Blockchain-based financial asset custodian system

Abstract

The application discloses a financial asset custody system based on a block chain, and particularly relates to the technical field of block chains, and comprises a data acquisition module, a model construction module, a composite verification module and an evaluation and disposal module.The data acquisition module collects transmission efficiency information and encrypted stability information of the financial asset custody system based on the block chain, and transmits the information to the model construction module for comprehensive analysis, and establishes a model.The operation state of the financial asset custody system based on the block chain is evaluated and classified through mathematical analysis, the operation state type is compared and analyzed according to a preset verification standard, and an analysis signal is generated.A risk evaluation judgment is made according to the signal type, and a risk notification is made.The application can effectively reduce the operation risk of the financial asset custody system, judge abnormal states and issue early warning notifications, and effectively reduce the work burden of operation personnel.

Description

Technical Field

[0001] This invention relates to the field of blockchain technology, and more specifically, to a blockchain-based financial asset custody system. Background Technology

[0002] Blockchain-based financial asset custody systems can leverage blockchain technology to build financial service infrastructure, providing more secure, transparent, and efficient asset custody services. In the traditional financial system, asset custody is the responsibility of institutions to store and manage clients' financial assets, including but not limited to stocks, bonds, and funds. Blockchain-enabled custody systems, through distributed ledgers, smart contracts, and encryption technology, provide new forms for the storage, transfer, and trading of assets.

[0003] While blockchain technology boasts advantages such as decentralization, traceability, and hash-encrypted transmission, its large-scale application may face challenges due to insufficient scalability leading to decreased transaction processing efficiency. Because blockchain is a decentralized block structure, the connection processing of communication signals between nodes relies on consensus algorithms for identification and confirmation. With high model complexity, the consensus algorithm struggles to improve the processing efficiency of a large number of node communications. Furthermore, the existence of block intervals and differences in block size cause instability in data transmission latency, making it difficult to comprehensively assess node communication efficiency and transmission stability for effective supervision and management of the financial asset custody system.

[0004] To address the aforementioned shortcomings, a technical solution is proposed. Summary of the Invention

[0005] The purpose of this invention is to provide a blockchain-based financial asset custody system to address the shortcomings of the prior art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a blockchain-based financial asset custody system, comprising a data acquisition module, a model building module, a composite verification module, and an evaluation and disposal module;

[0007] The data acquisition module is used to collect transmission efficiency information and encryption stability information of the blockchain-based financial asset custody system, and transmit the transmission efficiency information and encryption stability information to the model building module;

[0008] The model building module is used to conduct comprehensive analysis based on encryption stability information and transmission efficiency information, build a model, and evaluate and classify the operating status of blockchain-based financial asset custody system through mathematical analysis.

[0009] The composite verification module is used to compare and analyze the operating status type of the blockchain-based financial asset custody system with the preset verification standards, and generate analysis signals.

[0010] The assessment and handling module is used to make assessments and judgments based on different analytical signals. Through the identification and analysis of different signals, it uses mathematical modeling to assess the risk status of the blockchain-based financial asset custody system and issues risk notifications.

[0011] Preferably, the transmission efficiency information is the transaction efficiency response delay coefficient, and the encryption stability information is the hash value conversion rate coefficient.

[0012] The preferred method for calculating the transaction efficiency response latency coefficient is as follows:

[0013] S101. Obtain the optimal data transmission delay time range of the blockchain-based financial asset custody system, and mark the optimal data transmission delay time range of the blockchain-based financial asset custody system as Dt1-Dt2;

[0014] S102. Obtain the data transmission delay time of the blockchain-based financial asset custody system within a time period T, and label the data transmission delay time of the blockchain-based financial asset custody system within a time period T as Dl, where l = {1,2,3…k}, and k is a positive integer;

[0015] S103. Obtain the data where the data transmission delay time Dl of the blockchain-based financial asset custody system exceeds the limit of the optimal data transmission delay time range Dt2 within a time period T, and label the data transmission delay time data that exceeds the limit of the optimal data transmission delay time range Dt2 as Dz, and z={1,2,3…j}, where j is a positive integer;

[0016] S104. The expression for calculating the transaction efficiency response latency coefficient Dx is as follows:

[0017] The preferred method for calculating the hash value conversion rate coefficient is as follows:

[0018] S201. Obtain the hash conversion time of hash encryption transmission in the blockchain-based financial asset custody system, and mark the hash conversion time of hash encryption transmission in the blockchain-based financial asset custody system as Ta. Obtain the time when the server node performs hash conversion according to the encryption key in the blockchain-based financial asset custody system, and mark the time when the server node performs hash conversion according to the encryption key as Ts.

