CN109787775B - Security authentication method based on Chen chaos system and finger vein auxiliary data - Google Patents
Security authentication method based on Chen chaos system and finger vein auxiliary data Download PDFInfo
- Publication number
- CN109787775B CN109787775B CN201910170057.9A CN201910170057A CN109787775B CN 109787775 B CN109787775 B CN 109787775B CN 201910170057 A CN201910170057 A CN 201910170057A CN 109787775 B CN109787775 B CN 109787775B
- Authority
- CN
- China
- Prior art keywords
- finger vein
- user
- image
- authentication
- auxiliary data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Landscapes
- Collating Specific Patterns (AREA)
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
Abstract
The invention discloses a security authentication method based on a Chen chaos system and finger vein auxiliary data, and belongs to the technical field of biological feature security and cryptography. The method comprises the following steps: acquiring a user finger vein image, extracting a global feature template, and storing the centroid position of the finger vein image; scrambling the pixel position of the global feature template by using Arnold Cat transformation; the finger vein auxiliary data is combined with a Chen chaos system to encrypt the pixel gray value of the global characteristic template; and completing the encrypted finger vein global feature template matching in the encrypted domain. The invention ensures the confidentiality and the integrity of finger vein information and the feasibility of a system, provides the function of scrambling the pixel position of the finger vein characteristic template and encrypting the pixel gray value of the finger vein characteristic template, and effectively enhances the capability of the finger vein characteristic template in resisting correlation coefficient analysis and resisting statistical analysis attack; the encryption process combines auxiliary data, has larger key space, and can be realized on various finger vein-based identity authentication systems.
Description
Technical Field
The invention belongs to the technical field of biological feature safety and cryptography, and particularly relates to a safety authentication method based on a Chen's chaotic system and finger vein auxiliary data.
Background
The finger vein is a biological feature located under the epidermis of the finger, is difficult to physically steal, and cannot be changed due to the change of the external environment and the epidermis of the skin. The non-contact acquisition device has no harm to human bodies, and finger vein files acquired by acquisition are small and the matching speed is high. The above characteristics make the biometric technology more widely applied to identity authentication.
Finger vein auxiliary data, finger vein characteristic information from the user. The total amount of information of the finger vein auxiliary data is far less than the total amount of information of the finger vein characteristics, and the finger vein auxiliary data does not reveal any remarkable information about the finger vein characteristics of the user, and can be generated and reconstructed by utilizing the key in encryption.
In recent years, the chaotic system is developed from simple to complex, and compared with the traditional cryptographic encryption algorithm, the chaotic system is more sensitive to an initial value, even the initial value is slightly changed, and correspondingly generated chaotic sequences are greatly different; the chaotic system has internal randomness and complex behaviors and ergodicity which are difficult to predict and analyze; the signal generated by the chaotic system has statistical information similar to white noise and can be regarded as a pseudo-random signal.
If a finger vein information is applied to an identity authentication system in a plaintext form without any encryption operation, the finger vein information is extremely vulnerable to a malicious attacker. The attacker can easily acquire the information related to the identity authentication, thereby forging false user identity and destroying the security of the identity authentication system. Therefore, an effective and safe finger vein authentication scheme is a necessary research direction under the eye.
"biomeric Data Encryption 3-D Chartic System" was proposed in 2016 by Garima Mehta and Malay Kishore Dutta. In the biometric data encryption scheme proposed by the users, the iris feature template information of the users is encrypted by a method of scrambling pixel positions and replacing pixel gray values. Although the method has larger key space, can resist partial attack and has certain security, the scheme still has some defects. The keys used to generate and reconstruct the encryption matrix are generated entirely by the system, being uncorrelated with the user's own biometric information so that the scheme can be replaced by other schemes that are functionally similar. And the size of the encryption matrix used in the pixel gray value replacement is different from that of the original iris characteristic template, and once the encryption matrix is cracked, the protection scheme has the risk of being broken.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a security authentication method based on a Chen chaos system and finger vein auxiliary data, which can effectively avoid the danger of being broken in the prior art and improve the reliability and the security of finger vein identification.
A safety authentication method based on a Chen's chaotic system and finger vein auxiliary data comprises the following steps:
step 1: acquiring a user finger vein image, extracting a global feature template, and storing the centroid position of the finger vein image;
step 2: scrambling the pixel position of the global feature template by using Arnold Cat transformation;
and step 3: the finger vein auxiliary data is combined with a Chen chaos system to encrypt the pixel gray value of the global characteristic template;
and 4, step 4: and completing the matching of the encrypted finger vein global feature template in the encrypted domain.
