Blockchain-based Scientific Research Data Depositing Method, Computer System, and Storage Medium

Abstract

The present invention relates to the field of information technology, and particularly relates to a scientific research data deposit method, a computer system and a storage medium based on a blockchain. The method includes the following steps: setting a host computer, collecting the working data of a scientific research device after the scientific research device is started; periodically packing the working data into a data packet, and associating the data packet with the scientific research device code and a timestamp as a deposit packet; extracting the hash value of the deposit packet, denoted as the deposit hash value; uploading the deposit hash value to the blockchain for storage to obtain the corresponding block height; storing the deposit packet in association with the deposit hash value and the block height; when verifying the deposit packet, extracting the hash value of the deposit packet and comparing it with the deposit hash value stored on the blockchain; if the extracted hash value of the deposit packet is consistent with the one stored on the blockchain, it is determined that the deposit packet is authentic. The substantial effect of the present invention is that by automatically collecting data packets after the scientific research device is started, the deposit of scientific research data is realized, and the authenticity of scientific research data can be guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of information technology, and particularly to a blockchain-based scientific research data deposit method, computer system, and storage medium. Background Art

[0002] Scientific research data is important basic data, which plays an irreplaceable and important role in the progress of human society and is also the cornerstone of the advancement of science and technology. Whether it is the proposal of scientific laws hundreds of years ago, or the development of new drugs today, the development of the digital earth, the discovery of the black hole photo, etc., all rely on the comprehensive analysis and utilization of the original data and related derivative data generated by experiments, observations, surveys, measurements, simulations, etc. Scientific research data has become a touchstone for testing the value of scientific research. On the one hand, scientific discoveries in many disciplines are data-based, aiming at new data discoveries, supplemented by mining tools and analysis means, and integrating data with important discoveries. On the other hand, data has become the test basis for repeating scientific experiments and ensuring the authenticity and reliability of research results. Therefore, it is of great significance to ensure the authenticity and integrity of scientific research data. However, current scientific research data is stored in the form of electronic data. Since electronic data is easily tampered with, it is difficult to ensure the authenticity of scientific research data, which affects the sharing, verification, and application of scientific research data. Therefore, it is necessary to study a deposit scheme suitable for scientific research data.

[0003] The prior art discloses a blockchain-based digital deposit platform. In this platform, the server performs a hash operation on a file in response to a request from a client to submit an electronic format file, and obtains a hash value corresponding to the file; the server exchanges information with a distributed file system, stores the file with the corresponding hash value as the name and obtains the storage ID of the file; the server exchanges information with a blockchain network, and submits the hash value, storage ID, and file creation information corresponding to the file to the blockchain network; the blockchain network stores transaction data through a smart contract and packages it into a block after successful consensus, and then returns the stored block transaction ID value to the server; the server locally stores the submitted file and the corresponding hash value, storage ID, and transaction ID of the file, and returns the storage status information of the file to the client. Although its technical solution can achieve the authenticity and reliability of data, its technical solution consumes a large amount of server resources and is not suitable for the deposit of scientific research data with a large quantity usually. Summary of the Invention

[0004] The technical problem to be solved by the present invention is the lack of a technical solution suitable for the scientific research data deposit scheme. A blockchain-based scientific research data deposit method, computer system, and storage medium are proposed, which can achieve the deposit of scientific research data.

[0005] To solve the above technical problems, the technical solution adopted by the present invention is as follows: A method for storing scientific research data based on blockchain, comprising the following steps:

[0006] Set up a host computer. After the scientific research equipment is started, the host computer automatically collects the working data of the scientific research equipment;

[0007] Periodically pack the working data into data packets, and associate the data packets with the scientific research equipment code and timestamp as storage evidence packets;

[0008] Extract the hash value of the storage evidence packet, denoted as the storage evidence hash value;

[0009] Upload the storage evidence hash value to the blockchain for storage to obtain the corresponding block height;

[0010] Store the storage evidence packet in association with the storage evidence hash value and the block height;

[0011] When verifying the storage evidence packet, extract the hash value of the storage evidence packet and compare it with the storage evidence hash value stored on the blockchain; if the extracted hash value of the storage evidence packet is consistent with the one stored on the blockchain, it is determined that the storage evidence packet is authentic; otherwise, if the extracted hash value of the storage evidence packet is inconsistent with the one stored on the blockchain, it is determined that the storage evidence packet has been modified.

