A copyright evidence storage management method and system based on a blockchain

Abstract

This invention relates to the field of blockchain technology and provides a blockchain-based copyright evidence management method and system. The method includes: comparing the current fragment-level evidence storage time offset with a threshold inflection point; when the offset exceeds the threshold inflection point, generating a corresponding correction factor based on the degree of excess; and correcting the fragment-level redundant evidence storage strength of the target government video archive based on the correction factor. This invention addresses the impact of fragment-level evidence storage time offset on subsequent evidence collection, auditing, or liability determination comparison results in multi-platform distribution and authorization scenarios. It proposes a method to construct the relationship between fragment-level evidence storage time offset and fragment correspondence matching error rate based on historical evidence storage samples. By identifying the threshold inflection point, it transforms time offset differences that were originally considered to be within a tolerable range into quantifiable control criteria.

Description

Technical Field

[0001] This invention belongs to the field of blockchain technology, and in particular relates to a blockchain-based copyright evidence management method and system. Background Technology

[0002] With the continuous advancement of digital government construction, the demand for the digitization, structuring, and traceability management of government data is increasing. In particular, government video archives, as important carriers of electronic evidence, are widely used in scenarios such as law enforcement recording, administrative approval, public services, and emergency response. To ensure the authenticity, integrity, and immutability of government video archives, copyright preservation methods based on blockchain technology are gradually being introduced. Through distributed ledgers, timestamp solidification, and multi-node consensus mechanisms, the generation time, content characteristics, and circulation process of government video archives are reliably recorded, thereby enhancing the credibility of government data management.

[0003] In practical applications, government video archives often need to be shared and transferred between multiple business systems or government platforms. This includes access between different departmental systems, synchronization between provincial and municipal platforms, and data exchange between law enforcement, auditing, and archiving systems, creating a multi-platform distribution and authorization scenario. In this scenario, the same government video archive typically requires segment-level copyright registration at multiple storage nodes and synchronization across different platforms. Due to differences in system architecture, processing capabilities, network environment, and node load across platforms, time discrepancies can easily arise during the multi-node writing and cross-platform synchronization of segment-level evidence data, leading to inconsistent storage times for the same video segment across different nodes or platforms.

[0004] Existing technologies typically handle these time differences through time synchronization mechanisms, delay compensation strategies, or data alignment methods to maintain the stability of the overall evidence preservation process. However, most of these technologies focus on ensuring data consistency during the evidence preservation stage, lacking in-depth analysis of the potential impact of such time differences on subsequent evidence collection, auditing, or liability determination processes. Especially in scenarios requiring segment-level comparison or evidence verification of government video archives, these time differences may affect the accuracy of segment correspondence matching, but existing technologies have not yet provided effective means to analyze historical data and proactively control this impact, thus affecting the stability and reliability of government video archive comparison results to some extent. Summary of the Invention

[0005] The purpose of this invention is to provide a blockchain-based copyright registration and management method and system, which aims to solve the problems mentioned in the background art.

[0006] This invention is implemented as follows: a blockchain-based copyright registration and management method, the method comprising:

[0007] S1. When the current segment-level copyright certificate of the target government video archive is under the multi-platform distribution and authorization scenario, the preset copyright certificate database is retrieved, and several historical certificate samples corresponding to the current copyright certificate status are selected from it; the "copyright certificate" refers to the credible record of the ownership information, generation time and circulation process of the government video archive.

[0008] S2. Determine the fragment-level evidence storage time offset generated during the multi-node writing and cross-platform synchronization of fragment-level evidence storage data for each historical evidence storage sample, as well as the fragment correspondence matching error rate in subsequent fragment evidence collection, auditing, or liability determination comparison stages.

[0009] S3. Based on the changing relationship between the fragment-level evidence storage time offset and the fragment correspondence matching error rate of each historical evidence storage sample, determine the threshold inflection point corresponding to the fragment-level evidence storage time offset according to the changing relationship; below the threshold inflection point, the fragment correspondence matching error rate remains stable, and above the threshold inflection point, the fragment correspondence matching error rate shows an upward trend.