[0019] S202. Based on the comparison of data content between the sending and receiving ends of the blockchain-based financial asset custody system during a complete data transmission cycle, calculate the data transmission integrity rate. The expression for the transmission integrity rate Ti is: In the formula, Re is the size of the data packet received by the receiving server node, and Se is the size of the data packet sent by the sending node;

[0020] S203. Compare the calculated transmission integrity rate with the preset transmission integrity rate. Under the premise of meeting the preset transmission integrity rate specified by the data transmission, calculate the difference between the frequency hopping time Ta at the transmitting end and the frequency modulation time Ts at the receiving end according to the standard clock. Then, the expression for calculating the frequency hopping time difference Td is Td=|Ta-Ts|.

[0021] S204. Based on the complete data transmission process of several cycles, integrate them into a hash conversion time difference data set, and label the hash conversion time difference as Tf, where f = {1,2,3…h}, where f is the number of the hash conversion time difference in the data set, and h is a positive integer;

[0022] S205. Calculate the standard deviation Pz of the hash transformation time difference dataset. The expression for calculating the standard deviation Pz is as follows: In the formula It is the average of the differences at each hash transformation time, i.e.

[0023] S206, the expression for calculating the hash value conversion rate coefficient Fc is Fc=Pz×exp(Pz 2 +1).

[0024] The preferred approach is to use mathematical analysis to evaluate and classify the operational status of a blockchain-based financial asset custody system.

[0025] The operational status of blockchain-based financial asset custody systems is classified, and the hash encryption volatility index is calculated. The hash encryption volatility index Rd is expressed as Rd=C*[exp(Dx)+ln(Fc)], where C is a constant related to the complexity of the financial asset custody system model framework, Dx is the transaction efficiency response delay coefficient, and Fc is the hash value conversion variability coefficient.

[0026] The hash-encrypted volatility index of the blockchain-based financial asset custody system is calculated and compared with a preset hash-encrypted volatility index threshold. When the hash-encrypted volatility index of the blockchain-based financial asset custody system is greater than or equal to the hash-encrypted volatility index threshold, it is marked as a risk signal. When the hash-encrypted volatility index of the blockchain-based financial asset custody system is less than the hash-encrypted volatility index threshold, it is marked as a steady-state signal.

[0027] Preferably, the logic for evaluating and issuing risk notifications based on different analytical signals is as follows:

[0028] The risk signals marked within a period T are integrated into a risk signal dataset. The hash-encrypted volatility index within the dataset is denoted as Rs, where s is the hash-encrypted volatility index number, i.e., s = {1, 2, 3…g}, where g is a positive integer.

[0029] Calculate the standard deviation of several hash encryption volatility indices within the dataset, and denot the standard deviation of the hash encryption volatility index as Bj. Compare the standard deviation Bj of the hash encryption volatility index with a preset standard deviation threshold Dj of the hash encryption volatility index, and issue an early warning based on the comparison result. The processing logic is as follows:

[0030] If Bj is greater than or equal to Dj, the blockchain-based financial asset custody system is marked as high-risk, prompting staff to note that the blockchain-based financial asset custody system has serious potential risks and needs to be tested and verified.

[0031] If Bj is less than Dj, the blockchain-based financial asset custody system is marked as low-risk, indicating to staff that the blockchain-based financial asset custody system has low-risk potential and does not require testing or verification.

