Financial transaction system based on blockchain and big data
Technical Field
The invention relates to the technical field of financial transactions, in particular to a financial transaction system based on blockchain and big data.
Background
Along with the rapid development of internet technology, the internet gradually walks into people's life, brings huge facility for people, in the aspect of financial transaction, people only need through authentication just can realize financial transaction, authentication's mode also includes multiple, have password authentication, have fingerprint authentication, still face identification authentication, but in real life, people are comparatively often used still fingerprint authentication, but fingerprint authentication has certain limitation, if in the in-process of discernment, the condition that the blur appears in some fingerprints can be led to, make fingerprint matching failure's probability increase by a wide margin, and then influence user's payment experience.
For the above situation, a financial transaction system based on blockchain and big data is needed, when fingerprint information is acquired, finger information of a user is extracted, namely, not only the fingerprint information of the user is acquired, but also other aspect information of the finger of the user is included, and the user is assisted in fingerprint matching through the acquired other aspect information, so that fingerprint matching efficiency and accuracy are improved.
Disclosure of Invention
The present invention is directed to a financial transaction system based on blockchain and big data to solve the above-mentioned problems in the background art.
In order to solve the technical problems, the invention provides the following technical scheme: a blockchain and big data based financial transaction system, comprising: the user finger information acquisition module comprises a fingerprint password acquisition module and a finger secondary password acquisition module, the finger information verification module comprises a fingerprint password verification module and a finger secondary password verification module,
the fingerprint password acquisition module is used for acquiring fingerprint information of a user;
the finger secondary password acquisition module is used for acquiring the secondary password of the user finger, and the secondary password comprises: finger temperature T, finger bioelectric intensity I, and finger blood flow velocity V;
the fingerprint password verification module is used for matching the fingerprint information acquired by the fingerprint password acquisition module with the fingerprint information prestored by the user, solving the similarity c of the fingerprint information acquired by the fingerprint password acquisition module and the fingerprint information prestored by the user, judging the similarity c,
when c is larger than or equal to a first preset value, judging that the verification of the finger information of the user is successful,
when c is larger than or equal to the second preset value and smaller than the first preset value, executing the finger secondary password verification module,
when c is smaller than a second preset value, judging that the verification of the finger information of the user fails;
the finger secondary password verification module is used for comparing the secondary password of the user finger acquired by the finger secondary password acquisition module with the finger secondary password prestored by the user to judge whether the user finger information is successfully verified;
the transfer module is used for acquiring the judging result of the finger information verification module, judging whether to execute transfer operation according to the result of the user finger information verification,
the data generated in each module is stored in the form of a blockchain.
The invention realizes the verification of the collected finger information of the user through the cooperation of the modules, and further rapidly completes the matching of the finger information of the user.
Further, the fingerprint password acquisition module acquires fingerprint information of a user, wherein the fingerprint information comprises fingerprint patterns and fingerprint venation roughness of the finger,
the specific method for solving the fingerprint vein roughness is as follows:
s1.1, acquiring a fingerprint pattern of a finger;
s1.2, performing image binarization processing on a fingerprint image of a finger;
s1.3, counting the number b1 of black pixel points in the finger fingerprint image after the binarization processing of the image;
s1.4, dividing b2 by 2 to obtain the length b3 of the fingerprint venation in the finger fingerprint image, wherein the number b2 of black pixel points contacted with the outline of each fingerprint venation in the region of each fingerprint venation in the finger fingerprint image subjected to the binarization processing of the statistic image;
s1.5, dividing b1 obtained in the step S1.3 by b3 obtained in the step S1.4 to obtain a result which is the roughness b of the fingerprint venation, namely
When the fingerprint password acquisition module acquires fingerprint information, not only the fingerprint pattern of the finger is acquired, but also the fingerprint vein roughness is removed, because the fingerprint pattern and the fingerprint vein roughness of the finger both influence the fingerprint matching, when the corresponding value of the fingerprint vein roughness exceeds a certain range, the fingerprint pattern of the finger is blurred, the matching degree of the fingerprint matching is reduced, the fingerprint vein roughness is influenced by special environment, and when a user is immersed in water, the fingerprint vein roughness is increased. Because the fingerprint venation exists on the surface of the finger, the raised fingerprint venation firstly contacts the acquisition device, so that after the image binarization processing is carried out, the fingerprint venation area is represented by black pixel points, and other areas are represented by white pixel points, in the step S1.4, b2 represents the number of the black pixel points which are contacted with the outline of each fingerprint venation, the outline length is approximately equal to 2 times of the length b3 of the fingerprint venation in the fingerprint image of the finger, therefore, when b3 is obtained, b2 is divided by 2, b1 represents the total pixel points of the fingerprint venation in the fingerprint image of the finger, which is equivalent to the total area of the fingerprint venation in the fingerprint image of the finger, and b1 is divided by b3, so that the average thickness of the fingerprint venation in the fingerprint image of the finger can be obtained, namely the fingerprint venation thickness b.