[0010] S4. Compare the current fragment-level evidence storage time offset with the threshold inflection point. When it exceeds the threshold inflection point, generate a corresponding correction factor based on the degree of excess, and correct the fragment-level redundant evidence storage strength of the target government video archive based on the correction factor.

[0011] As a further limitation of the technical solution of the present invention, the fragment-level copyright evidence data generated during the fragment-level copyright evidence preservation process includes at least the government video archive fragment identifier, fragment metadata, distribution platform identifier, and authorization record.

[0012] As a further limitation of the technical solution of the present invention, the correspondence with the current copyright evidence preservation status specifically refers to the fact that the historical evidence preservation samples and the current target government video archives are the same as or within a preset similar range in at least one of the specific evidence preservation data types, number of distribution platforms, number of segments, node load status, and authorization synchronization frequency.

[0013] As a further limitation of the technical solution of the present invention, the specific calculation process of the fragment-level evidence storage time offset includes: extracting the evidence storage time information corresponding to the same government video archive fragment at different evidence storage nodes or distribution platforms, determining the maximum time value and the minimum time value in the evidence storage time information, and taking the difference between the maximum time value and the minimum time value as the fragment-level evidence storage time offset.

[0014] As a further limitation of the technical solution of the present invention, the historical evidence sample is limited to the existence of subsequent fragment evidence collection, auditing or liability determination comparison process, and the fragment correspondence matching result is generated in the comparison process.

[0015] As a further limitation of the technical solution of the present invention, the specific calculation process of the segment correspondence matching error rate includes: performing segment-level matching between historical government video archive segments of historical evidence samples and corresponding evidence collection, auditing or responsibility determination comparison video segments, counting the number of historical government video archive segments that failed to match, and determining the segment correspondence matching error rate as the ratio of the number of historical government video archive segments that failed to match to the total number of historical government video archive segments participating in the matching.

[0016] As a further limitation of the technical solution of this embodiment of the invention, the process of establishing the change relationship includes:

[0017] Several historical evidence samples are sorted in ascending order of fragment-level evidence time offset to obtain an ordered sample sequence;

[0018] Extract the segment correspondence matching error rate corresponding to each historical evidence sample in the ordered sample sequence, and construct a change curve based on the segment-level evidence storage time offset and the corresponding segment correspondence matching error rate to characterize the change relationship between the two.

[0019] As a further limitation of the technical solution of this embodiment of the invention, step S4 specifically includes:

[0020] Obtain the fragment-level copyright registration time offset generated during the current fragment-level copyright registration process, and compare the fragment-level copyright registration time offset with the threshold inflection point;

[0021] When the current fragment-level evidence storage time offset does not exceed the threshold inflection point, the current fragment-level redundant evidence storage strength remains unchanged;

[0022] When the current fragment-level evidence storage time offset exceeds the threshold inflection point, a corresponding correction factor is generated according to the degree of exceeding the threshold inflection point, and the fragment-level redundant evidence storage strength of the target government video archive is improved based on the correction factor to improve the stability of fragment-level copyright evidence storage data.

[0023] The improved correction includes at least one or more of the following: increasing the multi-node confirmation level of critical segments, increasing the frequency of segment-level metadata synchronization, and increasing the number of redundant backups of segment authorization records.

[0024] As a further limitation of the technical solution of this invention embodiment, when improving the evidence strength of fragment-level redundancy in the target government video archive, a preset segmented correction function is adopted, the correction function including:

[0025] ;

[0026] in, This refers to the corrected fragment-level redundancy evidence strength. This refers to the initial fragment-level redundancy evidence strength. This refers to the upper limit of the value of fragment-level redundancy evidence strength. This refers to the current fragment-level evidence storage time offset. This refers to the threshold inflection point. This refers to exceeding the limit. This refers to the preset control correction strength coefficient, and it satisfies... Greater than 0, This refers to the correction factor.