Further, the step 1 specifically comprises the following steps:
step 1.1, acquiring an original finger vein image of a user, calculating to obtain the centroid position of the image, and storing the centroid position in a database; completing the rotation correction of the original image by using the centroid position information; acquiring an ROI (region of interest) image of the finger vein through the sub-window;
the centroid position information is used for completing rotation correction of the image by using the information in the image processing part; in the user authentication process, whether correct auxiliary data in a database is acquired or not is determined by judging whether the distance between two centroid positions acquired in registration and authentication is within a set threshold value or not so as to generate a correct encryption matrix;
step 1.2, extracting a finger vein global feature template from a current ROI image by using a Niblack algorithm; filtering, filling and image thinning are carried out on the global feature template, and finally the global feature template is normalized into a 64 x 96 image matrix which is set as: F.
further, the step 2 is specifically as follows:
step 2.1: cutting a 64 × 96 global feature template F to obtain 3 square sub-feature templates with sizes of 64 × 64, 32 × 32, and 32 × 32, respectively, and setting as: f1,F2,F3；
Step 2.2: randomly extracting 4 pixel positions in the current ROI image to obtain the corresponding pixel gray value set as f1,f2,f3,f4(ii) a Generating 4 ranges using a random number generator [1,10000 ]]Internal randomThe number is set as: r is1,r2,r3,r4(ii) a Will f is1,f2,f3,f4And r1,r2,r3,r4Corresponding multiplication by a1＝f1×r1,b1＝f2×r2,c1＝f3×r3,d1＝f4×r4Forming a 2 x 2 matrix by the obtained results, and regenerating the matrix if the determinant result of the matrix needs to be 1; this step is repeated 3 times, obtaining 32 × 2 independent transformation matrices, and setting as: t is1,T2,T3；
Step 2.3: the user is prompted to enter 3 iterations, set as: k is a radical of1,k2,k3The value range is [1,10 ]8-1]，k1,k2,k3Considered the first key set, set to K1 (K)1,k2,k3) The user can keep the information;
the user needs to correctly input the 3 iteration times during authentication, if the input is wrong, a subsequent result is wrong, and finally the authentication fails;
step 2.4, correspondingly entering the obtained 3 sub-feature templates, 3 transformation matrixes and 3 iteration times into Arnold Cat transformation respectively; splicing the transformed 3 sub-feature templates into a 64 x 96 transformed global feature template again, and setting as follows: FT1。
Further, the step 3 is specifically as follows:
step 3.1: randomly generating 8 row values and 8 column values, and setting as: n is1,n2,n3,n4,n5,n6,n7,n8And m1,m2,m3,m4,m5,m6,m7,m8The range of row and column values is determined by the size of the current finger vein ROI image; and acquiring corresponding 8 pixel gray values in the current ROI image according to the row and column values, and setting the gray values as: g (n)1,m1),g(n2,m2),g(n3,m3),g(n4,m4),g(n5,m5),g(n6,m6),g(n7,m7),g(n8,m8)；
Step 3.2: converting the currently obtained 8 gray values into binary numbers with 8 bits, and splicing every two gray values back and forth to form 4 binary numbers with 16 bits, wherein the binary numbers are set as follows: q. q.s1,q2,q3,q4；x0＝q1⊕q2⊕q3⊕q4，x0As a first initial value for entering the Chen chaos system;
x is to be0Binary number expressed as 16 bits: x is the number of0＝x01 x02 x03…x014 x015 x016，x0Circularly left-shifted by one bit to obtain a second initial value y0＝x016 x01 x02 x03…x014 x015Circularly left-shifting two bits to obtain a third initial value z0＝x015 x016 x01 x02 x03…x014；
(x0,y0,z0) Considered as a second key set, set to K2 (x)0,y0,z0)；
Step 3.3: initial value (x) to be obtained0,y0,z0) Substituting into the Chen chaos mapping, iterating for 192 times to obtain a corresponding chaos sequence group, and setting as follows: (L)1,L2,L3) (ii) a Wherein L is1,L2,L3Each represents a group of chaotic sequences, and the number of elements of each group of sequences is 192;
step 3.4: retention of L1,L2,L3，L4＝L1⊕L2⊕L3Is prepared by mixing L1,L2,L3,L4All elements in the encryption matrix are arranged to form a sub-encryption matrix with the size of 8 multiplied by 96;
step 3.5: repeating the 4 steps for 8 times to obtain 8 sub-encryption matrixes with the size of 8 multiplied by 96, and splicing all the sub-encryption matrixes to obtain an encryption matrix E with the size of 64 multiplied by 96 for replacing the gray value of the pixel;
step 3.6: prompting the user to input a storage password ps for storing 64 pairs of row and column values, so that the user can conveniently extract the password in authentication; in addition, 64 gray values are additionally stored, and a user can not directly extract when inputting a password during authentication;
step 3.7: global feature FT of finger vein with scrambled pixel position1And (3) carrying out XOR on the template and the encryption matrix E: FE1＝FT1^ E, obtain the characteristic template FE with the encrypted gray value1And the data is stored in a database, so that the data is convenient for matching in authentication, and the user registration is completed.