[0032] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0033] This invention detects the hash-encrypted volatility index of a blockchain-based financial asset custody system. When anomalies are detected in the stability and real-time performance of data processing, a comprehensive analysis of the subsequent operational status of the blockchain-based financial asset custody system is conducted to identify potential anomalies and issue early warnings. On the one hand, this allows staff to promptly detect potential anomalies and prevent risks caused by reduced stability and real-time performance of data processing, thereby effectively preventing system security risks. On the other hand, it facilitates staff monitoring the overall status of the blockchain-based financial asset custody system, improving monitoring and management efficiency. Attached Figure Description

[0034] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0035] Figure 1 This is a system module diagram of the present invention. Detailed Implementation

[0036] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0037] Example 1

[0038] Please see Figure 1 As shown, the present invention is a blockchain-based financial asset custody system, including a data acquisition module, a model building module, a composite verification module, and an evaluation and disposal module;

[0039] The data acquisition module is used to collect transmission efficiency information and encryption stability information of the blockchain-based financial asset custody system, and transmit the transmission efficiency information and encryption stability information to the model building module;

[0040] The model building module is used to conduct comprehensive analysis based on encryption stability information and transmission efficiency information, build a model, and evaluate and classify the operating status of blockchain-based financial asset custody system through mathematical analysis.

[0041] The composite verification module is used to compare and analyze the operating status type of the blockchain-based financial asset custody system with the preset verification standards, and generate analysis signals.

[0042] The assessment and handling module is used to make assessments and judgments based on different analytical signals. Through the identification and analysis of different signals, it uses mathematical modeling to assess the risk status of the blockchain-based financial asset custody system and issues risk notifications.

[0043] If the data transmission delay in a blockchain-based financial asset custody system is too long, it may have the following serious impacts on the system:

[0044] Slow transaction speed: Transactions on the blockchain require a series of confirmation steps and consensus mechanisms. If data transmission is delayed for too long, the entire transaction process will become slow, which may lead to user dissatisfaction, especially in the field of financial transactions that require fast execution.

[0045] High costs: Long data transmission delays can lead to increased transaction costs. In financial markets, time sensitivity and low cost are crucial. Excessive delays can reduce system efficiency, increase transaction costs, and affect the system's competitiveness.

[0046] Uncertainty and risk: Blockchain systems are typically designed with a transaction confirmation process to ensure the validity of transactions. If data transmission is delayed, the confirmation process becomes slow, which may increase the uncertainty and risk of transactions, especially in highly volatile market environments.

[0047] Degraded user experience: Long delays will reduce the user experience, especially for financial service users who need immediate feedback. Users may become dissatisfied, lose confidence, and seek faster and more reliable alternatives.

[0048] Impact on market liquidity: Market liquidity is crucial for the normal operation of financial markets. If a blockchain-based custody system causes a slowdown in transaction speed due to data transmission delays, it may affect market liquidity and make the market less active.

[0049] Therefore, avoiding excessively long data transmission delays in blockchain-based financial asset custody systems can effectively prevent the aforementioned serious consequences.

[0050] The data transmission latency of a blockchain-based financial asset custody system is represented by a transaction efficiency response latency coefficient, the specific calculation process of which is as follows:

[0051] S101. Obtain the optimal data transmission delay time range of the blockchain-based financial asset custody system, and mark the optimal data transmission delay time range of the blockchain-based financial asset custody system as Dt1-Dt2;

[0052] It should be noted that by conducting stress performance tests on the blockchain-based financial asset custody system, the data processing and logical operation capabilities of the blockchain-based financial asset custody system can be tested at different intervals to determine whether they can maintain a high-efficiency and accurate state, thereby determining the optimal data transmission delay time range for the blockchain-based financial asset custody system.

[0053] S102. Obtain the data transmission delay time of the blockchain-based financial asset custody system within a time period T, and label the data transmission delay time of the blockchain-based financial asset custody system within a time period T as Dl, where l = {1,2,3…k}, and k is a positive integer;

[0054] It should be noted that performance monitoring tools can be used to analyze and monitor the status of blockchain-based financial asset custody systems. Open-source system performance monitoring tools include Prometheus, InfluxDB, Zabbix, etc., which can use multi-dimensional data models, define multiple labels for monitoring data, and record and save performance data through time series.

[0055] S103. Obtain the data where the data transmission delay time Dl of the blockchain-based financial asset custody system exceeds the limit of the optimal data transmission delay time range Dt2 within a time period T, and label the data transmission delay time data that exceeds the limit of the optimal data transmission delay time range Dt2 as Dz, and z={1,2,3…j}, where j is a positive integer;

[0056] S104. The expression for calculating the transaction efficiency response latency coefficient Dx is as follows:

[0057] As can be seen from the expression of the transaction efficiency response delay coefficient, the larger the transaction efficiency response delay coefficient generated by the blockchain-based financial asset custody system within time T, the worse the stability and real-time performance of the blockchain-based financial asset custody system. Conversely, the smaller the transaction efficiency response delay coefficient generated by the blockchain-based financial asset custody system within time T, the better the stability and real-time performance of the blockchain-based financial asset custody system.