[0012] Preferably, when extracting the storage evidence hash value, extract the hash value of the previous cycle's storage evidence packet together with the current cycle's storage evidence packet as the storage evidence hash value.

[0013] Preferably, the host computer is connected to multiple scientific research equipment, collects the working data of multiple scientific research equipment, and when packing the working data into data packets, intercepts part of the working data of other scientific research equipment and incorporates it into the data packets.

[0014] Preferably, the method for storing scientific research data further includes: adding the numbers and timestamps of the corresponding scientific research equipment before and after the part of the working data respectively.

[0015] Preferably, when extracting the storage evidence hash value, the following steps are also executed:

[0016] Establish a fast verification code extraction model, input the storage evidence packet into the fast verification code extraction model to obtain a fast verification code;

[0017] Upload both the fast verification code and the storage evidence hash value to the blockchain for storage;

[0018] When verifying the evidence deposit package, extract the quick verification code of the evidence deposit package. If the extracted quick verification code matches the one stored on the blockchain, it is determined that the evidence deposit package is genuine. If the extracted quick verification code does not match the one stored on the blockchain, then extract the hash value of the evidence deposit package. If the extracted hash value of the evidence deposit package is consistent with the one stored on the blockchain, it is determined that the evidence deposit package is genuine. Otherwise, if the extracted hash value of the evidence deposit package is inconsistent with the one stored on the blockchain, it is determined that the evidence deposit package has been modified.

[0019] Preferably, the method for establishing a quick verification code extraction model includes:

[0020] Set a label set and a data length;

[0021] Generate a number of sample data, where the sample data includes paired data values and labels. The number of digits of the data value matches the data length, and the label belongs to the label set;

[0022] Establish a neural network model. The input layer neurons of the neural network model respectively correspond to the values of each bit of the data value, and the output of the neural network model is the label;

[0023] Use a number of the sample data to train and test the neural network model until the accuracy rate of the neural network model reaches a preset threshold;

[0024] Represent the evidence deposit package in binary and divide it into a number of binary numbers according to a preset length. The data value of the binary number matches the data length;

[0025] Input the number of binary numbers into the trained neural network model one by one as the quick verification code extraction model, and the concatenation of the labels of all binary numbers is used as the quick verification code.

[0026] Preferably, the data value is represented in hexadecimal.

[0027] Preferably, the method for establishing a quick verification code extraction model further includes:

[0028] Divide the data value into multiple sub-data according to a preset bit length, and the neurons of the input layer of the neural network model correspond to the sub-data.

[0029] A computer system, the computer system includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the method for depositing scientific research data based on blockchain as described above.

[0030] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned blockchain-based scientific research data deposit method is implemented.

[0031] The substantial effect of the present invention is that after the scientific research equipment is started, data packets are automatically collected, and then a deposit package is formed to realize the deposit of scientific research data, which can ensure the authenticity of scientific research data; a faster verification method for the authenticity of scientific research data is formed through the quick verification code, providing a new verification method for the authenticity of scientific research data; the efficiency of verifying the authenticity of scientific research data can be improved by means of the quick verification code. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a schematic flowchart of the scientific research data deposit method in an embodiment of the present invention.

[0033] Figure 2 It is a schematic flowchart of the quick verification code extraction method in an embodiment of the present invention.

[0034] Figure 3 It is a schematic flowchart of the method for establishing a quick verification code extraction model in an embodiment of the present invention.

