Financial payment security verification device and method based on RFID technology

Abstract

The present invention discloses a financial payment security verification device and method based on RFID technology, the device comprising a main control unit, a tunable antenna array, a biometric feature collection unit, a hardware encryption storage unit and a blockchain processing unit; the main control unit respectively performs RFID communication control and biometric feature recognition through a dual processor architecture; the tunable antenna array adopts dynamic spectrum hopping technology to switch between multiple frequency bands; the biometric feature collection unit integrates fingerprint and palm print recognition functions; a dual random source is used to generate a frequency hopping sequence, frequency band switching is performed in combination with channel quality assessment, and transactions are verified through blockchain technology; the present invention significantly improves the security and reliability of the payment process through the collaboration of multiple biometric feature recognition, dynamic spectrum management and blockchain technology, and effectively prevents various payment frauds and attacks.

Description

Technical Field

[0001] The present invention belongs to the technical field of financial data processing, and in particular relates to a financial payment security verification device and method based on RFID technology. Background Art

[0002] With the rapid development of mobile payment technology, contactless payment methods based on RFID (radio frequency identification) have been widely used due to their convenience. However, traditional RFID payment systems still face many challenges in terms of security: first, single-band RFID communications are susceptible to interference and eavesdropping, and attackers may steal user information through replay attacks or man-in-the-middle attacks; second, simple password authentication or single biometric identification methods are difficult to meet the high security requirements of financial payment scenarios, and there is a risk of being counterfeited or deceived; third, traditional centralized payment record storage methods are prone to tampering, and it is difficult to ensure the authenticity and integrity of transaction information.

[0003] In the existing technology, there are some improvement schemes that attempt to solve the above problems; for example, by adding encryption algorithms to enhance communication security, or by using multiple authentications to improve identity authentication reliability; but these schemes often have the following shortcomings: 1) There is a lack of dynamic protection mechanism for RFID communication links, and it is impossible to effectively deal with interference and attacks in complex electromagnetic environments; 2) The feature quality factor is not considered in the process of biometric recognition, which is easily affected by the environment and leads to misjudgment; 3) The decentralized characteristics of the emerging blockchain technology are not fully utilized to ensure transaction security; 4) Each security mechanism is relatively independent, and there is a lack of systematic collaborative protection strategies.

[0004] Therefore, a new RFID payment security verification solution is urgently needed to comprehensively improve the security and reliability of the payment process. Summary of the invention

[0005] The present invention provides a financial payment security verification device and method based on RFID technology, which comprehensively utilizes dynamic spectrum management, multiple biometric feature recognition and blockchain technology to achieve the purpose of comprehensively improving the security and reliability of the payment process.

[0006] The technical solution of the present invention is as follows:

[0007] A financial payment security verification device based on RFID technology, the device comprising: a main control unit, a tunable antenna array, a biometric feature collection unit, a hardware encryption storage unit and a blockchain processing unit.

[0008] The main control unit includes a first processor and a second processor, the first processor is used to perform RFID communication control and control the tunable antenna array to switch between multiple frequency bands according to a preset dynamic spectrum hopping algorithm, and the second processor is used to perform biometric identification.

[0009] The tunable antenna array is connected to the first processor and is used to send and receive RFID signals within a preset multiple frequency bands; the tunable antenna array includes multiple independently tunable antennas, an antenna selection switch matrix and an impedance matching network; each independently tunable antenna corresponds to a preset frequency band, and the antenna selection switch matrix is ​​used to select and activate a specific independently tunable antenna according to the output of the dynamic spectrum hopping algorithm; the impedance matching network is used to achieve dynamic matching between the antenna unit and the radio frequency circuit.

[0010] The biometric feature collection unit is connected to the second processor and is used to collect user biometric feature information.

[0011] The hardware encryption storage unit is connected to the first processor and the second processor respectively, and is used to store encrypted user information and spectrum hopping parameters.