Further, the step 3 comprises:
step 3.8: when the user is authenticated, the user is prompted to input the password ps storing information during registration, and the current input password ps' is judged to be correct. If the password ps' is correct, extracting 64 row and column values stored in the database; such as password ps' error, the current authentication process is terminated.
Further, the step 3 comprises:
step 3.9: calculating the distance between the centroid position of the finger vein image obtained in the authentication process and the centroid position stored in the database, wherein the distance unit is represented by the number of elements;
step 3.10: judging whether the distance is within a set threshold value; if the distance between the two centroid positions is in [0,3], extracting 64 gray values stored in a database during registration, and directly using the auxiliary data to form an encryption matrix; if the current position is not in [0,3], acquiring a gray value in the current ROI image according to the corresponding position by using the extracted 64 row values and column values to generate an encryption matrix and prompting a user that the finger vein information currently processed is possibly wrong;
step 3.11: the current generated encryption matrix E ' and the feature template FT ' subjected to current completion position scrambling '1Exclusive or: FE'1＝FT′1E ' is obtained, and the global feature template FE ' with the gray value encrypted in the authentication process is obtained '1。
Further, the expression of the Chen chaos mapping is as follows:
further, in step 3.3, a first modulo operation is performed on the result of each iteration, and the modulus is 2048; after the iteration is completed, in order to ensure that the iteration data can be fully utilized, L is added1,L2,L3Is modulo 256 a second time so that the final data is all distributed over 0,255]Among them.
Further, the step 4 is specifically as follows:
step 4.1: FE 'is calculated over an encrypted domain'1And FE1The distance unit is expressed by the number of elements;
step 4.2: judging whether the distance is within a set threshold value; if the distance is in [0,1], the user authentication is successful; if not in [0,1], the user authentication fails.
The invention has the beneficial effects that: the invention provides a security authentication scheme based on a Chen's chaotic system and finger vein auxiliary data, provides a method for indirectly generating a secret key and protecting the security of original finger vein characteristic information for various identity authentication systems based on finger vein characteristics, and ensures the confidentiality and integrity of finger vein information and the feasibility of the system. The invention provides the function of setting the pixel position of the disordered finger vein characteristic template and encrypting the pixel gray value of the finger vein characteristic template, thereby effectively enhancing the capability of the finger vein characteristic template in resisting correlation coefficient analysis and resisting statistical analysis attack; incorporating auxiliary data in the encryption process, with a large key space (about 3.4 x 10)62). The method can be used in all systems with finger vein identity authentication, and has strong popularization.
Drawings
FIG. 1 is a flow chart of a security authentication scheme based on a Chen chaos system and finger vein auxiliary data;
FIG. 2 is a schematic diagram of an authentication failure resulting from an input of a wrong number of iterations;
FIG. 3 is a schematic diagram of user registration success;
FIG. 4 is a schematic diagram of vein centroid distance mismatch leading to authentication failure;
fig. 5 is a schematic diagram of the user inputting correct data to pass identity authentication.
Detailed Description
The technical scheme of the invention is further explained by combining the drawings in the specification.
A security authentication method based on a Chen's chaotic system and finger vein auxiliary data is shown in figure 1 and comprises the steps of obtaining a user finger vein image, extracting a global feature template and storing the centroid position information of the finger vein image; scrambling the pixel position of the global feature template by using Arnold Cat transformation; the finger vein auxiliary data is combined with a Chen chaos system to encrypt the pixel gray value of the global characteristic template; storing the encrypted characteristic template for template matching during authentication; and prompting the user to input a storage password and storing corresponding data. During authentication, comparing the distance between the currently obtained centroid position and the centroid position obtained during registration, and judging whether auxiliary data are directly extracted for reconstructing an encryption matrix; the encrypted feature template matching is done in the encrypted domain.