[0058] If the encryption rules of a blockchain-based financial asset custody system are too consistent, it will have the following adverse effects on the system:

[0059] Lack of flexibility: Highly consistent encryption rules can lead to an overly strict system that lacks flexibility. In the financial sector, adjustments are sometimes necessary to meet specific business needs or regulatory requirements. Excessive consistency rules can hinder the flexibility and adaptability of the system.

[0060] Low scalability: Enforcing highly consistent encryption rules may increase the burden on the system and reduce its scalability. If the system cannot scale effectively under high load, it may lead to performance degradation and affect the processing speed and efficiency of transactions.

[0061] Interaction difficulty: In the financial field, different institutions and systems may have different encryption standards and rules. If the encryption rules of a blockchain-based custody system are too consistent, it may increase the difficulty of interaction with other systems because they may not conform to the standards of other systems.

[0062] Overly conservative: Highly consistent encryption rules can make a system too conservative, hindering the adoption of new and more secure encryption technologies and algorithms. As the field of encryption continues to evolve, over-reliance on a single set of rules can cause a system to lag behind the latest security standards.

[0063] The calculation steps for the hash value conversion variability coefficient of a blockchain-based financial asset custody system are as follows:

[0064] S201. Obtain the hash conversion time of hash encryption transmission in the blockchain-based financial asset custody system, and mark the hash conversion time of hash encryption transmission in the blockchain-based financial asset custody system as Ta. Obtain the time when the server node performs hash conversion according to the encryption key in the blockchain-based financial asset custody system, and mark the time when the server node performs hash conversion according to the encryption key as Ts.

[0065] It should be noted that the timing of hash conversion for data transmission at the smart wearable device terminal is determined and declared based on the sensor monitoring logs of the smart wearable device, while the timing of hash conversion by the server node based on the encryption key is marked based on the server data processing logs.

[0066] S202. Based on the comparison of data content between the sending and receiving ends of the blockchain-based financial asset custody system during a complete data transmission cycle, calculate the data transmission integrity rate. The expression for the transmission integrity rate Ti is: In the formula, Re is the size of the data packet received by the receiving server node, and Se is the size of the data packet sent by the sending node;

[0067] S203. Compare the calculated transmission integrity rate with the preset transmission integrity rate. Under the premise of meeting the preset transmission integrity rate specified by the data transmission, calculate the difference between the frequency hopping time Ta at the transmitting end and the frequency modulation time Ts at the receiving end according to the standard clock. Then, the expression for calculating the frequency hopping time difference Td is Td=|Ta-Ts|.

[0068] It should be noted that the standard time is the time declared by the cesium atomic clock of the National Time Service Center;

[0069] S204. Based on the complete data transmission process of several cycles, integrate them into a hash conversion time difference data set, and label the hash conversion time difference as Tf, where f = {1,2,3…h}, where f is the number of the hash conversion time difference in the data set, and h is a positive integer;

[0070] S205. Calculate the standard deviation Pz of the hash transformation time difference dataset. The expression for calculating the standard deviation Pz is as follows: In the formula It is the average of the differences at each hash transformation time, i.e.

[0071] S206, the expression for calculating the hash value conversion rate coefficient Fc is Fc=Pz×exp(Pz 2 +1);

[0072] According to the calculation expression of the hash value conversion rate coefficient, the larger the hash value conversion rate coefficient of a blockchain-based financial asset custody system, the worse the stability and data security of the blockchain-based financial asset custody system. Conversely, the smaller the hash value conversion rate coefficient of a blockchain-based financial asset custody system, the better the stability and data security of the blockchain-based financial asset custody system.