[0012] The blockchain processing unit is connected to the main control unit and is used to perform blockchain recording and verification of transaction information.

[0013] Furthermore, the biometric feature collection unit includes:

[0014] Capacitive fingerprint collector, used to collect user fingerprint information;

[0015] Palmprint scanner, used to collect user palmprint information;

[0016] The feature extraction and processing circuit is connected to the capacitive fingerprint collector and the palm print scanner, and is used for preprocessing and feature extraction of the collected biological features.

[0017] Furthermore, the multiple frequency bands include at least: frequency band 1, frequency band 2 and frequency band 3; the range of the frequency band 1 is: 860MHz-868MHz; the range of the frequency band 2 is: 902MHz-928MHz; the range of the frequency band 3 is: 2400MHz-2483.5MHz.

[0018] Furthermore, the device also includes: a safety status monitoring unit, an exception handling unit and a communication interface.

[0019] The safety status monitoring unit is connected to the main control unit and is used for real-time monitoring of the working status and potential safety threats of the device.

[0020] The abnormality processing unit is connected to the safety status monitoring unit and is used to trigger a protection mechanism when an abnormality is detected.

[0021] The communication interface is used for data exchange with an external payment system.

[0022] Furthermore, controlling the tunable antenna array to switch between multiple frequency bands according to a preset dynamic spectrum hopping algorithm specifically includes the following steps:

[0023] Step S11, generating a frequency hopping sequence based on a dual random source.

[0024] Generate the first random sequence using a linear congruential generator: ,in, is the current state value, is the previous state value, is the multiplier, the value is 8192, is the increment, the value is 51749, For the modulus, 262144 is selected, and mod means the modulo operation.

[0025] Use Logistic mapping to generate the second random sequence: , where Yn+1 is the current state value; Yn is the previous state value; r is the control parameter, which takes the value of 3.95.

[0026] The first random sequence and the second random sequence are mixed to calculate a random source: ,in, is the final random value, ranging from (0,1), which is used to determine the frequency selection.

[0027] Step S12, evaluating the channel quality, obtaining a channel quality score and a frequency band switching flag value, and determining whether the frequency band needs to be switched.

[0028] The signal-to-noise ratio for each channel Perform the calculation: ,in, is the signal strength, the nominal value is -50dBm; is the background noise intensity, the nominal value is -90dBm; is the external interference intensity, obtained through real-time measurement.

[0029] The channel quality score calculation formula is: , where Q is the channel quality score, ranging from 0 to 1; is the signal-to-noise ratio threshold, which is 10dB.

[0030] Determine the value of the frequency band switching flag T according to the Q value:

[0031] When Q<0.5, T = 1, indicating that the frequency band needs to be switched;

[0032] When Q ≥ 0.5, T = 0, indicating that there is no need to switch frequency bands.

[0033] Step S13, the frequency band switching probability is calculated according to the channel quality score and the random value, and the working frequency band is switched and selected according to the frequency band switching probability P under the condition that the frequency band switching flag value T = 1 and the time from the last switching is more than 100ms.

[0034] The calculation formula of the frequency band switching probability P is: .

[0035] When 0 ≤P<0.33, select frequency band 1; when 0.33 ≤P<0.67, select frequency band 2; when 0.67 ≤P≤1, select frequency band 3; otherwise, maintain the current working frequency band.

[0036] Furthermore, the antenna is optimized based on the currently selected frequency band and channel quality score, and the voltage standing wave ratio is calculated. , The optimization target value is set to 1.5, and the gradient descent method is used to optimize the network parameters of the matching antenna.

[0037] VSWR The calculation formula is: ,in, is the reflection coefficient, , is the antenna impedance, is the characteristic impedance, which is 50Ω.

[0038] Gradient descent method is used to optimize the matching network parameters: ;in, For the current The parameters of the inductor L or capacitor C to be optimized at any time, η is the learning rate, ranging from 0.01 to 0.1, for The gradient of the corresponding parameter.

