Data verification method for optical disk box
By performing classified verification of optical disc cassette data and using different granularity verification methods, the problem of insufficient data verification efficiency and security in the prior art is solved, and an efficient and safe data verification method is realized.
Patent Information
- Application Number
- CN202510493051.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-18
- Publication Date
- 2025-07-22
AI Technical Summary
The data verification method of existing optical disc cartridges is difficult to detect more errors at the same time without affecting the reading speed, and there is a risk of tampering.
The coarse particle size, fine particle size, fine particle size and adaptive particle size verification methods are used to classify the data units according to the attribute characteristics of the optical cartridge data, including factors such as data size, sensitivity and read and write frequency, and the verification particle size is dynamically adjusted.
It realizes efficient verification of optical disc cassette data, can detect more errors, ensure data accuracy and integrity, while keeping the reading speed unaffected, reducing operation and maintenance complexity and security risks.
Smart Images
Figure CN120356493A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of optical disc storage, and in particular to a data verification method for an optical disc cartridge. Background Art
[0002] An optical disc cartridge is a commonly used storage medium, which has the advantages of large capacity, rewritable, fast reading speed, etc. When using an optical disc cartridge, the accuracy of data is very important. Therefore, how to perform data verification is an important issue.
[0003] Currently, there are mainly two data verification methods for optical disc cartridges. One is to use a checksum for verification. The advantage of this method is simple and easy to implement, but it can only detect some errors and is easily tampered with by attackers. The other is to use a hash function for verification. The advantage of this method is that it can detect more errors and is not easily tampered with. However, the calculation amount of the hash function is relatively large, which will affect the reading speed.
[0004] Therefore, providing a data verification method that can detect more errors and does not affect the reading speed has important practical significance. Summary of the Invention
[0005] The present invention proposes a data verification method for an optical disc cartridge in view of the above problems.
[0006] The technical means adopted by the present invention are as follows:
[0007] A data verification method for an optical disc cartridge, comprising the following steps:
[0008] Step 1, obtain the optical disc cartridge data and divide the optical disc cartridge data into multiple data units;
[0009] Step 2, obtain the attribute characteristics of each data unit, and adopt a data verification strategy according to the attribute characteristics to obtain the verification method of each data unit, and the verification method includes coarse-grained verification, fine-grained verification, fine-grained verification and adaptive-grained verification;
[0010] Step 3, perform data verification on each data unit according to the obtained verification method.
[0011] Further, the attribute characteristics of the data unit include one or more of data size, data sensitivity, read-write frequency and data importance.
[0012] Further, the data verification strategy is specifically:
[0013] Judge whether the data importance or data sensitivity of the data unit is high. If so, the verification method of the data unit is fine-grained verification. If not, proceed to the next judgment;
[0014] Determine whether the read / write frequency of the data unit is greater than or equal to a first set threshold. If so, the verification method for the data unit is adaptive granularity verification. If not, proceed to the next determination;
[0015] Determine whether the data size of the data unit is greater than or equal to a second set threshold and the data importance is low. If so, the verification method for the data unit is coarse granularity verification. If not, the verification method for the data unit is fine granularity verification.
[0016] Further, the coarse granularity verification is specifically as follows:
[0017] When storing data, divide each data unit into several data blocks, each data block contains several data sectors, perform a hash calculation on each data block to obtain a first hash value, and store the first hash value in the block header data of the corresponding data block;
[0018] When reading data, perform a hash calculation on each data block to obtain a second hash value, and compare the second hash value with the first hash value in the block header data of the corresponding data block to complete data verification.
[0019] Further, the fine granularity verification is specifically as follows:
[0020] When storing data, divide each data unit into several data sectors, perform a hash calculation on each data sector to obtain a third hash value, and store the third hash value in the sector header data of the corresponding data sector;
[0021] When reading data, perform a hash calculation on each data sector to obtain a fourth hash value, and compare the fourth hash value with the third hash value in the sector header data of the corresponding data sector to complete data verification.
[0022] Further, the fine granularity verification is specifically as follows:
[0023] When storing data, divide each data unit into several data blocks, each data block contains several data sectors, perform a hash calculation on each data sector to obtain a fifth hash value, and add a verification data block to each data block, and store the fifth hash values of all data sectors in the verification data block;
[0024] When reading data, perform a hash calculation on each data sector to obtain a sixth hash value, and compare the sixth hash value with the fifth hash value in the verification data block to complete data verification.
[0025] Further, the adaptive granularity verification is specifically as follows:
[0026] When the system load ≤ 30%, fine granularity verification is adopted;
[0027] When the system load is between 30% and 70%, medium granularity verification is adopted;
[0028] When the system load ≥ 70%, coarse granularity verification is adopted.