[0073] Example 3

[0074] The operational status of blockchain-based financial asset custody systems is classified, and a hash encryption volatility index is calculated. The hash encryption volatility index Rd is calculated as follows: Rd = C * [exp(Dx) + ln(Fc)], where C is a constant related to the complexity of the financial asset custody system model framework, Dx is the transaction efficiency response delay coefficient, and Fc is the hash value conversion variability coefficient. As can be seen from the calculation expression of the hash encryption volatility index, the larger the transaction efficiency response delay coefficient and the larger the hash value conversion variability coefficient, the larger the hash encryption volatility index, and the worse the stability and data security of the blockchain-based financial asset custody system.

[0075] Calculate the hash-encrypted volatility index of the blockchain-based financial asset custody system, and compare the hash-encrypted volatility index of the blockchain-based financial asset custody system with a preset hash-encrypted volatility index threshold. When the hash-encrypted volatility index of the blockchain-based financial asset custody system is greater than or equal to the hash-encrypted volatility index threshold, it is marked as a risk signal. When the hash-encrypted volatility index of the blockchain-based financial asset custody system is less than the hash-encrypted volatility index threshold, it is marked as a steady-state signal.

[0076] The assessment and handling module integrates the risk signals marked within a period T into a risk signal dataset. The hash-encrypted volatility index within the dataset is then calibrated as Rs, where s is the hash-encrypted volatility index number, i.e., s = {1, 2, 3…g}, where g is a positive integer.

[0077] Calculate the standard deviation of several hash encryption volatility indices within the dataset, and denot the standard deviation of the hash encryption volatility index as Bj. Compare the standard deviation Bj of the hash encryption volatility index with a preset standard deviation threshold Dj of the hash encryption volatility index, and issue an early warning based on the comparison result. The processing logic is as follows:

[0078] If Bj is greater than or equal to Dj, the blockchain-based financial asset custody system is marked as high-risk, prompting staff to note that the blockchain-based financial asset custody system has serious potential risks and needs to be tested and verified.

[0079] If Bj is less than Dj, the blockchain-based financial asset custody system is marked as low-risk, indicating to staff that the blockchain-based financial asset custody system has low-risk potential and does not require testing or verification.

[0080] This invention detects the hash-encrypted volatility index of a blockchain-based financial asset custody system. When anomalies are detected in the stability and real-time performance of data processing, a comprehensive analysis of the subsequent operational status of the blockchain-based financial asset custody system is conducted to identify potential anomalies and issue early warnings. On the one hand, this allows staff to promptly detect potential anomalies and prevent risks caused by reduced stability and real-time performance of data processing, thereby effectively preventing system security risks. On the other hand, it facilitates staff monitoring the overall status of the blockchain-based financial asset custody system, improving monitoring and management efficiency.

[0081] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0082] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as computer program goods. The computer program goods include one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0083] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0084] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0085] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the system described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0086] If the aforementioned functions are implemented as software functional units and sold or used as independent goods, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of software goods. This computer software goods are stored in a storage medium and include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0087] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A blockchain-based financial asset custody system, characterized in that, It includes a data acquisition module, a model building module, a composite verification module, and an evaluation and handling module; The data acquisition module is used to collect transmission efficiency information and encryption stability information of the blockchain-based financial asset custody system, and transmit the transmission efficiency information and encryption stability information to the model building module; The model building module is used to conduct comprehensive analysis based on encryption stability information and transmission efficiency information, build a model, and evaluate and classify the operating status of blockchain-based financial asset custody system through mathematical analysis. The composite verification module is used to compare and analyze the operating status type of the blockchain-based financial asset custody system with the preset verification standards, and generate analysis signals. The assessment and handling module is used to make assessments and judgments based on different analytical signals. Through the identification and analysis of different signals, it uses mathematical modeling to assess the risk status of the blockchain-based financial asset custody system and issues risk notifications.

2. The blockchain-based financial asset custody system according to claim 1, characterized in that, The transmission efficiency information is the transaction efficiency response delay coefficient, and the encryption stability information is the hash value conversion rate coefficient.