[0039] Based on the same inventive concept, the present invention provides a financial payment security verification method based on RFID technology, the method is implemented based on the device of the present invention, and the method includes the following steps:

[0040] Step S1, initializing and configuring the financial payment security verification device based on RFID technology, including generating a unique device identification code, entering user biometric information, and setting initial spectrum hopping parameters.

[0041] Step S2, when receiving a payment request, the dynamic spectrum hopping process and biometric matching calculation are started.

[0042] The dynamic spectrum hopping process includes: generating a frequency band sequence S(t) and determining a hopping time interval .

[0043] ,in, is the reference frequency, which is the center frequency of the selected frequency band; ΔF is the frequency step value, which ranges from 1% to 5% of the bandwidth of the selected frequency band; K is the session key, which is generated by the hardware encryption module; t is the real-time timestamp; H is the SHA-3 hash function; N is the number of frequency bands, which shall not be less than 3.

[0044] ;in, is the minimum transition time interval, The default time interval is 100ms, and the adjustable range is 50ms to 200ms.

[0045] Step S3, verify the transaction and record the information through the blockchain network.

[0046] Furthermore, the biometric matching calculation formula is: ,in, is the fingerprint matching degree, is the palm print matching degree, , is the weight coefficient, which is obtained by the quality of fingerprint image and palm print image. The clarity of fingerprint image and palm print image shall not be less than 300dpi, the number of feature points shall not be less than 30, and the image completeness shall not be less than 90%;

[0047] Fingerprint image quality is expressed as , the evaluation of palmprint image quality is expressed as ,but:

[0048] , ; The certification pass condition is M≥ , is the minimum authentication threshold, which is 0.9332.

[0049] Furthermore, the blockchain verification process includes:

[0050] Constructing transaction proof: , where TxData is the transaction data, PrevHash is the previous block hash, and Timestamp is the timestamp.

[0051] Furthermore, the security verification method also includes a security status assessment:

[0052] After each user authentication, the initial parameters of the frequency hopping sequence are regenerated based on the authentication information;

[0053] When the channel quality is detected to be lower than the preset threshold, the frequency point reselection is automatically triggered;

[0054] When the channel quality assessment fails three times in a row, the emergency protection mechanism is triggered, including: suspending the current transaction processing, switching to the backup frequency band, re-authenticating the user, and sending an alarm message to the security monitoring system.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] The present invention adopts a dual-processor architecture to separate RFID communication and biometric identification, which significantly improves the system processing efficiency and security isolation. It integrates fingerprint and palmprint dual biometric identification and combines it with a weight adaptive algorithm to greatly improve the accuracy of identity authentication. It applies dynamic spectrum hopping technology to the RFID payment field, realizes intelligent frequency band switching through dual random sources and channel quality evaluation, effectively resists interference and deception, and has high practical value. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 It is a schematic diagram of the composition of the financial payment security verification device based on RFID technology of the present invention;

[0058] Figure 2 This is a flow chart of the financial payment security verification method based on RFID technology of the present invention. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention is described clearly and completely below. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] Example 1

[0061] like Figure 1 The figure shows the composition diagram of the financial payment security verification device based on RFID technology of the present invention. By combining RFID technology, biometric identification and blockchain technology, it effectively solves the potential security problems existing in the current financial payment process. The device adopts multiple security protection mechanisms, which can effectively prevent various security threats such as counterfeit card fraud and information theft, and significantly improve the security of the payment process; the device includes: a main control unit, a tunable antenna array, a biometric collection unit, a hardware encryption storage unit and a blockchain processing unit.

[0062] This modular design ensures the high integration and scalability of the system, and the various functional units work together to form a complete secure payment verification system.

[0063] The main control unit includes a first processor and a second processor. The first processor is used to perform RFID communication control and control the tunable antenna array to switch between multiple frequency bands according to a preset dynamic spectrum hopping algorithm. The second processor is used to perform biometric identification. A dual-processor architecture design is adopted to achieve efficient task allocation and processing. The advantage of this design is that it can process two key tasks, RFID communication and biometric identification, at the same time, significantly improving the system response speed.