Furthermore, when the finger contacts the acquisition equipment, the finger secondary password acquisition module acquires the secondary password through the corresponding sensor on the acquisition equipment,
the finger temperature is acquired by a temperature sensor on the acquisition equipment;
the finger bioelectric strength is acquired by a bioelectric sensor on the acquisition equipment;
the finger blood flow velocity is obtained by collecting data through a vibration sensor on the collecting device, calculating the product of the vibration value z and the blood flow coefficient f measured by the vibration sensor through different vibrations generated by different finger blood flow velocities, wherein the obtained product is the finger blood flow velocity V, namely V=f.z,
the blood flow coefficient f is a relation coefficient between the vibration frequency measured by the finger and the blood flow speed of the finger.
The finger secondary password acquisition module further acquires the blood flow velocity of the finger by acquiring the vibration frequency of the finger by utilizing the relation between the blood flow velocity of the finger and the vibration frequency.
Further, the fingerprint password verification module pre-stores fingerprint information of the user in advance, wherein the pre-stored fingerprint information comprises a fingerprint graph of the user finger and the thickness of the user fingerprint venation.
Furthermore, the fingerprint password verification module only compares the similarity of fingerprint patterns of the user fingers in the matching process, and the method for specifically solving the similarity in the matching process is as follows:
s2.1, marking a pre-stored fingerprint pattern of a user finger as c1, and marking the fingerprint pattern of the finger in the fingerprint information acquired by the fingerprint password acquisition module as c2;
s2.2, respectively carrying out image binarization processing on the c1 and the c2, respectively obtaining corresponding pixels of the central line corresponding to each fingerprint vein from the processed c1 and c2 through the contour position relation of each fingerprint vein, and marking the obtained corresponding pixels of the central line;
s2.3, respectively extracting the marked pixel points in the c1 and the c2, overlapping the c1 and the c2, and establishing a plane rectangular coordinate system by taking the midpoint of the overlapped c1 and c2 as an origin;
s2.4, respectively calculating the distance between the corresponding marked pixel points in the c1 and the c2, respectively comparing the obtained distance c3 with a third preset value,
when c3 is larger than or equal to a third preset value, the pixel point corresponding to c3 in c1 is marked for the second time,
when c3 is smaller than a third preset value, not processing the pixel point corresponding to c3 in c 1;
s2.5, counting the number c4 of the pixels marked by the c1 in the step S2.3 and the number c5 of the pixels marked by the c1 in the step S2.4 for the second time, dividing the c4 by the c5, and marking the obtained quotient as the similarity c between the acquired fingerprint information and the pre-stored fingerprint information of the user, namely
The fingerprint password verification module processes the fingerprint graph in an image binarization mode, can accurately extract fingerprint information, is more clear in fingerprint information, is favorable for matching the fingerprint information, can clearly identify the pixel points compared during fingerprint matching in a marking mode, and enables data processing to be more accurate and the determination of the coordinates of the pixel points to be more uniform in a same plane rectangular coordinate system mode.
Further, the finger secondary password verification module is required to obtain the fingerprint vein roughness b of the collected user finger before verifying the secondary password of the collected user finger, and by comparing b with a fourth preset value, judges whether the collected user finger is stained with water or not,
when b is larger than or equal to a fourth preset value, judging that the collected user fingers are stained with water;
and when b is smaller than a fourth preset value, judging that the collected user fingers are not stained with water.
The finger secondary password verification module judges whether the collected finger of the user is wet or not according to the collected finger vein roughness b of the finger of the user, and executes different judgment modes according to different judgment results.
