calculates a key used for encryption processing based on the fingerprint unique value output from the feature calculation unit 4. Of course, the fingerprint unique value itself can be used as a key as it is. However, in order to reduce the possibility that the unique value is known to a third party, or when the number of bits of the unique value differs from the key used for data encryption, The key can be determined using the determined hash function. The hash function is a mapping function that cannot obtain the value of the input from the calculation result (the inverse function cannot be estimated).

The data encryption unit 5 uses the key calculated by the encryption key calculation unit 4 to perform encryption processing on the plaintext data file prepared on the PC. For the encryption processing, for example, a common key encryption method such as DES which uses a common encryption key is used. After the calculation, the encryption key is deleted. As a result, the contents of the data file stored in the encrypted data storage unit 6 are stored in an encrypted state. If the value of the key used for this encryption cannot be known, the third party Cannot decrypt this data file.

Next, when the user who encrypted the data file decrypts the data file later, the following procedure is performed. The user decrypts this data file in the encrypted data storage unit 6 of the PC (restores the contents by decrypting the data)
In order to perform the above operation, the data file stored in the encrypted data storage unit 6 is specified, and then the fingerprint of the finger used for the encryption is input to the fingerprint sensor 10.
The fingerprint sensor 10 reads this fingerprint and outputs a ridge extraction unit 11.
Output to

The singularity detection unit 12 detects the positions of the core singularity and the delta singularity from the ridge information obtained by the ridge extraction unit 11 in the same manner as in the encryption, and determines the coordinate values. The main pattern determining unit 14 includes a ridge extracting unit 11 and a singular point detecting unit 12.
The pattern pattern (main classification) is determined based on the ridge information and the singular point information obtained from the above. The nodal line extraction unit 13 detects and determines the position and direction of a first joint line (hereinafter, a nodal line) included in the input fingerprint image.

The feature calculating unit 15 performs encryption at the time of encryption based on the information of the singular point, the main pattern, and the nodal line position input from the singular point detecting unit 12, the main pattern determining unit 14, and the nodal line extracting unit 13. , Calculate the characteristic values similar to the eigenvalue calculation, and combine them to calculate the eigenvalue by the same calculation method as in the encryption. The encryption key calculation unit 4 calculates a key used for the decryption process based on the fingerprint unique value output from the feature calculation unit 15 in the same manner as in the encryption.

The data decryption unit 7 uses the key calculated by the encryption key calculation unit 4 at the time of decryption, and uses the encrypted data storage unit 6
Performs decryption processing on the data file stored in. The same method as in the encryption is used for the decryption processing.
Thus, the contents of the data file stored in the encrypted data storage unit 6 are decrypted, and the contents of the original plaintext file data are restored, so that the user who has input the fingerprint can read the contents.

By such an operation, the information processing apparatus 1
On the other hand, decryption is permitted only when a correct and identical fingerprint of a legitimate user is input during encryption and decryption. In this case, there is no need for the user to remember the key for decryption and the password for starting the decryption operation, and there is no fear that the password cannot be decrypted due to forgetting the password. Further, since decryption cannot be performed unless a correct fingerprint is input, it is possible to prevent a third party from impersonating the user of the data file and reading the data illegally.

Further, since it is not necessary to store the secret key used for decrypting the data file in the information processing device 1, the secret key is read illegally, and the decryption process is executed to delete the contents of the file. Decryption can be prevented, and highly secure data storage can be realized.

<Second Embodiment> Next, a second embodiment will be described with reference to FIG. In this figure, the same parts as those of the embodiment shown in FIG. 1 are denoted by the same reference numerals, and description thereof will be omitted. The information processing apparatus 1 shown in this figure differs from the information processing apparatus 1 shown in FIG. 1 in that a random number generation unit 8 is newly provided.

The encryption key calculation unit 4 in the first embodiment
Uses the fingerprint unique value calculated by the fingerprint unique value calculation unit 3 as it is as an encryption key, or uses the fingerprint unique value as an input to a function such as a hash function to perform a certain calculation, and uses the function calculation result as an encryption key. Is used. In the present embodiment, a random number generation unit 8 is provided, and the encryption key calculation unit 4 receives a different random number generated by the random number generation unit 8 and a fingerprint unique value each time, and, for example, encrypts the sum of these values. By inputting the function of the key calculation unit 4, even if the same fingerprint is input, the encryption key is different each time.