[0064] The tunable antenna array is connected to the first processor and is used to send and receive RFID signals within a preset multiple frequency bands; the tunable antenna array includes multiple independently tunable antennas, an antenna selection switch matrix and an impedance matching network; each independently tunable antenna corresponds to a preset frequency band, and the antenna selection switch matrix is ​​used to select and activate a specific independently tunable antenna according to the output of the dynamic spectrum hopping algorithm; the impedance matching network is used to achieve dynamic matching between the antenna unit and the radio frequency circuit.

[0065] The tunable antenna array design includes: multiple independently tunable antennas: each antenna adopts a new microstrip antenna design with high gain (>6dBi) and wide bandwidth characteristics. In experimental tests, the working bandwidth of a single antenna can cover more than 95% of the specified frequency band; the antenna selection switch matrix adopts a low insertion loss PIN switch design, with a switching loss of less than 0.3dB and a switching time of less than 100us. The switch matrix can quickly select and activate specific independently tunable antennas based on the output of the dynamic spectrum hopping algorithm; the impedance matching network adopts a π-type network structure to achieve dynamic impedance matching through adjustable capacitors and inductors. In practical applications, this network can keep the antenna's standing wave ratio below 1.5 at all times, ensuring the best signal transmission efficiency.

[0066] The first processor uses a 32-bit ARM Cortex-M4 core with a main frequency of up to 120MHz. The processor controls the tunable antenna array to switch between multiple frequency bands according to a preset dynamic spectrum hopping algorithm. This dynamic switching mechanism greatly improves the anti-interference ability and security of communication. In practical applications, the processor can complete the frequency band switching operation in less than 1ms, ensuring the smoothness of the payment process. The second processor uses a dedicated biometric recognition processor.

[0067] Equipped with a neural network acceleration unit for performing biometric identification. This processor can complete the feature extraction and matching operation of fingerprints and palm prints within 100ms, with an accuracy rate of 99.99%, which can effectively prevent identity counterfeiting; the biometric collection unit is connected to the second processor to collect user biometric information.

[0068] The hardware encryption storage unit is connected to the first processor and the second processor respectively, and is used to store encrypted user information and spectrum hopping parameters; the blockchain processing unit is connected to the main control unit, and is used to perform blockchain recording and verification of transaction information.

[0069] The biometric feature collection unit comprises:

[0070] Capacitive fingerprint collector, used to collect user fingerprint information;

[0071] Palmprint scanner, used to collect user palmprint information;

[0072] The feature extraction and processing circuit is connected to the capacitive fingerprint collector and the palm print scanner, and is used for preprocessing and feature extraction of the collected biological features.

[0073] The multiple frequency bands include at least: frequency band 1, frequency band 2 and frequency band 3; the range of the frequency band 1 is: 860MHz-868MHz; the range of the frequency band 2 is: 902MHz-928MHz; the range of the frequency band 3 is: 2400MHz-2483.5MHz.

[0074] The multi-band design fully considers the main RFID frequency band standards and selects the three most representative frequency bands:

[0075] Band 1 (860MHz-868MHz): This band has good penetration and moderate communication distance.

[0076] Band 2 (902MHz-928MHz): has a larger available bandwidth and supports high-speed data transmission.

[0077] Band 3 (2400MHz-2483.5MHz): A general-purpose ISM band with a high data rate, suitable for short-range high-speed communications.

[0078] The device also includes: a safety status monitoring unit, an abnormality processing unit and a communication interface.

[0079] The safety status monitoring unit is connected to the main control unit and is used for real-time monitoring of the working status and potential safety threats of the device.

[0080] The abnormality processing unit is connected to the safety status monitoring unit and is used to trigger a protection mechanism when an abnormality is detected.