Further, the finger secondary password verification module obtains the finger bioelectric strength I and the finger blood flow velocity V in the secondary password obtained by the finger secondary password obtaining module under the condition that the collected finger of the user is soaked in water, compares the obtained result with the finger secondary password pre-stored by the user, wherein the finger secondary password pre-stored by the user comprises the finger bioelectric strength I1 and the finger blood flow velocity V1,
the absolute value of the difference value between I and I1 is obtained, and the obtained absolute value is divided by a bioelectrical intensity conversion coefficient m1 to obtain a quotient which is marked as n1;
obtaining the absolute value of the difference between V and V1, dividing the obtained absolute value by a blood flow velocity conversion coefficient m2 to obtain a quotient marked as n2;
normalizing the two factors of finger bioelectric strength and finger blood flow speed, namely multiplying n1 and n2 to obtain an error value W between the acquired finger secondary password and the finger secondary password prestored by the user,
i.e.
W is compared with a first threshold value and,
when W is greater than or equal to a first threshold value, judging that the verification of the finger information of the user fails;
and when W is smaller than the first threshold value, judging that the verification of the finger information of the user is successful.
Under the condition that the collected finger of the user is stained with water, the finger secondary password verification module can acquire the finger bioelectric intensity I and the finger blood flow velocity V in the secondary password obtained by the finger secondary password acquisition module to judge, and therefore, when the hand is stained with water, the water absorbs heat, so that the temperature of the finger is not accurately tested, and meanwhile, the water also has conductivity, and when the finger bioelectric intensity I is tested, the resistance of the finger epidermis can be reduced, and the measured result is more accurate.
Further, the finger secondary password verification module obtains the finger temperature T and the finger blood flow velocity V in the secondary password obtained by the finger secondary password obtaining module under the condition that the collected finger of the user is not soaked with water, compares the obtained result with the finger secondary password pre-stored by the user, wherein the finger secondary password pre-stored by the user comprises the finger temperature T1 and the finger blood flow velocity V1,
the absolute value of the difference value between T and T1 is obtained, and the obtained absolute value is divided by a temperature conversion coefficient m3 to obtain a quotient marked as n3;
obtaining the absolute value of the difference between V and V1, dividing the obtained absolute value by a blood flow velocity conversion coefficient m2 to obtain a quotient marked as n2;
normalizing the two factors of finger temperature and finger blood flow speed, namely multiplying n3 and n2 to obtain an error value W between the acquired finger secondary password and the finger secondary password prestored by the user,
i.e.
The W is compared with a second threshold value,
when W is greater than or equal to a second threshold value, judging that the verification of the finger information of the user fails;
and when W is smaller than the second threshold value, judging that the verification of the finger information of the user is successful.
Under the condition that the collected user's finger is not stained with water, the finger secondary password verification module can acquire the finger temperature T and the finger blood flow velocity V in the secondary password obtained by the finger secondary password acquisition module to judge, but does not adopt the finger bioelectric strength I, because the resistance of the finger skin is larger when the skin is dry, the measured finger bioelectric strength I is inaccurate.
Further, the transfer module obtains the judgment result of the finger information verification module,
when the judgment result of the finger information verification module is that the user finger information verification is successful, the transfer module executes transfer operation;
when the judgment result of the finger information verification module is that the user finger information verification fails, the transfer module does not execute transfer operation.
Compared with the prior art, the invention has the following beneficial effects: according to the fingerprint matching method and device, when the fingerprint information is acquired, the finger information of the user is extracted, namely, not only the fingerprint information of the user is acquired, but also other aspects of information of the user finger are included, the user is assisted in fingerprint matching through the acquired other aspects of information, and the fingerprint matching efficiency and accuracy are improved.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a schematic diagram of a blockchain and big data based financial transaction system of the present invention;
FIG. 2 is a flowchart of a method for determining the roughness of a fingerprint in a fingerprint password acquisition module of a financial transaction system based on blockchain and big data;
FIG. 3 is a flow chart of a method for specifically obtaining similarity in a matching process of fingerprint password verification modules of a financial transaction system based on blockchains and big data.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-3, the present invention provides the following technical solutions: a blockchain and big data based financial transaction system, comprising: the user finger information acquisition module comprises a fingerprint password acquisition module and a finger secondary password acquisition module, the finger information verification module comprises a fingerprint password verification module and a finger secondary password verification module,
the fingerprint password acquisition module is used for acquiring fingerprint information of a user;
the finger secondary password acquisition module is used for acquiring the secondary password of the user finger, and the secondary password comprises: finger temperature T, finger bioelectric intensity I, and finger blood flow velocity V;
the fingerprint password verification module is used for matching the fingerprint information acquired by the fingerprint password acquisition module with the fingerprint information prestored by the user, solving the similarity c of the fingerprint information acquired by the fingerprint password acquisition module and the fingerprint information prestored by the user, judging the similarity c,
when c is larger than or equal to a first preset value, judging that the verification of the finger information of the user is successful,
when c is larger than or equal to the second preset value and smaller than the first preset value, executing the finger secondary password verification module,
when c is smaller than a second preset value, judging that the verification of the finger information of the user fails;
the finger secondary password verification module is used for comparing the secondary password of the user finger acquired by the finger secondary password acquisition module with the finger secondary password prestored by the user to judge whether the user finger information is successfully verified;
the transfer module is used for acquiring the judging result of the finger information verification module, judging whether to execute transfer operation according to the result of the user finger information verification,
the data generated in each module is stored in the form of a blockchain.