At the time of encryption, an encryption key is generated from the random number generated by the random number generator 8 and the fingerprint unique value as described above, the contents of the plaintext data file are encrypted, and the fingerprint unique value is discarded on the spot. The random number is stored in the encrypted data storage unit 6 together with the encrypted data. At the time of decryption, a key used for decryption is calculated from the stored random number and the fingerprint unique value calculated from the newly input fingerprint (this should be equal to the fingerprint unique value at the time of encryption). The same key can be calculated by the same calculation as that for encryption, and used for decryption.

Further, at the time of encryption, the user sends a certain password or a data string such as a password to the encryption key calculation unit 4 through input means such as a keyboard, a numeric keypad, a mouse, and a tablet provided in the PC. The user input data is digitized by some method (for example, a character code is obtained for each character, and the numerical value can be converted by adding or multiplying the character code) and added to the fingerprint unique value in the same manner as the random number. For example, the key value may be made more difficult to guess. In this case, unlike the case of the random number, the user inputs the user input data stored again at the time of decryption, and uses this to calculate the same decryption key as at the time of encryption at the encryption key calculation unit 4. Thus, there is no need to save this user input data.

As described above, since the key used for decryption cannot be restored only by the data stored in the apparatus, the security can be further enhanced.

In the above description, a local data encryption / decryption operation in a personal computer has been described. However, when the personal computer is used as a user terminal such as a server / client system via a network, a server is not used. It can also be used to encrypt data stored in.

In this case, the fingerprint image acquired by the fingerprint sensor connected to the PC at hand of the user used as the terminal is subjected to processing up to the fingerprint unique value calculation or the encryption key calculation, and the calculated unique value or encryption key is calculated. The data is sent to the server via the network as it is, and the data stored on the server is encrypted and decrypted. Furthermore, by generating an encryption key including a random number and user-input data as described above, even if the encryption key is obtained illegally, it cannot be used for the next decryption, so that a more secure system can be realized. Can be.

Third Embodiment Next, a third embodiment will be described with reference to FIG. Here, a description will be given assuming that login authentication using a fingerprint is performed on a PC.

Various systems that use biometrics such as fingerprints to prevent impersonation by others in authentication of login of a computer or the like have already been proposed, but basically, feature data (registered fingerprints) used for fingerprint collation are used. Data) is stored somewhere, the user who requests authentication at the time of authentication inputs a fingerprint, and authentication is realized by determining whether the feature data obtained from this input data matches the registered fingerprint data by the collation operation. Was. In this case, the registered fingerprint data must be stored somewhere, and if it is stolen illegally, unauthorized impersonation can be realized by inputting this data as if it were obtained from the input data. Problem. The present embodiment prevents this and realizes highly secure and reliable authentication.

First, a process of registering own fingerprint data by inputting a fingerprint to the fingerprint sensor 40 by a legitimate user for authentication will be described with reference to solid arrows shown in FIG. In FIG. 3, the fingerprint data input from the fingerprint sensor 40 is used to calculate a unique value in the fingerprint unique value calculation unit 43 in the same manner as described above.
At 4, an encryption key is calculated. This operation is the same as in the first embodiment.

On the other hand, in the feature extracting section 48, the fingerprint sensor 4
The fingerprint image obtained from 0 is received, and a process for extracting features used for fingerprint identification from the fingerprint image is executed. As a method for realizing feature extraction, for example, a document “Automatic fingerprint matching using minutiae network features --- Feature extraction process-” Hiroshi Asai, Yukio Hoshino, Kazuo Kiji, IEICE Transactions,
ol. J72-D-II, no. 5, pages 724-7
32, May 1989.

Here, a ridge pattern is extracted from a grayscale image including ridges by a binarization process and a thinning process, and after detecting the positions of the end points and the branch points, the intersections on the line segment connecting the ridge patterns are detected. The number of ridges is counted, and the relationship diagram is represented as digital data, which is used as a fingerprint feature for collation.