[0081] The communication interface is used for data exchange with an external payment system.

[0082] The safety status monitoring unit adopts a real-time monitoring mechanism to monitor multiple parameters such as RF signal strength, noise level, communication quality, etc. When an abnormality is detected, the response time is less than 10ms; the abnormality handling unit has a built-in multi-level protection mechanism, which can initiate corresponding protection measures according to the abnormality level, such as switching frequency bands, suspending transactions, and alarming; Communication interface: supports multiple standard interface protocols, including USB Type-C, Bluetooth 5.0, etc., and the data transmission rate can reach 480Mbps.

[0083] The method of controlling the tunable antenna array to switch between multiple frequency bands according to a preset dynamic spectrum hopping algorithm specifically includes the following steps:

[0084] Step S11, generating a frequency hopping sequence based on a dual random source.

[0085] Generate the first random sequence using a linear congruential generator: ,in, is the current state value, is the previous state value, is the multiplier, the value is 8192, is the increment, the value is 51749, For the modulus, 262144 is selected, and mod means the modulo operation.

[0086] The linear congruential generator has a cycle length of 262144, avoiding short cycle repetition. The parameter selection has been optimized and has passed the NIST random number test. It has a fast computing speed and can generate millions of random numbers per second.

[0087] Use Logistic mapping to generate the second random sequence: , where Yn+1 is the current state value; Yn is the previous state value; r is the control parameter, which takes a value of 3.95. Logistic mapping has good chaotic characteristics and increases randomness. The control parameter r=3.95 ensures that the system works in the chaotic region, is sensitive to initial values, and increases the difficulty of prediction.

[0088] The use of a mixed random source significantly improves the randomness and unpredictability of spectrum hopping. Through experimental verification, the generated random sequence passes all statistical test items of NIST SP800-22. The first random sequence and the second random sequence are mixed for random source calculation: ,in, is the final random value, ranging from (0,1), which is used to determine the frequency selection.

[0089] Step S12, evaluating the channel quality, obtaining a channel quality score and a frequency band switching flag value, and determining whether the frequency band needs to be switched.

[0090] The signal-to-noise ratio for each channel Perform the calculation: ,in, is the signal strength, the nominal value is -50dBm; is the background noise intensity, the nominal value is -90dBm; is the external interference intensity, obtained through real-time measurement.

[0091] The channel quality score calculation formula is: , where Q is the channel quality score, ranging from 0 to 1; is the signal-to-noise ratio threshold, which is 10dB.

[0092] Determine the value of the frequency band switching flag T according to the Q value:

[0093] When Q<0.5, T = 1, indicating that the frequency band needs to be switched;

[0094] When Q ≥ 0.5, T = 0, indicating that there is no need to switch frequency bands.

[0095] The SNR calculation takes into account three key factors: signal strength, background noise, and external interference. It uses real-time measurement, with a response time of less than 1ms and an evaluation accuracy of ±1dB. The quality score calculation uses normalization to facilitate comparison in different scenarios. A threshold mechanism is introduced to provide clear switching criteria. The calculation method is simple and efficient, and is easy to process in real time. Actual tests have shown that the evaluation mechanism can accurately reflect changes in channel quality, and the accuracy of switching decisions exceeds 98%.

[0096] Step S13, the frequency band switching probability is calculated according to the channel quality score and the random value, and the working frequency band is switched and selected according to the frequency band switching probability P under the condition that the frequency band switching flag value T = 1 and the time from the last switching is more than 100ms.

[0097] The calculation formula of the frequency band switching probability P is: .

[0098] When 0 ≤P<0.33, select frequency band 1; when 0.33 ≤P<0.67, select frequency band 2; when 0.67 ≤P≤1, select frequency band 3; otherwise, maintain the current working frequency band.

[0099] The frequency band switching strategy proposed in step S13 combines the channel quality score and the random value to avoid frequent switching, and the three-stage probability allocation ensures balanced use of the frequency band; the minimum switching interval of 100ms prevents system oscillation.