1. The user finger vein global feature template extraction part comprises the following specific steps:
1.1, acquiring an original finger vein image of a user, calculating the centroid position of the image, and storing the centroid position of the finger vein image in a database; completing the rotation correction of the original image by using the centroid position information; an ROI (region of interest) image of the finger vein is acquired through the sub-window.
The centroid position information is used for completing rotation correction of the image by using the information in the image processing part; in the user authentication process, whether correct auxiliary data in a database is acquired or not is judged by judging whether the distance between the registered 2 mass center information acquired by authentication is within a set threshold value or not, so that a correct encryption matrix is generated. The use of the centroid location information effectively reduces the false rejection rate in the authentication process.
1.2, extracting a finger vein global feature template from the obtained finger vein ROI image by using a Niblack algorithm; and filtering, filling and image thinning are carried out on the extracted global feature template, and finally the global feature template is normalized into a 64 x 96 image matrix which is set as F. According to the experience, the invention recommends setting the window size to be 4 and the coefficient to be 0.05 in the Niblack algorithm.
2. The Arnold Cat transform scrambling refers to the position of a vein global feature template pixel, and the method comprises the following specific steps:
2.1 cutting 64 × 96 finger vein global feature template F to obtain 3 square sub-feature templates with sizes of 64 × 64, 32 × 32 and 32 × 32, and setting the sub-feature templates as F1,F2,F3。
2.2 randomly extracting 4 pixel positions in the finger vein ROI image, obtaining the corresponding pixel gray value, and setting as: f. of1,f2,f3,f4(ii) a Generating 4 ranges using a random number generator [1,10000 ]]The random number in (2) is set as: r is1,r2,r3,r4(ii) a Will f is1,f2,f3,f4And r1,r2,r3,r4Corresponding multiplication by a1＝f1×r1,b1＝f2×r2,c1＝f3×r3,d1＝f4×r4The results are organized into a 2 x 2 matrix.
Since the Arnold Cat mapping, now commonly used, is shown by the following expression:
wherein x isn，ynFor the gray scale position of the pixel, M is the size of the image being processed, a, b, c, d satisfy the following condition:
if the 2 x 2 determinant satisfies determinant (2), then the matrix is considered to be a valid transformation matrix; if the determinant (2) is not satisfied, the matrix is regenerated untilThe condition of the determinant (2) is satisfied. This step was repeated 3 times to obtain 32 × 2 independent transformation matrices, set as T1,T2,T3。
2.3 prompt the user to enter 3 iterations, set as: k is a radical of1,k2,k3The value range is [1,10 ]8-1]，k1,k2,k3Considered the first key set, set to K1 (K)1,k2,k3) And the user can take care of the information.
The user needs to correctly input the 3 iteration times during authentication, if the input is wrong, a subsequent result will be wrong, and finally the authentication fails as shown in fig. 2.
2.4 correspondingly entering the obtained 3 sub-feature templates, 3 transformation matrixes and 3 iteration times into Arnold Cat transformation respectively; re-splicing the transformed 3 sub-feature templates into a 64 x 96 transformed global feature template set as FT1。
The purpose of this step is to destroy the correlation between the original feature template data, resist the attack of correlation coefficient, and achieve the basic visual confusion purpose.
However, since the Arnold Cat mapping in the form of expression (1) is easy to generate a cycle, this means that if an attacker tries to input different iterations frequently through an exhaustive method, it is likely that a forged feature template will be generated, and after the Arnold Cat transformation, a part of the forged feature template will be the original correct transformation result. Furthermore, since scrambling the pixel positions does not substantially affect the pixel gray scale values, the transformed feature template still cannot resist the statistical analysis attack, and therefore the encryption operation is performed on the pixel gray scale values of the feature template to ensure the security of the finger vein information of the user.
3. The finger vein auxiliary data is combined with the pixel gray value of the encryption characteristic template of the Chen chaos system.
3.1 randomly generating 8 Row values and 8 column values, set to n1,n2,n3,n4,n5,n6,n7,n8And m1,m2,m3,m4,m5,m6,m7,m8The range of row and column values is determined by the size of the current finger vein ROI image; and acquiring corresponding 8 pixel gray values in the current ROI image according to the row and column values, and setting the gray values as: g (n)1,m1),g(n2,m2),g(n3,m3),g(n4,m4),g(n5,m5),g(n6,m6),g(n7,m7),g(n8,m8)。
Since the number of pixels in the ROI image is much larger than 8, arbitrarily obtaining 8 pixel gray values does not reveal any significant information about the user's finger vein features, and these pixel gray values can be regarded as auxiliary data, which is used to generate a key for subsequent encryption.