[0027] A blockchain-based copyright registration and management system, the system comprising:

[0028] The sample screening module is used to retrieve a preset copyright certificate database and select several historical certificate samples that correspond to the current copyright certificate status when the current segment-level copyright certificate of the identified target government video archive is in a multi-platform distribution and authorization scenario.

[0029] The parameter calculation module is used to determine the fragment-level evidence storage time offset generated by each historical evidence sample during the multi-node writing and cross-platform synchronization of fragment-level evidence storage data, as well as the fragment correspondence matching error rate in the subsequent fragment evidence collection, auditing or liability determination comparison stages.

[0030] The inflection point determination module is used to determine the threshold inflection point corresponding to the fragment-level evidence storage time offset and the fragment correspondence matching error rate based on the changing relationship between the fragment-level evidence storage time offset and the fragment correspondence matching error rate of each historical evidence storage sample. Below the threshold inflection point, the fragment correspondence matching error rate remains stable, while above the threshold inflection point, the fragment correspondence matching error rate shows an upward trend.

[0031] The correction control module is used to compare the current fragment-level evidence storage time offset with the threshold inflection point. When it exceeds the threshold inflection point, a corresponding correction factor is generated according to the degree of excess, and the fragment-level redundant evidence storage strength of the target government video archive is corrected based on the correction factor.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] This invention addresses the impact of fragment-level evidence storage time offset on subsequent evidence collection, auditing, or liability determination comparison results in multi-platform distribution and authorization scenarios. It proposes a method to construct the relationship between fragment-level evidence storage time offset and fragment correspondence matching error rate based on historical evidence samples. By identifying threshold inflection points, time offset differences previously considered within a tolerable range are transformed into quantifiable control criteria. Furthermore, when the current fragment-level evidence storage time offset exceeds the threshold inflection point, a correction factor is generated based on the degree of excess, dynamically adjusting the strength of fragment-level redundant evidence storage, thereby providing preemptive compensation before evidence collection, auditing, or liability determination occurs. Compared to existing technologies, this invention achieves a shift from ex-post correction to ex-ante prevention, effectively controlling redundant resource investment while ensuring the stability of fragment correspondence matching, thus possessing high practical value and widespread applicability. Attached Figure Description

[0034] Figure 1 A flowchart of the method provided in the embodiments of the present invention;

[0035] Figure 2 This is a flowchart illustrating the process of correcting the fragment-level redundancy evidence strength of a target government video archive in the method provided in this embodiment of the invention;

[0036] Figure 3 The application architecture diagram of the system provided in the embodiments of the present invention. Detailed Implementation

[0037] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0038] Figure 1 A flowchart of the method provided by an embodiment of the present invention is shown.

[0039] Specifically, a blockchain-based copyright registration and management method includes the following steps:

[0040] Step S1: When the current segment-level copyright registration of the target government video archive is identified as being distributed and authorized across multiple platforms, a preset copyright registration database is retrieved, and several historical registration samples corresponding to the current copyright registration status are selected. The segment-level copyright registration data generated during the segment-level copyright registration process includes at least the government video archive segment identifier, segment metadata, distribution platform identifier, and authorization record. "Copyright registration" broadly refers to a reliable record of the ownership information, generation time, and circulation process of government video archives.

[0041] The historical evidence samples are limited to those that have undergone subsequent fragment evidence collection, auditing, or liability determination comparison processes, and for which fragment correspondence matching results are generated during the comparison process. The correspondence with the current copyright evidence preservation status specifically refers to the historical evidence samples and the current target government video archives being identical or within a preset similarity range in at least one of the following: specific evidence data type, number of distribution platforms, number of fragments, node load status, and authorization synchronization frequency.