The collation characteristic data obtained by the fingerprint characteristic extraction unit 48 is sent to the data encryption unit 45, where it is encrypted using the key determined by the encryption key calculation unit 44. That is, fingerprint feature data is input as plaintext file data in the first embodiment. The encrypted data is stored in the fingerprint feature data storage unit 46.

On the other hand, the operation when the user requests authentication for login will be described with reference to the dashed arrow shown in FIG. When a fingerprint is input to the fingerprint sensor 40,
As in the case of the registration, the fingerprint unique value calculation unit 43 for the fingerprint data input from the fingerprint sensor 40 in the same manner as described above.
, A unique value is calculated, and an encryption key is calculated in the encryption key calculation unit 44. This operation is the same as in the first embodiment. This key is sent to the data decryption unit 47 to be used for decrypting the fingerprint characteristic data stored in the fingerprint characteristic data storage unit 46. Data decryption unit 4
7 decrypts the fingerprint feature data stored in the fingerprint feature data storage unit 46 using the key.

In the feature extracting section 48, the fingerprint sensor 4
0, and performs a process of extracting a feature used for fingerprint identification from the fingerprint image. The feature data of the input fingerprint at the time of matching obtained as a result is compared with the fingerprint matching unit 41.
Send to The fingerprint collation unit 41 collates the fingerprint characteristic data at the time of registration decrypted by the data decryption unit 47 with the characteristic data of the input fingerprint at the time of collation, and determines a match.

As a method for realizing the collation for identifying the imprinter using the fingerprint, for example, a document “Automatic fingerprint collation by minutiae network feature—collation process—”
Hiroshi Asai, Yukio Hoshino, Kazuo Kiji, IEICE Transactions, vol. J72-D-II, no. 5, page 73
3-740, May 1989.

Here, the number of intersecting ridges on the line segment connecting the end points of the ridges and the branch points is counted, the positions are represented by digital data, and then the similarity between them is evaluated. By doing so, collation is realized. The fingerprint feature used in this method is that the correct matching result can be obtained stably even if there is misalignment or distortion between the imprinted fingerprints.The score is sufficiently high for the same finger, but almost zero for different fingers. The data size is much smaller than the input fingerprint image.
There is an advantage that the amount of calculation processing for collation is small.

In the present embodiment, fingerprint feature data used for fingerprint matching with extremely high accuracy is encrypted using an encryption key calculated based on a fingerprint unique value, and a valid user presents a fingerprint. Without this, this data can be stolen because you cannot decrypt it and access its contents,
While improper use is not possible, when fingerprints are imprinted by a legitimate user, eigenvalues are calculated from them, the fingerprint features are decoded, and highly accurate verification is performed with the input fingerprint to achieve highly reliable authentication. be able to.

In the above description, a local log-in operation in a PC has been described. However, when the PC is used as a user terminal of a system for performing electronic commerce via a network, for example, the identity verification in the transaction is performed. Can also be used. In this case, the fingerprint feature data input by the user is encrypted based on the fingerprint unique value of the user, and transmitted from the terminal for the user of the system for performing the electronic commerce to the authentication host of the electronic commerce via the network, and the authentication is performed. The host performs identity verification by checking the match with the fingerprint feature data stored therein. Data flowing on the network is encrypted based on the fingerprint unique value, and cannot be reused even if obtained by a third party illegally. Further, there is no need to agree on an encryption key between the transmitting side and the receiving side for each communication, and it is not necessary to store the key somewhere.

Further, in this case, if the information processing apparatus used by the user is not a so-called stationary PC terminal but a card-like one, the convenience for carrying is more excellent. By mounting a fingerprint sensor and a chip for calculation and data storage on a card on which an integrated circuit such as an IC card can be mounted, a portable terminal that communicates with such an e-commerce user terminal via a network is provided. An authentication card can be realized.

In the above description, the method of calculating the fingerprint unique value using the fingerprint of one finger has been described. Of course, a plurality of fingers are input, and the unique values of the plurality of fingerprints calculated in the same manner are combined. Calculating the key can further increase security. The order of inputting a plurality of fingers can be treated as a part of the user input data in the second embodiment, and the encryption key can also be made dependent on this order to increase security.