3.2 convert the currently obtained 8 gray values into 8-bit binary numbers, and splice two by two to form 4 16-bit binary numbers, which are set as: q. q.s1,q2,q3,q4；x0＝q1⊕q2⊕q3⊕q4，x0As the first initial value for entering the chen chaos system.
X is to be0Binary number expressed as 16 bits: x is the number of0＝x01 x02 x03…x014 x015 x016 ,x0Circularly left-shifted by one bit to obtain a second initial value y0＝x016 x01 x02 x03…x014 x015Circularly left-shifted by two bits to obtain a third initial value z0＝x015 x016 x01 x02 x03…x014。
x0,y0,z0Considered as a second key set, set to K2 (x)0,y0,z0)。
The Chen chaotic system used in the method belongs to a three-dimensional chaotic system, and 3 initial values are required to enter chaotic mapping to generate a corresponding chaotic sequence. Compared with a commonly used one-dimensional chaotic system, the Chen chaotic system can realize rapid diffusion, has higher randomness and unpredictability, and has larger key space, thereby having stronger attack resistance. The expression of the Chen chaos mapping used in this scheme is as follows:
3.3 initial value (x) to be obtained0,y0,z0) Substituting into the Chen chaos mapping, iterating for 192 times to obtain a corresponding chaos sequence group, and setting as follows: (L)1,L2,L3). Wherein L is1,L2,L3Each representing a group of sequences, each group of sequences having 192 elements.
In the calculation, in order to avoid the generation of data which is too large and exceeds the computer operation capacity, the first modulus operation is carried out on the result of each iteration, and the modulus is 2048; after the iteration is completed, in order to ensure that the iteration data can be fully utilized, L is added1,L2,L3Each element in (a) is modulo 256 a second time. Thus, the final data are all distributed in [0,255 ]]Among them.
3.4 Retention of L1,L2,L3。L4＝L1⊕L2⊕L3Is prepared by mixing L1,L2,L3,L4All the elements in the array form a sub-encryption matrix with the size of 8 multiplied by 96.
3.5 repeating the above 4 steps 8 times to obtain 8 sub-encryption matrixes with the size of 8 × 96, and splicing all the sub-encryption matrixes to obtain an encryption matrix E for replacing the gray value of the pixel. The matrix E is 64 × 96 in size.
3.6 prompting the user to input a storage password ps which is used for storing 64 pairs of row and column values, so that the user can conveniently extract the values during authentication; in addition, 64 gray values are additionally stored, and the user cannot directly extract the input password ps at the time of authentication.
3.7 finger vein Global feature template FT to scramble pixel positions1Exclusive or with encryption matrix E: FE1＝FT1^ E, obtain after encryptingFeature template FE of1. The data is stored in a database, so that the data can be conveniently matched during authentication.
By this time the user registration function is completed, a display window informs that the current registration was successful as shown in fig. 3.
In the user authentication, the steps of extracting the finger vein feature template and scrambling the pixel position of the feature template are the same as those in the registration, but the whole process of generating the encryption matrix is slightly different. Due to the influence of noise, collection angle and other factors, the gray value of the image generated by the same finger vein of the same user in each collection has a certain slight deviation.
Obtaining corresponding gray value in the current ROI image according to 64 row-column values in the database, and reconstructing the initial value x by using the gray value0′,y0′,z0', to form a new encryption matrix E'. According to the sensitive dependency of the chaotic system on the initial value, due to the difference of the initial value, the chaotic sequence is greatly different compared with the chaotic sequence generated during registration, and the generated E' is certainly greatly different from the encryption matrix E generated during registration. This can cause the present scheme to have an extremely high false reject rate in authentication.
3.8 when the user is authenticated, firstly, the user is prompted to input the password ps of the stored information during registration, and the currently input password ps' is judged to be correct. If the password ps' is correct, extracting 64 row and column values stored in the database; such as password ps' error, the current authentication process is terminated.
3.9 calculating the distance between the centroid position of the finger vein image obtained in the authentication process and the centroid position stored in the database, wherein the distance unit is expressed by the number of elements.
3.10 if the distance between the two centroid positions is in the threshold value [0, mu ], extracting 64 gray values stored in a database during registration, and directly using the auxiliary data to form an encryption matrix; if the current position is not in the threshold [0, mu ], acquiring a gray value in the current ROI image according to the corresponding position by using the extracted 64 row and column values to generate an encryption matrix and prompting a user that the currently processed finger vein information may be incorrect as shown in FIG. 4. Empirically, the recommended threshold is set to [0,3 ].