The invention realizes the verification of the collected finger information of the user through the cooperation of the modules, and further rapidly completes the matching of the finger information of the user.
The fingerprint password acquisition module acquires fingerprint information of a user, wherein the fingerprint information comprises fingerprint patterns and fingerprint venation roughness of the finger,
the specific method for solving the fingerprint vein roughness is as follows:
s1.1, acquiring a fingerprint pattern of a finger;
s1.2, performing image binarization processing on a fingerprint image of a finger;
s1.3, counting the number b1 of black pixel points in the finger fingerprint image after the binarization processing of the image;
s1.4, dividing b2 by 2 to obtain the length b3 of the fingerprint venation in the finger fingerprint image, wherein the number b2 of black pixel points contacted with the outline of each fingerprint venation in the region of each fingerprint venation in the finger fingerprint image subjected to the binarization processing of the statistic image;
s1.5, dividing b1 obtained in the step S1.3 by b3 obtained in the step S1.4 to obtain a result which is the roughness b of the fingerprint venation, namely
When the fingerprint password acquisition module acquires fingerprint information, not only the fingerprint pattern of the finger is acquired, but also the fingerprint vein roughness is removed, because the fingerprint pattern and the fingerprint vein roughness of the finger both influence the fingerprint matching, when the corresponding value of the fingerprint vein roughness exceeds a certain range, the fingerprint pattern of the finger is blurred, the matching degree of the fingerprint matching is reduced, the fingerprint vein roughness is influenced by special environment, and when a user is immersed in water, the fingerprint vein roughness is increased.
The finger secondary password acquisition module acquires the secondary password through a corresponding sensor on the acquisition equipment when the finger is in contact with the acquisition equipment,
the finger temperature is acquired by a temperature sensor on the acquisition equipment;
the finger bioelectric strength is acquired by a bioelectric sensor on the acquisition equipment;
the finger blood flow velocity is obtained by collecting data through a vibration sensor on the collecting device, calculating the product of the vibration value z and the blood flow coefficient f measured by the vibration sensor through different vibrations generated by different finger blood flow velocities, wherein the obtained product is the finger blood flow velocity V, namely V=f.z,
the blood flow coefficient f is a relation coefficient between the vibration frequency measured by the finger and the blood flow speed of the finger.
The finger secondary password acquisition module further acquires the blood flow velocity of the finger by acquiring the vibration frequency of the finger by utilizing the relation between the blood flow velocity of the finger and the vibration frequency.
The fingerprint password verification module is used for pre-storing fingerprint information of a user in advance, wherein the pre-stored fingerprint information comprises a fingerprint graph of the user's finger and the thickness of the user's fingerprint venation.
The fingerprint password verification module only compares the similarity of fingerprint patterns of the user fingers in the matching process, and the method for specifically solving the similarity in the matching process comprises the following steps:
s2.1, marking a pre-stored fingerprint pattern of a user finger as c1, and marking the fingerprint pattern of the finger in the fingerprint information acquired by the fingerprint password acquisition module as c2;
s2.2, respectively carrying out image binarization processing on the c1 and the c2, respectively obtaining corresponding pixels of the central line corresponding to each fingerprint vein from the processed c1 and c2 through the contour position relation of each fingerprint vein, and marking the obtained corresponding pixels of the central line;
s2.3, respectively extracting the marked pixel points in the c1 and the c2, overlapping the c1 and the c2, and establishing a plane rectangular coordinate system by taking the midpoint of the overlapped c1 and c2 as an origin;
s2.4, respectively calculating the distance between the corresponding marked pixel points in the c1 and the c2, respectively comparing the obtained distance c3 with a third preset value,
when c3 is larger than or equal to a third preset value, the pixel point corresponding to c3 in c1 is marked for the second time,
when c3 is smaller than a third preset value, not processing the pixel point corresponding to c3 in c 1;
s2.5, counting the number c4 of the pixels marked by the c1 in the step S2.3 and the number c5 of the pixels marked by the c1 in the step S2.4 for the second time, dividing the c4 by the c5, and marking the obtained quotient as the similarity c between the acquired fingerprint information and the pre-stored fingerprint information of the user, namely
The fingerprint password verification module processes the fingerprint graph in an image binarization mode, can accurately extract fingerprint information, is more clear in fingerprint information, is favorable for matching the fingerprint information, can clearly identify the pixel points compared during fingerprint matching in a marking mode, and enables data processing to be more accurate and the determination of the coordinates of the pixel points to be more uniform in a same plane rectangular coordinate system mode.