In the above description, the case of a fingerprint is described as an example of biometrics. However, the fingerprint sensor and the fingerprint eigenvalue calculation unit are input with different biometrics (biological characteristics unique to an individual), If replaced by means for extracting and calculating eigenvalues, other biometrics such as palm print, face, iris, retinal blood vessel pattern, palm shape, handwriting, and voice print can be used.

As described above, an invariant characteristic amount is obtained from the biometric data, a key used for the encryption / decryption processing is calculated based on the characteristic amount, and data is encrypted using this key.
When data is decrypted, an invariant feature is calculated from the newly input biometrics data, a key to be used for encryption / decryption processing is calculated based on this, and data is decrypted using this key. Thus, it is possible to prevent unauthorized acquisition of data and the like.

In the present invention, an invariant feature value (fingerprint unique value) is obtained from the input fingerprint data, a key is calculated using this as a key, and the key is used for encryption. As the invariant feature, a fingerprint is classified in advance and a feature uniquely calculated from a measurable feature between a pattern, a core, a delta, a maximum curvature point, and a nodal line is used. Without the fingerprint of the person, it cannot be decrypted and there is no need to store the key anywhere, so that secure encryption can be realized. Of course, there is a feature that the fingerprint cannot be restored from this key.

In file encryption, plaintext is encrypted using a value obtained by eigenvalue calculation from an input fingerprint at the time of registration or a value obtained by adding a random number or a user input password to the file, and these are stored in the apparatus. . At the time of decryption, a key is created from the result of performing a fingerprint unique value calculation on a new decryption input fingerprint, and the data is decrypted.

Furthermore, in communication and storage of features used for fingerprint collation in applications such as authentication, fingerprint feature data may be encrypted with a key created by a combination of a key obtained in the above-described fingerprint key generation and a random number. it can. If the random number is stored or communicated with this and the fingerprint is used again at the time of decryption, secure authentication using the fingerprint is realized, and since the fingerprint data is determined by the random number, it is protected by one-time encryption. Will be done.

A program for realizing the functions shown in FIGS. 1, 2 and 3 is recorded on a computer-readable recording medium, and the program recorded on this recording medium is read and executed by a computer system. Thus, the encryption / decryption process may be performed. Here, the “computer system” includes an OS and hardware such as peripheral devices. The “computer system” also includes a homepage providing environment (or a display environment) if a WWW system is used. The “computer-readable recording medium” is a floppy disk, a magneto-optical disk,
A portable medium such as an OM or a CD-ROM, or a storage device such as a hard disk built in a computer system.

The “computer-readable recording medium” is a program that is dynamically transmitted for a short time, such as a communication line for transmitting a program via a network such as the Internet or a communication line such as a telephone line. (A transmission medium or a transmission wave), in which case a program that holds a program for a certain period of time, such as a volatile memory in a computer system serving as a server or a client, is also included. The program may be for realizing a part of the functions described above, and may be a program for realizing the functions described above in combination with a program already recorded in the computer system, that is, a so-called difference file (differential file). Program).

[0070]

As described above, according to the present invention, by using the file encryption technology based on biometrics, there is no need to store the password and there is no need to store the password. This provides an effect that an information processing device that makes it difficult to access data can be realized.

According to the present invention, further, in data encryption, encryption is performed using a key calculated only by inputting the biometric data,
There is also obtained an effect that data concealment that can be decrypted only by the user can be realized while preventing unauthorized acquisition of the key.

Further, according to the present invention, when storing and communicating biometrics data in an information processing apparatus, the data is encrypted using a key calculated only by inputting the biometrics data. Management of biometric information can be facilitated and illegal outflow can be prevented.

According to the present invention, a key is generated by using a random number and a character string input by a user together,
Even if the same fingerprint is used, an effect is obtained that the encryption key is different each time, so that another person cannot use the same fingerprint illegally.

[Brief description of the drawings]

FIG. 1 is a block diagram showing a configuration of a first embodiment of the present invention.

FIG. 2 is a block diagram showing a configuration of a second embodiment of the present invention.

FIG. 3 is a block diagram showing a configuration of a third embodiment of the present invention.