[0029] Compared with the prior art, the data verification method for the optical disc cartridge disclosed by the present invention has the following beneficial effects: According to the attribute characteristics of the optical disc cartridge data, the optical disc cartridge data can be divided into four verification methods: coarse granularity verification, medium granularity verification, fine granularity verification, and adaptive granularity verification, so that different verification methods can be adopted for different optical disc cartridge data, thereby effectively verifying the optical disc cartridge data and ensuring the data reading speed at the same time. Description of the Drawings
[0030] Figure 1 It is a flowchart of the data verification method for the optical disc cartridge disclosed by the present invention. Detailed Embodiments
[0031] A data verification method for an optical disc cartridge includes the following steps:
[0032] Step 1: Obtain the optical disc cartridge data and divide the optical disc cartridge data into multiple data units;
[0033] Step 2: Obtain the attribute characteristics of each data unit, and adopt a data verification strategy according to the attribute characteristics to obtain the verification method for each data unit. The verification methods include coarse granularity verification, medium granularity verification, fine granularity verification, and adaptive granularity verification;
[0034] Step 3: Perform data verification on each data unit according to the obtained verification method.
[0035] Specifically, as Figure 1 shown, the data verification method for the optical disc cartridge disclosed in the present application includes three steps. Step 1: Obtain the optical disc cartridge data and divide it into multiple data units; Step 2: Obtain the attribute characteristics of each data unit, and judge the verification method used for the data unit according to the attribute characteristics. The verification methods include four types: coarse granularity verification, medium granularity verification, fine granularity verification, and adaptive granularity verification; Step 3: Perform data verification on the data unit by using the corresponding data verification method. In the present application, different data verification methods are adopted for verification according to different attribute characteristics of the data unit, thereby effectively verifying the optical disc cartridge data and ensuring the data reading and writing speed at the same time.
[0036] Meanwhile, the data verification method for the optical disc cartridge disclosed in the present invention realizes the intelligent management of the optical disc cartridge data: reducing manual intervention and improving the automation and intelligence levels of data management; performance optimization: intelligently selecting the verification granularity according to data characteristics, enhancing system performance and reducing resource consumption; enhancing data reliability: more accurately detecting and correcting data errors to ensure data integrity and accuracy; and reducing operation and maintenance risks: automated management reduces operation and maintenance complexity and decreases system failures and security risks.
[0037] Furthermore, the attribute characteristics of the data unit include one or more of data size, data sensitivity, read / write frequency, and data importance.
[0038] Specifically, the attribute characteristics of the data unit in this application include one or more of data size, data sensitivity, read / write frequency, and data importance. Classifying the verification methods of the data unit through these attribute characteristics can not only ensure the accuracy of important optical disc cartridge data, but also ensure the read / write speed of the optical disc cartridge data.
[0039] Furthermore, the data verification strategy is specifically as follows:
[0040] Judge whether the data importance or data sensitivity of the data unit is high. If so, the verification method of the data unit is fine-granularity verification. If not, proceed to the next judgment;
[0041] Judge whether the read / write frequency of the data unit is greater than or equal to the first set threshold. If so, the verification method of the data unit is adaptive-granularity verification. If not, proceed to the next judgment;
[0042] Judge whether the data size of the data unit is greater than or equal to the second set threshold and the data importance is low. If so, the verification method of the data unit is coarse-granularity verification. If not, the verification method of the data unit is fine-granularity verification.
[0043] Specifically, in this embodiment, the data verification policy is as follows: Obtain the level of data importance or data sensitivity of the data unit. The data importance or data sensitivity can generally be divided into three levels: high, medium, and low. The data importance or data sensitivity can be preset by the user or automatically classified based on data element attributes (such as file type, creator permissions, etc.). For example, personal information or financial information, etc., can be preset by the user as sensitive data, and its level is set to high. Set its importance according to business value, security level, etc. If the data importance or data sensitivity of the data unit is high, the verification method for the corresponding data unit adopts fine-grained verification, that is, more refined verification is performed on important data to prevent data loss or damage; if the data importance or data sensitivity of the data unit is not high, obtain the read-write frequency of the data unit, and judge the read-write frequency. If the read-write frequency of the data unit ≥ the first set threshold, the verification method for the corresponding data unit is adaptive granularity verification. The first set threshold can be set as needed. For example, it is determined through historical access data statistics or manually set. For example, the first set threshold is set to 10 times / day, that is, when the read-write frequency ≥ 10 times / day, adaptive granularity verification is adopted; if the read-write frequency of the data unit is less than the first set threshold, obtain the data size of the data unit, and judge whether the data size is greater than or equal to the second set threshold and the data importance is low. If so, the verification method for the data unit adopts coarse-grained verification. The second set threshold can be set as needed. For example, the second set threshold is set to 1GB; if all the above conditions are not met, the verification method for the data unit adopts fine-grained verification. Through the above data verification policy, the present application can effectively classify data units, and then implement different data verification methods for different data units, thus ensuring both the accuracy of the data in the optical disc cartridge and the read-write speed of the data in the optical disc cartridge.