3. The blockchain-based financial asset custody system according to claim 2, characterized in that, The calculation method for the transaction efficiency response latency coefficient is as follows: S101. Obtain the optimal data transmission delay time range of the blockchain-based financial asset custody system, and mark the optimal data transmission delay time range of the blockchain-based financial asset custody system as Dt1-Dt2; S102. Obtain the data transmission delay time of the blockchain-based financial asset custody system within a time period T, and label the data transmission delay time of the blockchain-based financial asset custody system within a time period T as Dl, where l = {1,2,3…k}, and k is a positive integer; S103. Obtain the data where the data transmission delay time Dl of the blockchain-based financial asset custody system exceeds the limit of the optimal data transmission delay time range Dt2 within a time period T, and label the data transmission delay time data that exceeds the limit of the optimal data transmission delay time range Dt2 as Dz, and z={1,2,3…j}, where j is a positive integer; S104. The expression for calculating the transaction efficiency response latency coefficient Dx is as follows:

4. The blockchain-based financial asset custody system according to claim 2, characterized in that, The calculation method for the hash value conversion rate coefficient is as follows: S201. Obtain the hash conversion time of hash encryption transmission in the blockchain-based financial asset custody system, and mark the hash conversion time of hash encryption transmission in the blockchain-based financial asset custody system as Ta. Obtain the time when the server node performs hash conversion according to the encryption key in the blockchain-based financial asset custody system, and mark the time when the server node performs hash conversion according to the encryption key as Ts. S202. Based on the comparison of data content between the sending and receiving ends of the blockchain-based financial asset custody system during a complete data transmission cycle, calculate the data transmission integrity rate. The expression for the transmission integrity rate Ti is: In the formula, Re is the size of the data packet received by the receiving server node, and Se is the size of the data packet sent by the sending node; S203. Compare the calculated transmission integrity rate with the preset transmission integrity rate. Under the premise of meeting the preset transmission integrity rate specified by the data transmission, calculate the difference between the frequency hopping time Ta at the transmitting end and the frequency modulation time Ts at the receiving end according to the standard clock. Then, the expression for calculating the frequency hopping time difference Td is Td=|Ta-Ts|. S204. Based on the complete data transmission process of several cycles, integrate them into a hash conversion time difference data set, and label the hash conversion time difference as Tf, where f = {1,2,3…h}, where f is the number of the hash conversion time difference in the data set, and h is a positive integer; S205. Calculate the standard deviation Pz of the hash transformation time difference dataset. The expression for calculating the standard deviation Pz is as follows: In the formula It is the average of the differences at each hash transformation time, i.e. S206, the expression for calculating the hash value conversion rate coefficient Fc is Fc=Pz×exp(Pz 2 +1).

5. The blockchain-based financial asset custody system according to claim 1, characterized in that, The logic behind using mathematical analysis to assess and classify the operational status of blockchain-based financial asset custody systems is as follows: The operational status of blockchain-based financial asset custody systems is classified, and the hash encryption volatility index is calculated. The hash encryption volatility index Rd is expressed as Rd=C*[exp(Dx)+ln(Fc)], where C is a constant related to the complexity of the financial asset custody system model framework, Dx is the transaction efficiency response delay coefficient, and Fc is the hash value conversion variability coefficient. The hash-encrypted volatility index of the blockchain-based financial asset custody system is calculated and compared with a preset hash-encrypted volatility index threshold. When the hash-encrypted volatility index of the blockchain-based financial asset custody system is greater than or equal to the hash-encrypted volatility index threshold, it is marked as a risk signal. When the hash-encrypted volatility index of the blockchain-based financial asset custody system is less than the hash-encrypted volatility index threshold, it is marked as a steady-state signal.

6. The blockchain-based financial asset custody system according to claim 5, characterized in that, The logic for assessing and issuing risk notifications based on different analytical signals is as follows: The risk signals marked within a period T are integrated into a risk signal dataset. The hash-encrypted volatility index within the dataset is denoted as Rs, where s is the hash-encrypted volatility index number, i.e., s = {1, 2, 3…g}, where g is a positive integer. Calculate the standard deviation of several hash encryption volatility indices within the dataset, and denot the standard deviation of the hash encryption volatility index as Bj. Compare the standard deviation Bj of the hash encryption volatility index with a preset standard deviation threshold Dj of the hash encryption volatility index, and issue an early warning based on the comparison result. The processing logic is as follows: If Bj is greater than or equal to Dj, the blockchain-based financial asset custody system is marked as high-risk, prompting staff to note that the blockchain-based financial asset custody system has serious potential risks and needs to be tested and verified. If Bj is less than Dj, the blockchain-based financial asset custody system is marked as low-risk, indicating to staff that the blockchain-based financial asset custody system has low-risk potential and does not require testing or verification.

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