[0042] In this embodiment of the invention, blockchain technology has been widely applied in copyright registration scenarios. Through distributed ledgers, immutability, and timestamp-based authentication, it achieves a reliable record of the consistency of the creation time and content of digital works. In typical single-platform copyright registration scenarios, government video archives typically only require registration on a single platform after uploading. The processing chain is short, and there is no need for segment-level copyright registration data synchronization across multiple distribution platforms. Therefore, segment-level registration time offsets with analytical significance are usually not generated. In contrast, in multi-platform distribution and authorization scenarios, after initial copyright registration, the same target government video archive needs to be authorized and distributed to multiple distribution platforms. Correspondingly, segment-level copyright registration data corresponding to the same government video archive segment needs to be written to multiple registration nodes and synchronized across different distribution platforms. This results in time differences between different nodes or platforms for the same government video archive segment, i.e., segment-level registration time offsets.

[0043] For government video archives, the process of segment-level copyright registration typically involves dividing the target government video archive into several segments and generating corresponding segment-level copyright registration data for each segment. In multi-platform distribution and authorization scenarios, this segment-level copyright registration data undergoes processing steps such as multi-node writing, cross-platform synchronization, and authorization status updates. Due to differences in interface response speed, network transmission status, node load status, and synchronization scheduling rhythm among different distribution platforms, inconsistencies may occur in the registration time information for the same government video archive segment across different nodes or distribution platforms, resulting in segment-level registration time offsets.

[0044] It should be noted that when the fragment-level evidence storage time offset is within a small range, existing systems can usually absorb or correct this offset through mechanisms such as synchronization buffering, time alignment, index compensation, or post-processing correction. In other words, while the fragment-level evidence storage time offset objectively exists, it is insufficient to significantly affect the subsequent processing results. In other words, when the offset is small, the system itself possesses a certain degree of fault tolerance and resilience; therefore, this fluctuation is generally considered a normal phenomenon within an acceptable range in the field.

[0045] However, during the research process of this invention, it was found that in some historical evidence samples, especially in historical evidence cases where subsequent fragment evidence collection, auditing, or liability determination processes occurred and fragment correspondence matching results were generated, fragment-level evidence time offset is not always a negligible factor. Specifically, the fragment evidence collection, auditing, or liability determination process refers to, after receiving a claim for evidence collection, auditing, or liability determination against a specific government video archive, performing fragment-level copyright evidence data corresponding to the specified government video archive and matching it with the video to be compared. By extracting video fragment features and performing similarity calculations, the correspondence between the specified government video archive fragment and the video fragment to be compared is determined, thereby generating fragment correspondence matching results. In this process, the fragment correspondence matching error rate can be obtained by statistically analyzing the proportion of the number of specified government video archive fragments that failed to match to the total number of specified government video archive fragments participating in the matching.

[0046] Further analysis revealed that in multi-platform distribution and authorization scenarios, when the fragment-level evidence storage time offset is within a small range, the system's inherent time alignment, fragment index correction, and matching fault tolerance capabilities typically keep the fragment correspondence matching error rate stable or only slightly altered. However, when the fragment-level evidence storage time offset increases beyond a certain range, the system's original compensation capabilities become insufficient. The fragment time axis misalignment, accumulated fragment index offset, and synchronization delay amplification effects caused by cross-platform time inconsistencies gradually become apparent, leading to an increase in the fragment correspondence matching error rate. Although this increase may not be drastic in some scenarios and is not easily noticeable in the short term, it adversely affects the accuracy of the evidence chain and the reliability of fragment mapping in subsequent evidence collection, auditing, or liability determination processes.

[0047] Based on the above findings, this invention proposes that when performing segment-level copyright evidence preservation in a multi-platform distribution and authorization scenario for the current target government video archive, even if it is not yet certain whether subsequent evidence collection, auditing, or liability determination will occur, the segment-level redundancy evidence preservation strength can be increased in advance when the segment-level evidence preservation time offset reaches or approaches a preset tolerance threshold. This can proactively suppress the potential increase in the segment correspondence matching error rate. The segment-level redundancy evidence preservation strength refers to the degree of redundancy protection configured for the same government video archive segment during copyright evidence preservation, which can be specifically reflected in multi-node confirmation levels, segment-level metadata synchronization frequency, and the number of redundant backups of authorization records. By increasing the segment-level redundancy evidence preservation strength, the consistency, recoverability, and anti-offset capability of segment-level copyright evidence preservation data in a multi-platform distribution and authorization scenario can be enhanced, thereby reducing the risk of an increase in the segment correspondence matching error rate if subsequent evidence collection, auditing, or liability determination occurs.