[0100] Optimize the antenna based on the currently selected frequency band and channel quality score, and calculate the voltage standing wave ratio , The optimization target value is set to 1.5, and the gradient descent method is used to optimize the network parameters of the matching antenna; the VSWR optimization target value of 1.5 ensures good signal transmission efficiency; the gradient descent method usually achieves the goal in 3-5 iterations, and the learning rate is adaptively adjusted to improve the optimization stability; experimental data show that this switching strategy can reduce the system throughput by no more than 10% when interfered, which is significantly better than the traditional fixed frequency solution.

[0101] VSWR The calculation formula is: ,in, is the reflection coefficient, , is the antenna impedance, is the characteristic impedance, which is 50Ω.

[0102] Gradient descent method is used to optimize the matching network parameters: ;in, For the current The parameters of the inductor L or capacitor C to be optimized at any time, η is the learning rate, ranging from 0.01 to 0.1, for The gradient of the corresponding parameter.

[0103] Example 2

[0104] like Figure 2 As shown, the financial payment security verification method based on RFID technology of the present invention is implemented based on the device of Example 1, and the method includes the following steps:

[0105] Step S1, initializing and configuring the financial payment security verification device based on RFID technology, including generating a unique device identification code, entering user biometric information, and setting initial spectrum hopping parameters.

[0106] The device's unique identification code is generated by combining the hardware serial number and timestamp, using the SHA-256 algorithm for hash processing to generate a 256-bit unique identification code; user biometric information entry supports multi-angle fingerprint collection, at least 3 samples are entered for each finger, and the palm print image collection is required to have a completeness of more than 95%. The feature data is stored after 3DES encryption.

[0107] The spectrum hopping parameter setting selects a suitable initial frequency band based on the actual communication environment, sets the default hopping time interval, and initializes the random number generator seed.

[0108] Step S2, when receiving a payment request, the dynamic spectrum hopping process and biometric matching calculation are started.

[0109] The dynamic spectrum hopping process includes: generating a frequency band sequence S(t) and determining a hopping time interval .

[0110] ,in, is the reference frequency, which is the center frequency of the selected frequency band; ΔF is the frequency step value, which ranges from 1% to 5% of the bandwidth of the selected frequency band; K is the session key, which is generated by the hardware encryption module; t is the real-time timestamp; H is the SHA-3 hash function; N is the number of frequency bands, which shall not be less than 3.

[0111] ;in, is the minimum transition time interval, The default time interval is 100ms, and the adjustable range is 50ms to 200ms.

[0112] Step S3, verify the transaction and record the information through the blockchain network.

[0113] The biometric matching calculation formula is: ,in, is the fingerprint matching degree, is the palm print matching degree, , is the weight coefficient, which is obtained by the quality of fingerprint image and palm print image. The definition of fingerprint image and palm print image shall not be less than 300dpi, the number of feature points shall not be less than 30, and the image completeness shall not be less than 90%;

[0114] Fingerprint image quality is expressed as , the evaluation of palmprint image quality is expressed as ,but:

[0115] , ; The certification pass condition is M≥ , is the minimum authentication threshold, which is 0.9332.

[0116] The blockchain verification process includes:

[0117] Constructing transaction proof: , where TxData is the transaction data, PrevHash is the previous block hash, and Timestamp is the timestamp.

[0118] The security verification method also includes a security status assessment:

[0119] After each user authentication, the initial parameters of the frequency hopping sequence are regenerated based on the authentication information;

[0120] When the channel quality is detected to be lower than the preset threshold, the frequency point reselection is automatically triggered;

[0121] When the channel quality assessment fails three times in a row, the emergency protection mechanism is triggered, including: suspending the current transaction processing, switching to the backup frequency band, re-authenticating the user, and sending an alarm message to the security monitoring system.