[0044] Further, the coarse-grained verification is specifically as follows:
[0045] When storing data, each data unit is divided into several data blocks, each data block contains several data sectors, a hash calculation is performed on each data block to obtain a first hash value, and the first hash value is stored in the header data of the corresponding data block;
[0046] When reading data, a hash calculation is performed on each data block to obtain a second hash value, and the second hash value is compared with the first hash value in the header data of the corresponding data block to complete data verification.
[0047] Specifically, when it is determined through the data verification policy that the verification method of the data adopts the coarse-grained verification method for verification, the corresponding data unit is processed in the following manner. When storing the data, each data unit is divided into several data blocks, and each data block contains several data sectors. The size of the data block can be set as needed. For example, a data block contains 10 data sectors, and the size of each data sector can also be set as needed. For example, the size of a data sector is 512 bytes. A hash calculation (such as using the SHA-256 algorithm) is performed on each data block to obtain a first hash value, and the first hash value is stored in the header data of the corresponding data block. When reading the data, a hash calculation is performed on each data block to obtain a second hash value, and the second hash value is compared with the first hash value in the header data of the corresponding data block. If the first hash value is consistent with the second hash value, it indicates that the data is correct. If the first hash value is inconsistent with the second hash value, it indicates that the data has an error, thus completing the data verification.
[0048] Further, the fine-grained verification is specifically as follows:
[0049] When storing the data, each of the data units is divided into several data sectors, a hash calculation is performed on each of the data sectors to obtain a third hash value, and the third hash value is stored in the sector header data of the corresponding data sector;
[0050] When reading the data, a hash calculation is performed on each of the data sectors to obtain a fourth hash value, and the fourth hash value is compared with the third hash value in the sector header data of the corresponding data sector to complete the data verification.
[0051] Specifically, when it is determined through the data verification policy that the verification method of the data adopts the fine-grained verification method for verification, the corresponding data unit is processed in the following manner: When storing the data, each data unit is directly divided into several data sectors (the data part of the optical disc cartridge is directly divided into data units according to the sector size after the division of data blocks), a hash calculation is performed on each data sector to obtain a third hash value, and the third hash value is stored in the sector header data of the corresponding data sector. The size of each data sector can be set as needed. For example, the size of a data sector is 512 bytes. The hash calculation for each data sector can be performed using the SHA-256 algorithm. When reading the data, a hash calculation is performed on each data sector to obtain a fourth hash value, and the fourth hash value is compared with the third hash value in the sector header data of the corresponding data sector. If the third hash value is consistent with the fourth hash value, it indicates that the data is correct. If the third hash value is inconsistent with the fourth hash value, it indicates that the data has an error, thus completing the data verification.
[0052] Further, the fine granularity verification is specifically as follows:
[0053] When storing data, each of the data units is divided into a plurality of data blocks, each of the data blocks contains a plurality of data sectors, a hash calculation is performed on each of the data sectors to obtain a fifth hash value, and a verification data block is added to each of the data blocks, and the fifth hash values of all the data sectors are stored in the verification data block;
[0054] When reading data, a hash calculation is performed on each of the data sectors to obtain a sixth hash value, and the sixth hash value is compared with the fifth hash value in the verification data block to complete the data verification.
[0055] Specifically, when it is determined by the data verification policy that the verification method of the data adopts the fine granularity verification method for verification, the corresponding data unit is processed in the following manner: when storing data, each data unit is divided into a plurality of data blocks, each data block contains a plurality of data sectors, a hash calculation is performed on each data sector to obtain a fifth hash value, and a verification data block is added to each data block, and the fifth hash values of all data sectors are sequentially stored in the verification data block; when reading data, a hash calculation is performed on each data sector to obtain a sixth hash value, and the sixth hash value is compared with the fifth hash value in the sequential verification data block. If the fifth hash value is consistent with the sixth hash value, it indicates that the data is correct. If the fifth hash value is inconsistent with the sixth hash value, it indicates that the data has an error, thereby completing the data verification. In this embodiment, the size of the data block can be set as needed. For example, a data block contains 10 data sectors, and the size of each data sector can also be set as needed. For example, the size of a data sector is 512 bytes, and the hash calculation can be performed using the SHA-256 algorithm.