[0035] Figure 4 It is a schematic diagram of the computer system structure in an embodiment of the present invention.

[0036] Wherein: 11. Memory, 12. Computer program, 13. Processor. EMBODIMENTS

[0037] The following further specifically describes the specific embodiments of the present invention through specific embodiments and in conjunction with the drawings.

[0038] Before introducing the solution of this embodiment, the application scenario of this embodiment is introduced.

[0039] Blockchain is a distributed shared ledger and database, with characteristics such as decentralization, immutability, full traceability, traceability, collective maintenance, and public transparency. These characteristics ensure the "honesty" and "transparency" of the blockchain and lay a foundation for creating trust in the blockchain. Therefore, reliable data deposit can be provided by means of the blockchain, which is very suitable for the deposit of easily tampered electronic data.

[0040] In the deposition of electronic data, the hash function plays an important role. The hash function compresses a message or data into a digest, reducing the amount of data and fixing the data format. The hash function shuffles and mixes the data to recreate a fingerprint called the hash value, also known as the hash code. The hash value was initially used to improve the utilization rate of storage space and can enhance the query efficiency of data. The hash value is usually represented by a short string composed of random letters and numbers. A good hash function rarely has hash collisions in the input domain. By not suppressing collisions to distinguish data in hash tables and data processing, it makes it more difficult to find database records. Currently, hash functions are commonly used for encrypting data. Due to the irreversible nature of the hash function, it can effectively protect data and at the same time provide a unique mapping of the data. However, the current hash functions have low computational efficiency. When extracting the hash value of data, it takes a long time. When verifying the authenticity of data, it also takes a large amount of time to extract the hash value, making it very inconvenient to verify the authenticity of data.

[0041] Scientific research data directly comes from relevant instruments and equipment. None of the current electronic data deposition technologies directly collect data from instruments and equipment. Moreover, all current deposition technologies require personnel to initiate deposition actively, resulting in the possibility that the collected data may still be modified before deposition, and the authenticity of scientific research data cannot be ensured. For this reason, this embodiment provides a method for depositing scientific research data based on blockchain, which can solve the problems of still not high authenticity of scientific research data deposition and long verification time. Please refer to the appendix Figure 1 The method for depositing scientific research data provided in this embodiment includes the following steps:

[0042] Step A01) Set up a host computer. After the scientific research equipment is started, the host computer automatically collects the working data of the scientific research equipment;

[0043] Step A02) Periodically package the working data into data packets, and associate the data packets with the scientific research equipment code and timestamp as deposition packets;

[0044] Step A03) Extract the hash value of the deposition packet, denoted as the deposition hash value;

[0045] Step A04) Upload the deposition hash value to the blockchain for storage and obtain the corresponding block height;

[0046] Step A05) Store the deposition packet associated with the deposition hash value and the block height;

[0047] Step A06) When verifying the deposition packet, extract the hash value of the deposition packet and compare it with the deposition hash value stored on the blockchain;

[0048] Step A07): If the hash value of the extracted evidence package is consistent with that stored on the blockchain, it is determined that the evidence package is authentic. Conversely, if the hash value of the extracted evidence package is inconsistent with that stored on the blockchain, it is determined that the evidence package has been modified. By directly reading the working data of the scientific research equipment and periodically creating data packets from the working data and then forming an evidence package, the evidence of scientific research data can be directly formed, avoiding the risk of scientific research data being modified before evidence storage and ensuring the authenticity of scientific research data evidence.

[0049] When extracting the evidence hash value, the hash value of the evidence package in the previous cycle is extracted together with the evidence package in the current cycle as the evidence hash value. By extracting the hash value of the evidence package in the previous cycle together with the evidence package in the current cycle, when maliciously modifying scientific research data, it is necessary to continuously modify all the subsequent cycle's evidence hash values synchronously, significantly increasing the cost of modifying scientific research data and ensuring the reliability of scientific research data evidence.