3.11 feature template FT 'scrambled with current completed position by currently generated encryption matrix E'1Exclusive or: FE'1＝FT′1E ' is obtained, and the global feature template FE ' with the gray value encrypted in the authentication process is obtained '1。
4. Template matching in encrypted domain
4.1 because the encryption operation on the grey values is to use the feature template FT1And the encryption matrix E is subjected to XOR, so that in the matching process of user authentication, the distance between the two encrypted feature templates is calculated on the encryption domain.
4.2 if the distance is within the threshold set by the scheme, the user authentication is successful as shown in fig. 5; otherwise, the user authentication fails. From experience, the recommendation threshold is set to [0,1 ].
The security authentication scheme based on the Chen chaos system and the finger vein auxiliary data is not limited to the description in the specification and the implementation mode. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the scope of the claims of the present invention.
Claims (8)
1. A safety authentication method based on a Chen's chaotic system and finger vein auxiliary data is characterized by comprising the following steps:
step 1: acquiring a user finger vein image, extracting a global feature template, and storing the centroid position of the finger vein image;
step 2: scrambling the pixel position of the global feature template by using Arnold Cat transformation;
and step 3: the finger vein auxiliary data is combined with a Chen chaos system to encrypt the pixel gray value of the global characteristic template; the step 3 is specifically as follows:
step 3.1: randomly generating 8 row values and 8 column values, and setting as: n is1,n2,n3,n4,n5,n6,n7,n8And m1,m2,m3,m4,m5,m6,m7,m8The range of row and column values is determined by the current finger veinDetermining the size of the ROI image; and acquiring corresponding 8 pixel gray values in the current ROI image according to the row and column values, and setting the gray values as: g (n)1,m1),g(n2,m2),g(n3,m3),g(n4,m4),g(n5,m5),g(n6,m6),g(n7,m7),g(n8,m8)；
Step 3.2: converting the currently obtained 8 gray values into binary numbers with 8 bits, and splicing every two gray values back and forth to form 4 binary numbers with 16 bits, wherein the binary numbers are set as follows: q. q.s1,q2,q3,q4；
x0As a first initial value for entering the Chen chaos system;
x is to be0Binary number expressed as 16 bits: x is the number of0＝x01 x02 x03 … x014 x015 x016，x0Circularly left-shifted by one bit to obtain a second initial value y0＝x016 x01 x02 x03 … x014 x015Circularly left-shifting two bits to obtain a third initial value z0＝x015 x016 x01 x02 x03 … x014；
(x0,y0,z0) Considered as a second key set, set to K2 (x)0,y0,z0)；
Step 3.3: initial value (x) to be obtained0,y0,z0) Substituting into the Chen chaos mapping, iterating for 192 times to obtain a corresponding chaos sequence group, and setting as follows: (L)1,L2,L3) (ii) a Wherein L is1,L2,L3Each represents a group of chaotic sequences, and the number of elements of each group of sequences is 192;
step 3.4: retention
Mixing L with1,L2,L3,L4All elements in the encryption matrix are arranged to form a sub-encryption matrix with the size of 8 multiplied by 96;
step 3.5: repeating the steps 3.1-3.4 for 8 times to obtain 8 sub-encryption matrixes with the size of 8 multiplied by 96, and splicing all the sub-encryption matrixes to obtain an encryption matrix E with the size of 64 multiplied by 96 for replacing the gray value of the pixel;
step 3.6: prompting the user to input a storage password ps for storing 64 pairs of row and column values, so that the user can conveniently extract the password in authentication; in addition, 64 gray values are additionally stored, and a user can not directly extract when inputting a password during authentication;
step 3.7: global feature FT of finger vein with scrambled pixel position1And (3) carrying out XOR on the template and the encryption matrix E: FE1＝FT1^ E, obtain the characteristic template FE with the encrypted gray value1The data is stored in a database, so that the data is convenient for matching during authentication, and the user registration is completed;
and 4, step 4: and completing the matching of the encrypted finger vein global feature template in the encrypted domain.
2. The method for security authentication based on the Chen's chaotic system and the finger vein auxiliary data according to claim 1, wherein the step 1 is as follows:
step 1.1, acquiring an original finger vein image of a user, calculating to obtain the centroid position of the image, and storing the centroid position in a database; completing the rotation correction of the original image by using the centroid position information; obtaining an ROI image of the finger vein through the sub-window;
the centroid position information is used for completing rotation correction of the image by using the information in the image processing part; in the user authentication process, whether correct auxiliary data in a database is acquired or not is determined by judging whether the distance between two centroid positions acquired in registration and authentication is within a set threshold value or not so as to generate a correct encryption matrix;
step 1.2, extracting a finger vein global feature template from a current ROI image by using a Niblack algorithm; filtering, filling and image thinning are carried out on the global feature template, and finally the global feature template is normalized into a 64 x 96 image matrix which is set as: F.