The finger secondary password verification module is used for acquiring the finger vein roughness b of the collected user finger before verifying the secondary password of the collected user finger, judging whether the collected user finger is stained with water or not by comparing the finger vein roughness b with a fourth preset value,
when b is larger than or equal to a fourth preset value, judging that the collected user fingers are stained with water;
and when b is smaller than a fourth preset value, judging that the collected user fingers are not stained with water.
The finger secondary password verification module judges whether the collected finger of the user is wet or not according to the collected finger vein roughness b of the finger of the user, and executes different judgment modes according to different judgment results.
The finger secondary password verification module can acquire the finger bioelectric strength I and the finger blood flow velocity V in the secondary password obtained by the finger secondary password acquisition module under the condition that the acquired finger of the user is soaked with water, compares the acquired result with the finger secondary password prestored by the user, wherein the finger secondary password prestored by the user comprises the finger bioelectric strength I1 and the finger blood flow velocity V1,
the absolute value of the difference value between I and I1 is obtained, and the obtained absolute value is divided by a bioelectrical intensity conversion coefficient m1 to obtain a quotient which is marked as n1;
obtaining the absolute value of the difference between V and V1, dividing the obtained absolute value by a blood flow velocity conversion coefficient m2 to obtain a quotient marked as n2;
normalizing the two factors of finger bioelectric strength and finger blood flow speed, namely multiplying n1 and n2 to obtain an error value W between the acquired finger secondary password and the finger secondary password prestored by the user,
i.e.
W is compared with a first threshold value and,
when W is greater than or equal to a first threshold value, judging that the verification of the finger information of the user fails;
and when W is smaller than the first threshold value, judging that the verification of the finger information of the user is successful.
Under the condition that the collected finger of the user is stained with water, the finger secondary password verification module can acquire the finger bioelectric intensity I and the finger blood flow velocity V in the secondary password obtained by the finger secondary password acquisition module to judge, and therefore, when the hand is stained with water, the water absorbs heat, so that the temperature of the finger is not accurately tested, and meanwhile, the water also has conductivity, and when the finger bioelectric intensity I is tested, the resistance of the finger epidermis can be reduced, and the measured result is more accurate.
The finger secondary password verification module can acquire the finger temperature T and the finger blood flow velocity V in the secondary password obtained by the finger secondary password acquisition module under the condition that the acquired finger of the user is not stained with water, compares the acquired result with the finger secondary password prestored by the user, wherein the finger secondary password prestored by the user comprises the finger temperature T1 and the finger blood flow velocity V1,
the absolute value of the difference value between T and T1 is obtained, and the obtained absolute value is divided by a temperature conversion coefficient m3 to obtain a quotient marked as n3;
obtaining the absolute value of the difference between V and V1, dividing the obtained absolute value by a blood flow velocity conversion coefficient m2 to obtain a quotient marked as n2;
normalizing the two factors of finger temperature and finger blood flow speed, namely multiplying n3 and n2 to obtain an error value W between the acquired finger secondary password and the finger secondary password prestored by the user,
i.e.
The W is compared with a second threshold value,
when W is greater than or equal to a second threshold value, judging that the verification of the finger information of the user fails;
and when W is smaller than the second threshold value, judging that the verification of the finger information of the user is successful.
Under the condition that the collected user's finger is not stained with water, the finger secondary password verification module can acquire the finger temperature T and the finger blood flow velocity V in the secondary password obtained by the finger secondary password acquisition module to judge, but does not adopt the finger bioelectric strength I, because the resistance of the finger skin is larger when the skin is dry, the measured finger bioelectric strength I is inaccurate.
The transfer module obtains the judgment result of the finger information verification module,
when the judgment result of the finger information verification module is that the user finger information verification is successful, the transfer module executes transfer operation;
when the judgment result of the finger information verification module is that the user finger information verification fails, the transfer module does not execute transfer operation.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.