[0048] In step S1, the target government video archive can be any government video archive work to be processed for copyright registration. It can originate from video files uploaded by content creators, video content generated within the platform, or external video resources imported with authorization. The preset copyright registration database is usually gradually accumulated by the blockchain registration system during long-term operation. Its underlying structure can include on-chain registration records, off-chain extended storage data, and log data related to the registration process. Specifically, it can include fragment-level copyright registration data of historical government video archives, corresponding registration time information, multi-node write records, cross-platform synchronization records, and subsequent fragment evidence collection, auditing, or liability determination results data. The acquisition of the above data can be achieved through existing blockchain data reading interfaces, log collection mechanisms, and data retrieval methods of copyright management systems, which are conventional technical means in this field.

[0049] In step S1, several historical evidence samples corresponding to the current copyright evidence storage conditions are selected from the copyright evidence storage database. The purpose is to construct a data foundation similar to the current target government video archive evidence storage environment, so as to ensure that the subsequent relationship between the segment-level evidence storage time offset and the segment correspondence matching error rate established based on historical data has reference value and comparability. If no selection is performed and all historical data is used directly, noise data can easily be introduced due to the large differences between different evidence storage scenarios, thereby affecting the accuracy of the threshold inflection point determination.

[0050] Furthermore, this invention sets relatively strict screening criteria for historical evidence samples. For example, it requires that historical evidence samples and current target government video archives be identical or within a preset similarity range in at least one of the following: evidence data type, number of distribution platforms, number of segments, node load status, and authorized synchronization frequency. This is because the above factors directly affect the segment-level evidence time offset and subsequent matching error rate. By controlling the consistency or similarity of these key factors, systematic differences between different samples can be effectively reduced, and the accuracy of change relationship analysis can be improved.

[0051] Furthermore, the screening criteria can be expanded according to actual application needs, such as including factors like network bandwidth status, node geographical distribution, evidence storage time window range, and video content complexity. The preset similarity range can be pre-set based on historical statistical data, empirical parameters, or through data analysis models. Its purpose is to allow for a certain degree of fluctuation, thereby ensuring sample comparability while avoiding insufficient sample size due to overly strict conditions. Since it is difficult to obtain completely identical historical evidence storage scenarios in actual system operation, adopting the method of "same or within the preset similarity range" can achieve a balance between sample quality and sample quantity, thereby improving the overall stability and applicability of the method.

[0052] Furthermore, the blockchain-based copyright evidence management method also includes the following steps:

[0053] Step S2: Determine the fragment-level evidence storage time offset generated during the multi-node writing and cross-platform synchronization of fragment-level evidence storage data for each historical evidence storage sample, as well as the fragment correspondence matching error rate in subsequent fragment evidence collection, auditing, or liability determination comparison stages.

[0054] The specific calculation process of the segment-level evidence storage time offset includes: extracting the evidence storage time information of the same government video archive segment at different evidence storage nodes or distribution platforms, determining the maximum and minimum time values ​​in the evidence storage time information, and using the difference between the maximum and minimum time values ​​as the segment-level evidence storage time offset.

[0055] The specific calculation process for the segment correspondence matching error rate includes: performing segment-level matching between historical government video archive segments of historical evidence samples and corresponding evidence collection, auditing, or liability determination comparison video segments; counting the number of historical government video archive segments that failed to match; and determining the segment correspondence matching error rate as the ratio of the number of historical government video archive segments that failed to match to the total number of historical government video archive segments that participated in the matching.