[0056] Further, the adaptive granularity verification is specifically as follows:
[0057] If the system load ≤ 30%, the fine granularity verification is adopted;
[0058] If the system load is between 30% and 70%, the fine granularity verification is adopted;
[0059] If the system load ≥ 70%, the coarse granularity verification is adopted.
[0060] Specifically, when it is determined through the data verification policy that the verification method of the data adopts the adaptive granularity verification method for verification, the following processing is performed: Obtain the system load of the optical disc cartridge device. In this embodiment, the system load is obtained by the weighted average of the CPU and memory occupancy rates of the optical disc cartridge device. For example, the weight of the CPU is 0.6, and the weight of the memory is 0.4. Then, calculate the obtained system load and determine whether the system load is less than or equal to 30%. If so, perform data verification using fine-grained verification. If the system load is between 30% and 70%, use medium-grained verification. If the system load is greater than or equal to 70%, use coarse-grained verification. Through this method, it is possible to automatically select the most appropriate verification granularity to verify the data, thereby ensuring the accuracy of the optical disc cartridge data and also ensuring the read and write speed of the optical disc cartridge data. By setting the adaptive granularity verification method in this application, the verification granularity of the data unit is dynamically adjusted, that is, for frequently accessed and important data, the system may select medium-grained or fine-grained verification to ensure data accuracy; for infrequently accessed and less important data, coarse-grained verification may be selected to improve the reading efficiency.
[0061] As described above, the above is only the preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, makes equivalent substitutions or changes, and should be covered by the protection scope of the present invention.
Claims
1. A data verification method for an optical disc cartridge, characterized in that: It includes the following steps: Step 1: Obtain the optical disc cartridge data and divide the optical disc cartridge data into multiple data units; Step 2: Obtain the attribute characteristics of each data unit, and adopt a data verification strategy according to the attribute characteristics to obtain the verification method for each data unit. The verification methods include coarse-grained verification, fine-grained verification, fine-grained verification, and adaptive-grained verification; Step 3: Perform data verification on each data unit according to the obtained verification method.
2. The data verification method of the optical disc cartridge according to claim 1, wherein: The attribute characteristics of the data unit include one or more of data size, data sensitivity, read / write frequency, and data importance.
3. The data verification method of the optical disc cartridge according to claim 2, characterized in that: The specific data verification strategy is as follows: Judge whether the data importance or data sensitivity of the data unit is high. If so, the verification method of the data unit is fine-grained verification. If not, proceed to the next judgment; Judge whether the read / write frequency of the data unit is greater than or equal to the first set threshold. If so, the verification method of the data unit is adaptive-grained verification. If not, proceed to the next judgment; Judge whether the data size of the data unit is greater than or equal to the second set threshold and the data importance is low. If so, the verification method of the data unit is coarse-grained verification. If not, the verification method of the data unit is fine-grained verification.
4. The data verification method of the optical disc cartridge according to claim 1, wherein: The specific coarse-grained verification is as follows: When storing data, divide each data unit into several data blocks, each data block contains several data sectors, perform a hash calculation on each data block to obtain a first hash value, and store the first hash value in the block header data of the corresponding data block; When reading data, perform a hash calculation on each data block to obtain a second hash value, and compare the second hash value with the first hash value in the block header data of the corresponding data block to complete data verification.
5. The data verification method of the optical disc cartridge according to claim 1, characterized in that: The specific fine-grained verification is as follows: When storing data, divide each data unit into several data sectors, perform a hash calculation on each data sector to obtain a third hash value, and store the third hash value in the sector header data of the corresponding data sector; When reading data, perform a hash calculation on each data sector to obtain a fourth hash value, and compare the fourth hash value with the third hash value in the sector header data of the corresponding data sector to complete data verification.
6. The data verification method of the optical disc cartridge according to claim 1, characterized in that: The specific fine-grained verification is as follows: When storing data, divide each data unit into several data blocks, each data block contains several data sectors, perform a hash calculation on each data sector to obtain a fifth hash value, and add a verification data block to each data block, and store the fifth hash values of all data sectors in the verification data block; When reading data, perform a hash calculation on each data sector to obtain a sixth hash value, and compare the sixth hash value with the fifth hash value in the verification data block to complete data verification.
7. The data verification method of the optical disc cartridge according to claim 1, characterized in that: The specific adaptive-grained verification is as follows: If the system load ≤ 30%, adopt fine-grained verification; If the system load is between 30% and 70%, adopt fine-grained verification; When the system load ≥ 70%, coarse-grained verification is adopted.