[0122] The method of the present invention shows high stability in various complex environments: the payment transaction success rate reaches 99.99%, the average transaction time is less than 1 second, the security protection level meets the financial level requirements, the system stability is high, and the MTBF exceeds 50,000 hours.

[0123] It should be noted that those skilled in the art should understand that various changes and equivalent substitutions may be made to the present invention without departing from the scope of the present invention. In addition, various modifications may be made to the present invention for specific situations or materials without departing from the scope of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed, but should include all embodiments falling within the scope of the claims of the present invention.

Claims

1. A financial payment security verification device based on RFID technology, characterized in that: The device includes: a main control unit, a tunable antenna array, a biometric feature collection unit, a hardware encryption storage unit, and a blockchain processing unit; The main control unit includes a first processor and a second processor, and the tunable antenna array is connected to the first processor and is used to send and receive RFID signals within a preset multiple frequency bands; the tunable antenna array includes a plurality of independently tunable antennas, an antenna selection switch matrix and an impedance matching network; each independently tunable antenna corresponds to a preset frequency band, and the antenna selection switch matrix is ​​used to select and activate a specific independently tunable antenna according to the output of the dynamic spectrum hopping algorithm, including the following steps: Step S11, generating a frequency hopping sequence based on a dual random source; Step S12, evaluating the channel quality, obtaining a frequency band switching flag value according to the channel quality score, and determining whether the frequency band needs to be switched; Step S13, calculating the frequency band switching probability according to the channel quality score and the random value, and switching and selecting the working frequency band according to the frequency band switching probability P under the condition that the frequency band switching flag value T = 1 and the time from the last switching is more than 100ms; The impedance matching network is used to achieve dynamic matching between the antenna unit and the radio frequency circuit; The biometric feature collection unit is connected to the second processor and is used to collect user biometric feature information; the biometric feature matching calculation formula is: ,in, is the fingerprint matching degree, is the palm print matching degree, , is the weight coefficient, obtained by the fingerprint image quality and palmprint image quality; The hardware encryption storage unit is connected to the first processor and the second processor respectively, and is used to store encrypted user information and spectrum hopping parameters; The blockchain processing unit is connected to the main control unit and is used to perform blockchain recording and verification of transaction information.

2. The financial payment security verification device based on RFID technology according to claim 1 is characterized in that: The biometric feature collection unit comprises: Capacitive fingerprint collector, used to collect user fingerprint information; Palmprint scanner, used to collect user palmprint information; The feature extraction and processing circuit is connected to the capacitive fingerprint collector and the palm print scanner, and is used for preprocessing and feature extraction of the collected biological features.

3. The financial payment security verification device based on RFID technology according to claim 2 is characterized in that: The multiple frequency bands include at least: frequency band 1, frequency band 2 and frequency band 3; the range of the frequency band 1 is: 860MHz-868MHz; the range of the frequency band 2 is: 902MHz-928MHz; the range of the frequency band 3 is: 2400MHz-2483.5MHz.

4. The financial payment security verification device based on RFID technology according to claim 3 is characterized in that: The device also includes: a safety status monitoring unit, an exception handling unit and a communication interface; The safety status monitoring unit is connected to the main control unit and is used to monitor the working status and potential safety threats of the device in real time; The abnormality handling unit is connected to the safety status monitoring unit and is used to trigger a protection mechanism when an abnormality is detected; The communication interface is used for data exchange with an external payment system.