3. the method for security authentication based on the Chen's chaotic system and the finger vein auxiliary data according to claim 2, wherein the step 2 is as follows:
step 2.1: cutting a 64 × 96 global feature template F to obtain 3 square sub-feature templates with sizes of 64 × 64, 32 × 32, and 32 × 32, respectively, and setting as: f1,F2,F3；
Step 2.2: randomly extracting 4 pixel positions in the current ROI image to obtain the corresponding pixel gray value set as f1,f2,f3,f4(ii) a Generating 4 ranges using a random number generator [1,10000 ]]The random number in (2) is set as: r is1,r2,r3,r4(ii) a Will f is1,f2,f3,f4And r1,r2,r3,r4Corresponding multiplication by a1＝f1×r1,b1＝f2×r2,c1＝f3×r3,d1＝f4×r4Forming a 2 x 2 matrix by the obtained results, and regenerating the matrix if the determinant result of the matrix needs to be 1; this step is repeated 3 times, obtaining 32 × 2 independent transformation matrices, and setting as: t is1,T2,T3；
Step 2.3: the user is prompted to enter 3 iterations, set as: k is a radical of1,k2,k3The value range is [1,10 ]8-1]，k1,k2,k3Considered the first key set, set to K1 (K)1,k2,k3) The user can keep the information;
the user needs to correctly input the 3 iteration times during authentication, if the input is wrong, a subsequent result is wrong, and finally the authentication fails;
step 2.4, correspondingly entering the obtained 3 sub-feature templates, 3 transformation matrixes and 3 iteration times into Arnold Cat transformation respectively; will becomeSplicing the changed 3 sub-feature templates into a 64 x 96 transformed global feature template again, and setting as follows: FT1。
4. The method for security authentication based on the Chen's chaotic system and the finger vein auxiliary data according to claim 1, wherein the step 3 comprises:
step 3.8: when the user is authenticated, prompting the user to input a password ps for storing information during registration, and judging that the current input password ps' is correct; if the password ps' is correct, extracting 64 row and column values stored in the database; such as password ps' error, the current authentication process is terminated.
5. The method according to claim 4, wherein the step 3 comprises:
step 3.9: calculating the distance between the centroid position of the finger vein image obtained in the authentication process and the centroid position stored in the database, wherein the distance unit is represented by the number of elements;
step 3.10: judging whether the distance is within a set threshold value; if the distance between the two centroid positions is in [0,3], extracting 64 gray values stored in a database during registration, and directly using the auxiliary data to form an encryption matrix; if the current position is not in [0,3], acquiring a gray value in the current ROI image according to the corresponding position by using the extracted 64 row values and column values to generate an encryption matrix and prompting a user that the finger vein information currently processed is possibly wrong;
step 3.11: the current generated encryption matrix E ' and the feature template FT ' subjected to current completion position scrambling '1Exclusive or:
obtaining a global feature template FE 'with the gray value encrypted in the authentication process'1。
6. The method for the security authentication based on the Chen chaos system and the finger vein auxiliary data according to claim 1, wherein the Chen chaos mapping expression is as follows:
7. the method according to claim 1, wherein in step 3.3, the first modulo operation is performed on the result of each iteration, and the modulo is 2048; after the iteration is completed, in order to ensure that the iteration data can be fully utilized, L is added1,L2,L3Is modulo 256 a second time so that the final data is all distributed over 0,255]Among them.