[0050] The host computer is connected to multiple scientific research devices to collect the working data of multiple scientific research devices. When packing the working data into data packets, partial working data of other scientific research devices is intercepted and incorporated into the data packets. By incorporating partial working data of other scientific research devices, when partial data of other scientific research devices is tampered with, the tamperer also needs to find all the evidence packages that incorporate the same partial working data and make unified modifications to ensure that there are no traces of the modification. However, intercepting and incorporating partial working data of other scientific research devices into the data packets is completely random, and it is difficult for the tamperer to quickly find all the relevant evidence packages and can only traverse all the evidence packages, significantly increasing the difficulty and cost of tampering with data and thus improving the reliability of scientific research data evidence.

[0051] The scientific research data evidence method further includes: adding the numbers and timestamps of the corresponding scientific research devices before and after partial working data respectively.

[0052] To improve the verification efficiency of scientific research data evidence, in addition to the hash value verification method, this embodiment provides a new verification method, that is, using a quick verification code for verification. Please refer to the appendix Figure 2 , when extracting the evidence hash value, the following steps are also executed:

[0053] Step B01): Establish a quick verification code extraction model, input the evidence package into the quick verification code extraction model to obtain the quick verification code;

[0054] Step B02): Upload both the quick verification code and the evidence hash value to the blockchain for storage;

[0055] In step B03) when verifying the evidence deposit package, extract the quick verification code of the evidence deposit package. If the extracted quick verification code matches the one stored on the blockchain, it is determined that the evidence deposit package is authentic. If the extracted quick verification code does not match the one stored on the blockchain, then extract the hash value of the evidence deposit package. If the extracted hash value of the evidence deposit package is consistent with the one stored on the blockchain, it is determined that the evidence deposit package is authentic. Conversely, if the extracted hash value of the evidence deposit package is inconsistent with the one stored on the blockchain, it is determined that the evidence deposit package has been modified. The quick verification code is extracted by the quick verification code extraction model, forming two parallel verification paths with the hash value verification. The verification result takes the hash value verification as the final result. However, in the case where the probability of scientific research data being tampered with is low, or the loss caused by the tampering of scientific research data is small, there is no need to adopt the extremely time-consuming hash value verification method. The quick verification code method can be used for quick verification.

[0056] Please refer to the appendix Figure 3 , the method for establishing the quick verification code extraction model includes:

[0057] Step C01) Set the label set and data length;

[0058] Step C02) Generate a number of sample data. The sample data includes paired data values and labels. The number of digits of the data value matches the data length, and the label belongs to the label set;

[0059] Step C03) Establish a neural network model. The input layer neurons of the neural network model respectively correspond to the values of each bit of the data value, and the output of the neural network model is the label;

[0060] Step C04) Use a number of sample data to train and test the neural network model until the accuracy rate of the neural network model reaches the preset threshold;

[0061] Step C05) Represent the evidence deposit package in binary and divide it into a number of binary numbers according to the preset length. The data value of the binary number matches the data length;

[0062] Step C06) Input the number of binary numbers into the trained neural network model one by one as the quick verification code extraction model, and the concatenation of the labels of all binary numbers is used as the quick verification code.

[0063] The neural network model can be regarded as a kind of hyperfunction, which can establish a complex mapping relationship between the input and the output. Even if the mapping relationship itself has no regular pattern, a stable mapping can be established through the neural network model. The training of the neural network model is time-consuming, but the execution efficiency of the trained neural network model is extremely high, much higher than that of the hash function.