[Explanation of symbols]

 1, 49: information processing device, 3, 43: fingerprint unique value calculation unit, 4, 44: encryption key calculation unit, 5, 45: data encryption unit, 6: encrypted data Storage unit, 7, 47: data decoding unit, 8: random number generation unit, 10, 40: fingerprint sensor, 46: fingerprint feature data storage unit, 48: fingerprint feature extraction unit, 41: Fingerprint collation unit.

Claims (11)

[Claims] 1. An information processing method for encrypting and decrypting data, the information processing method comprising: a process of obtaining an invariant feature amount from input biometric data; and an encryption process based on the feature amount. A process of calculating a key used for a decryption process, a process of encrypting data using the key, and a process of obtaining the feature amount from biometrics data newly input when decrypting the data, An information processing method comprising: a process of calculating a key used for encryption / decryption processing based on the feature amount; and a process of decrypting data using the key. 2. The information processing method according to claim 1, wherein each time a key used for encryption / decryption processing is calculated based on the feature amount, a process of generating a random number, and a key used for encryption / decryption process using the random number is performed. The information processing method according to claim 1, further comprising: calculating. 3. The information processing method according to claim 1, further comprising: reading a character string input by a user when calculating a key used for encryption / decryption processing based on the feature amount; and performing decryption using the character string. The information processing method according to claim 1, further comprising: calculating a key used for the processing. 4. An information processing method for performing personal authentication, the information processing method comprising: a biometric data input process for obtaining biometric data; and an eigenvalue calculation process for obtaining an invariant feature amount from the biometric data. An encryption key calculation process for obtaining an encryption key based on the feature amount; a feature extraction processing unit for extracting collation feature data from the biometric data; and decrypting the feature data using the encryption key. An information processing method, comprising: performing data encryption / decryption processing to perform decryption processing; and performing verification processing for verifying decrypted characteristic data against characteristic data extracted from newly input biometrics data. 5. The information processing method according to claim 1, wherein the biometrics data is image data of a fingerprint of a finger. 6. An information processing apparatus for encrypting and decrypting data, the information processing apparatus comprising: a biometrics data input unit for inputting biometrics data; and an invariant feature value from the biometrics data. An eigenvalue calculation unit to obtain, an encryption key calculation unit to obtain an encryption key based on the feature amount, and a data encryption / decryption unit to decrypt the data using the encryption key. Processing equipment. 7. The information processing apparatus according to claim 6, wherein the information processing apparatus further includes a random number generation unit that generates a random number used for obtaining an encryption key by calculation each time encryption is performed. apparatus. 8. The encryption key calculation unit reads an arbitrary character string input by a user when obtaining an encryption key by calculation, and obtains an encryption key based on the character string and the feature amount. The information processing device according to claim 6. 9. A biometrics data input unit for obtaining biometrics data, an eigenvalue calculating unit for obtaining an invariant feature value from the biometrics data, an encryption key calculating unit for obtaining an encryption key based on the feature value, A feature extraction unit that extracts matching feature data from the biometrics data, a data encryption / decryption unit that encrypts / decrypts the feature data using the encryption key, and biometrics newly input with the decrypted feature data. An information processing apparatus, comprising: a matching unit that performs matching with feature data extracted from data. 10. A computer-readable recording medium on which an information processing program for encrypting and decrypting data is recorded, wherein the information processing program obtains an invariant feature amount from input biometrics data. A process of calculating a key used for encryption / decryption processing based on the feature amount; a process of encrypting data using the key; and a newly input biometrics data at the time of data decryption. , A process of calculating a key used for an encryption / decryption process based on the feature amount, and a process of decoding data using the key. Recording medium on which an information processing program is recorded. 11. A computer-readable recording medium recording an information processing program for performing personal authentication, the information processing program comprising: a biometrics data inputting process for obtaining biometrics data; An eigenvalue calculation process for obtaining an invariant feature amount; an encryption key calculation process for obtaining an encryption key based on the feature amount; a feature extraction processing unit for extracting matching feature data from the biometric data; and using the encryption key. A data encryption / decryption process for encrypting / decrypting the feature data, and a matching process for matching the decrypted feature data with feature data extracted from newly input biometrics data. A recording medium on which an information processing program characterized by the following is recorded.