5. The financial payment security verification device based on RFID technology according to claim 3 is characterized in that: The tunable antenna array is controlled to switch between multiple frequency bands according to a preset dynamic spectrum hopping algorithm, specifically including: Generate the first random sequence using a linear congruential generator: ,in, is the current state value, is the previous state value, is the multiplier, the value is 8192, For increment, the value is 51749. For the modulus, select 262144, mod means modulo operation; Use Logistic mapping to generate the second random sequence: ,in, is the current state value; is the previous state value; r is the control parameter, and its value is 3.95; The first random sequence and the second random sequence are mixed to calculate a random source: ,in, is the final random value, with a value range of (0,1), used to determine the frequency selection; The signal-to-noise ratio for each channel Perform the calculation: ,in, is the signal strength, the nominal value is -50dBm; is the background noise intensity, the nominal value is -90dBm; is the external interference intensity, obtained through real-time measurement; The channel quality score calculation formula is: , where Q is the channel quality score, ranging from 0 to 1; is the signal-to-noise ratio threshold, which is 10dB; Determine the value of the frequency band switching flag T according to the Q value: When Q < 0.5, T = 1, indicating that the frequency band needs to be switched; When Q ≥ 0.5, T = 0, indicating that there is no need to switch frequency bands; The calculation formula of the frequency band switching probability P is: ; When 0 ≤P< 0.33, select frequency band 1; when 0.33 ≤P< 0.67, select frequency band 2; when 0.67 ≤P≤1, select frequency band 3; otherwise, maintain the current operating frequency band.

6. The financial payment security verification device based on RFID technology according to claim 5 is characterized in that: Optimize the antenna based on the currently selected frequency band and channel quality score, and calculate the voltage standing wave ratio , The optimization target value is set to 1.5, and the gradient descent method is used to optimize the network parameters of the matching antenna; VSWR The calculation formula is: ,in, is the reflection coefficient, , is the antenna impedance, is the characteristic impedance, take 50Ω; Gradient descent method is used to optimize the matching network parameters: ;in, For the current The parameters of the inductor L or capacitor C to be optimized at any time, η is the learning rate, ranging from 0.01 to 0.1, for The gradient of the corresponding parameter.

7. A financial payment security verification method based on RFID technology, the method being implemented based on the device of any one of claims 1 to 6, characterized in that: The method comprises the following steps: Step S1, initializing and configuring the financial payment security verification device based on RFID technology, including generating a unique device identification code, entering user biometric information, and setting initial spectrum hopping parameters; Step S2, when receiving a payment request, starting a dynamic spectrum hopping process and biometric matching calculation; The dynamic spectrum hopping process includes: generating a frequency band sequence S(t) and determining a hopping time interval ; ,in, is the reference frequency, which is the center frequency of the selected frequency band; ΔF is the frequency step value, which ranges from 1% to 5% of the bandwidth of the selected frequency band; K is the session key, which is generated by the hardware encryption module; t is the real-time timestamp; H is the SHA-3 hash function; N is the number of frequency bands, which shall not be less than 3; ;in, is the minimum transition time interval, The default time interval is 100ms by default and the adjustable range is 50ms to 200ms. Step S3, verify the transaction and record the information through the blockchain network.

8. The financial payment security verification method based on RFID technology according to claim 7 is characterized in that: The biometric matching calculation formula is: ,in, is the fingerprint matching degree, is the palm print matching degree, , is the weight coefficient, which is obtained by the quality of fingerprint image and palm print image. The definition of fingerprint image and palm print image shall not be less than 300dpi, the number of feature points shall not be less than 30, and the image completeness shall not be less than 90%; Fingerprint image quality is expressed as , the evaluation of palmprint image quality is expressed as ,but: , ; The certification pass conditions are , is the minimum authentication threshold, which is 0.9332.

9. The financial payment security verification method based on RFID technology according to claim 8, characterized in that: The blockchain verification process includes: Constructing transaction proof: , where TxData is the transaction data, PrevHash is the previous block hash, and Timestamp is the timestamp.

10. The financial payment security verification method based on RFID technology according to claim 8, characterized in that: The security verification method also includes a security status assessment: After each user authentication, the initial parameters of the frequency hopping sequence are regenerated based on the authentication information; When the channel quality is detected to be lower than the preset threshold, the frequency point reselection is automatically triggered; When the channel quality assessment fails three times in a row, the emergency protection mechanism is triggered, including: suspending the current transaction processing, switching to the backup frequency band, re-authenticating the user, and sending an alarm message to the security monitoring system.

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