8. The method for security authentication based on the Chen's chaotic system and the finger vein auxiliary data according to claim 1, wherein the step 4 is as follows:
step 4.1: FE 'is calculated over an encrypted domain'1And FE1The distance unit is expressed by the number of elements;
step 4.2: judging whether the distance is within a set threshold value; if the distance is in [0,1], the user authentication is successful; if not in [0,1], the user authentication fails.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910170057.9A CN109787775B (en) | 2019-03-06 | 2019-03-06 | Security authentication method based on Chen chaos system and finger vein auxiliary data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910170057.9A CN109787775B (en) | 2019-03-06 | 2019-03-06 | Security authentication method based on Chen chaos system and finger vein auxiliary data |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109787775A CN109787775A (en) | 2019-05-21 |
| CN109787775B true CN109787775B (en) | 2021-10-22 |
Family
ID=66486280
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910170057.9A Active CN109787775B (en) | 2019-03-06 | 2019-03-06 | Security authentication method based on Chen chaos system and finger vein auxiliary data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109787775B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113034139B (en) * | 2021-03-15 | 2023-12-26 | 中国人民大学 | Block chain multi-coin wallet based on living organism biological characteristic authentication and implementation method thereof |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103731271A (en) * | 2013-12-30 | 2014-04-16 | 北京工业大学 | On-line face identity authentication method based on homomorphic encrypting and chaotic scrambling |
| CN107169444A (en) * | 2017-05-11 | 2017-09-15 | 重庆科技学院 | Finger vein recognition system and method based on smart mobile phone separating treatment |
| CN109190509A (en) * | 2018-08-13 | 2019-01-11 | 阿里巴巴集团控股有限公司 | A kind of personal identification method, device and computer readable storage medium |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10269119B2 (en) * | 2015-12-07 | 2019-04-23 | Avigilon Analytics Corporation | System and method for background and foreground segmentation |
-
2019
- 2019-03-06 CN CN201910170057.9A patent/CN109787775B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103731271A (en) * | 2013-12-30 | 2014-04-16 | 北京工业大学 | On-line face identity authentication method based on homomorphic encrypting and chaotic scrambling |
| CN107169444A (en) * | 2017-05-11 | 2017-09-15 | 重庆科技学院 | Finger vein recognition system and method based on smart mobile phone separating treatment |
| CN109190509A (en) * | 2018-08-13 | 2019-01-11 | 阿里巴巴集团控股有限公司 | A kind of personal identification method, device and computer readable storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 《Biometric Data Encryption using 3-D Chaotic System》;Garima Mehta; Malay Kishore Dutta; Pyung SooKim;《2016 2nd International Conference on Communication Control and Intelligent Systems (CCIS)》;20170316;正文第1页至第4页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109787775A (en) | 2019-05-21 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Lee et al. | Biometric key binding: Fuzzy vault based on iris images | |
| Uludag et al. | Biometric cryptosystems: issues and challenges | |
| Lee et al. | A new method for generating an invariant iris private key based on the fuzzy vault system | |
| CA2780717C (en) | A method of assigning a secret to a security token, a method of operating a security token, storage medium and security token | |
| Maiorana | Biometric cryptosystem using function based on-line signature recognition | |
| Leng et al. | Dual-key-binding cancelable palmprint cryptosystem for palmprint protection and information security | |
| Mehta et al. | An efficient and lossless fingerprint encryption algorithm using Henon map & Arnold transformation | |
| Ranjan et al. | Improved and innovative key generation algorithms for biometric cryptosystems | |
| Kaur et al. | Template and database security in Biometrics systems: A challenging task | |
| CN109787775B (en) | Security authentication method based on Chen chaos system and finger vein auxiliary data | |
| Lacharme et al. | PIN-based cancelable biometrics | |
| Murillo-Escobar et al. | Secure access microcontroller system based on fingerprint template with hyperchaotic encryption | |
| Ziauddin et al. | Robust iris verification for key management | |
| Maček et al. | Mobile banking authentication based on cryptographically secured iris biometrics | |
| Nandini et al. | Efficient cryptographic key generation from fingerprint using symmetric hash functions | |
| CN116361774A (en) | Password cracking method and device | |
| Wilber et al. | PRIVV: Private remote iris-authentication with Vaulted Verification | |
| Maji et al. | A novel biometric template encryption scheme using sudoku puzzle | |
| Yang et al. | Non-invertible geometrical transformation for fingerprint minutiae template protection | |
| Gudavalli et al. | A template protection scheme for multimodal biometric system with fingerprint, palmprint, iris and retinal traits | |
| Trainys et al. | Encryption Keys Generation Based on Bio-Cryptography Finger Vein Method | |
| Fatima | Securing the biometric template: a survey | |
| Ajith et al. | Iris Cryptography for Security Purpose | |
| Sudhi et al. | Review paper on biometric template security | |
| Wang et al. | A new framework of Biometric encryption with filter-bank based fingerprint feature |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| EE01 | Entry into force of recordation of patent licensing contract | ||
| EE01 | Entry into force of recordation of patent licensing contract |
Application publication date: 20190521 Assignee: Zhejiang haomeng Technology Co.,Ltd. Assignor: HANGZHOU DIANZI University Contract record no.: X2022980024264 Denomination of invention: A security authentication method based on Chen's chaotic system and digital vein auxiliary data Granted publication date: 20211022 License type: Common License Record date: 20221202 |