[0064] In this embodiment, the set tags range from 0 to 0xFFFFFFFF, that is, from 0 to 4294967295, with a total of 4294967296 tags. The length of the data value is 1Mb. The data value modulo 0xFFFFFFFF is the tag of the data value. Taking 1Mb of scientific research data as the input and the tag as the classification result, a neural network model can be used to achieve classification. Although the neural network model cannot classify correctly 100% of the time, when the same data value is assigned to the wrong tag and then classified again later, it will still be assigned to the same tag as before. As long as the neural network model is not retrained, it can be ensured that the same data value is always assigned to the same tag, regardless of whether the tag is exactly the remainder of the data value modulo 0xFFFFFFFF. Therefore, the situation where the accuracy rate of the neural network model cannot reach 100% does not affect the deposit and verification of the data value. Because for the same data value, the same quick verification code will always be obtained. Moreover, precisely due to this inaccuracy and uncertainty of the neural network model, the difficulty of keeping the tampered scientific research data the same as the quick verification code before tampering increases sharply, and is even impossible to achieve.

[0065] If the neural network model can be properly kept confidential and a confidential device provides the service of extracting the quick verification code without exposing the neural network model itself, then data protection can be well achieved. That is, the deposit and verification efficiency of scientific research data is significantly improved, and at the same time, the impact on authenticity is relatively small. Because the probability of tampering with 1Mb of scientific research data without causing a change in the quick verification code is 1 / 4294967296, which is an extremely low probability. For some cases where, based on information from other channels, it can be judged that the probability of scientific research data being tampered with is low, or the loss caused by tampering with scientific research data is not significant, the quick verification code is sufficient to prove the authenticity of scientific research data. For example, in the sharing of scientific research data, when the recipient of scientific research data selects scientific research data, it is not necessary to verify the authenticity of each optional scientific research data. It is only necessary to quickly verify the authenticity of several scientific research data that are of interest, and then, after further selecting the scientific research data to be finally received, verify the authenticity through the hash value method for the selected scientific research data to protect the interests of the recipient of scientific research data and at the same time be sufficient to exclude the impact of tampering with scientific research data on the selection of scientific research data.

[0066] The data value is represented in hexadecimal, and the tag value is also represented in hexadecimal data. The method for establishing the quick verification code extraction model further includes: dividing the data value into multiple sub-data according to a preset bit length, and the neurons in the input layer of the neural network model correspond to the sub-data.

[0067] A computer system, please refer to the appendix Figure 4, the computer system includes a memory, a processor, and a computer program 12 stored in the memory and executable on the processor. When the computer program 12 is executed by the processor, it implements the blockchain-based scientific research data deposit method as described above.

[0068] The computer device can be a general-purpose computer device or a special-purpose computer device. In a specific implementation, the computer device can be a server cluster including multiple servers, such as a blockchain system including multiple nodes. Those skilled in the art can understand that Figure 4 merely examples of computer devices, which do not constitute a limitation on computer devices, may include more or fewer components than shown in the figure, or combine certain components, or different components. For example, it may also include input / output devices, network access devices, etc.

[0069] The processor 13 can be a central processing unit (CPU). The processor 13 can also be other general-purpose processors 13, digital signal processors 13 (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor 13 can be a microprocessor 13 or any conventional processor 13.

[0070] In some embodiments, the memory 11 can be an internal storage unit of the computer device, such as the hard disk or memory of the computer device. In other embodiments, the memory 11 can also be an external storage device of the computer device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the computer device. Further, the memory 11 can also include both the internal storage unit and the external storage device of the computer device. The memory 11 is used to store an operating system, application programs, a boot loader, data, and other programs. The memory 11 can also be used to temporarily store data that has been output or will be output.

[0071] A computer-readable storage medium stores a computer program 12. When the computer program 12 is executed by a processor, it implements the blockchain-based scientific research data deposit method as described above.

[0072] The substantial effects of the present invention are as follows: After the scientific research equipment is started, data packets are automatically collected, and then an evidence storage packet is formed to achieve the evidence storage of scientific research data, which can ensure the authenticity of scientific research data; A faster verification method for the authenticity of scientific research data is formed through the quick verification code, providing a new verification method for the authenticity of scientific research data; With the help of the quick verification code, the efficiency of verifying the authenticity of scientific research data can be improved.

[0073] The above-described embodiments are only a preferred solution of the present invention, and do not impose any form of limitation on the present invention. There are other variations and modifications without exceeding the technical solutions recorded in the claims.

Claims

1. A method for depositing scientific research data based on blockchain, characterized in that: It includes the following steps: Set a host computer. After the scientific research equipment is started, the host computer automatically collects the working data of the scientific research equipment; Periodically pack the working data into data packets, and associate the data packets with the scientific research equipment code and timestamp as deposit packets; Extract the hash value of the deposit packet, denoted as the deposit hash value; Upload the deposit hash value to the blockchain for storage and obtain the corresponding block height; Store the deposit packet associated with the deposit hash value and the block height; When verifying the deposit packet, extract the hash value of the deposit packet and compare it with the deposit hash value stored on the blockchain; if the extracted hash value of the deposit packet is consistent with the one stored on the blockchain, it is determined that the deposit packet is authentic. Otherwise, if the extracted hash value of the deposit packet is inconsistent with the one stored on the blockchain, it is determined that the deposit packet has been modified; When extracting the deposit hash value, the following steps are also executed: Establish a fast verification code extraction model, input the deposit packet into the fast verification code extraction model, and obtain a fast verification code; Upload both the fast verification code and the deposit hash value to the blockchain for storage; When verifying the deposit packet, extract the fast verification code of the deposit packet. If the extracted fast verification code matches the one stored on the blockchain, it is determined that the deposit packet is authentic. If the extracted fast verification code does not match the one stored on the blockchain, extract the hash value of the deposit packet. If the extracted hash value of the deposit packet is consistent with the one stored on the blockchain, it is determined that the deposit packet is authentic. Otherwise, if the extracted hash value of the deposit packet is inconsistent with the one stored on the blockchain, it is determined that the deposit packet has been modified; The method for establishing a fast verification code extraction model includes: Set a label set and a data length; Generate a number of sample data, where the sample data includes paired data values and labels. The number of digits of the data value matches the data length, and the label belongs to the label set; Establish a neural network model. The input layer neurons of the neural network model respectively correspond to the values of each bit of the data value, and the output of the neural network model is the label; Use a number of the sample data to train and test the neural network model until the accuracy rate of the neural network model reaches a preset threshold; Represent the deposit packet in binary and divide it into a number of binary numbers according to a preset length. The data value of the binary number matches the data length; Input the number of binary numbers into the trained neural network model one by one as the fast verification code extraction model, and the concatenation of the labels of all binary numbers is used as the fast verification code.

2. The method for depositing scientific research data based on blockchain according to claim 1, characterized in that: When extracting the deposit hash value, extract the hash value of the deposit packet in the previous cycle together with the deposit packet in this cycle as the deposit hash value.

3. The method for depositing scientific research data based on blockchain according to claim 1 or 2, characterized in that: The host computer is connected to multiple scientific research equipment, collects the working data of multiple scientific research equipment, and when packing the working data into data packets, intercepts part of the working data of other scientific research equipment and incorporates it into the data packets.

4. The method for depositing scientific research data based on blockchain according to claim 3, characterized in that: The scientific research data archiving method further includes: adding the numbers of corresponding scientific research equipment and timestamps before and after the partial working data respectively.

5. The blockchain-based scientific research data archiving method according to claim 1, characterized in that The data value is represented in hexadecimal.

6. The blockchain-based scientific research data archiving method according to claim 1, characterized in that The method for establishing a fast verification code extraction model further includes: Dividing the data value into multiple sub-data according to a preset bit length, and the neurons of the input layer of the neural network model correspond to the sub-data.

7. A computer system, characterized in that, The computer system includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the blockchain-based scientific research data archiving method according to any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the blockchain-based scientific research data archiving method according to any one of claims 1 to 6.

Images