[0056] In this embodiment of the invention, step S2 is a key step in the data quantification processing of historical evidence samples. Its purpose is to structure the differences in fragment-level evidence storage time generated in multi-platform distribution and authorization scenarios, as well as the comparison results of subsequent fragment evidence collection, auditing, or liability determination, so as to facilitate the establishment of the relationship between the fragment-level evidence storage time offset and the error rate of fragment correspondence matching.

[0057] Specifically, the calculation of the fragment-level evidence storage time offset is based on the difference in evidence storage time information between different evidence storage nodes or distribution platforms for the same government video archive fragment. In multi-platform distribution and authorization scenarios, the same government video archive fragment is usually written to multiple evidence storage nodes and synchronized between different distribution platforms, thus generating multiple corresponding evidence storage time information. In this embodiment, by extracting the evidence storage time information of the same government video archive fragment corresponding to different evidence storage nodes or distribution platforms, the maximum and minimum time values ​​in the evidence storage time information are determined, and the difference between the maximum and minimum time values ​​is used as the fragment-level evidence storage time offset, thereby characterizing the maximum time difference of the government video archive fragment in the cross-node, cross-platform processing process.

[0058] It should be noted that the calculation method for the fragment-level evidence storage time offset is not limited to the above-mentioned maximum time difference form. In other embodiments, different statistical methods can be used to determine it according to actual application needs. For example, the fragment-level evidence storage time offset can also be calculated by the average time difference, weighted average time difference, or time dispersion between the corresponding evidence storage time information of the same government video archive fragment at different evidence storage nodes or distribution platforms. Among them, the average time difference can reflect the overall time offset level, the weighted average time difference can be adjusted according to the importance of different nodes or distribution platforms, and the time dispersion is used to measure the degree of dispersion of the distribution of each evidence storage time information, thereby characterizing the features of the fragment-level evidence storage time offset from different perspectives.

[0059] On the other hand, the calculation of the segment correspondence matching error rate is based on the statistical analysis of the segment correspondence matching results generated by historical evidence samples in subsequent segment evidence collection, auditing, or liability determination comparison stages. Specifically, by performing segment-level matching between historical government video archive segments of historical evidence samples and corresponding video segments used for evidence collection, auditing, or liability determination comparison, the number of historical government video archive segments that failed to match is counted, and the ratio of the number of historical government video archive segments that failed to match to the total number of historical government video archive segments participating in the matching is determined as the segment correspondence matching error rate. The segment correspondence matching error rate is used to characterize the accuracy of segment matching during the evidence collection, auditing, or liability determination comparison process; the higher the value, the more significant the matching error.

[0060] It should be further noted that the method for calculating the segment correspondence matching error rate described above is a relatively common technique in this field, especially in applications such as video forensics, auditing or liability determination, content comparison, and similarity analysis. The accuracy of the matching results is typically measured by statistically analyzing the proportion of failed matches or the proportion of mismatches. Therefore, this invention does not aim to improve the matching error rate calculation method itself, but rather to perform a correlation analysis between the matching error rate and the segment-level evidence storage time offset to uncover the patterns of change between them and determine subsequent control strategies accordingly.

[0061] Furthermore, the blockchain-based copyright evidence management method also includes the following steps:

[0062] Step S3: Based on the changing relationship between the fragment-level evidence storage time offset and the fragment correspondence matching error rate of each historical evidence storage sample, determine the threshold inflection point corresponding to the fragment-level evidence storage time offset according to the changing relationship; wherein, below the threshold inflection point, the fragment correspondence matching error rate remains stable, and above the threshold inflection point, the fragment correspondence matching error rate shows an upward trend.

[0063] The process of establishing the change relationship includes: sorting several historical evidence samples in ascending order of fragment-level evidence time offset to obtain an ordered sample sequence; extracting the fragment correspondence matching error rate of each historical evidence sample in the ordered sample sequence; and constructing a change curve based on the fragment-level evidence time offset and the corresponding fragment correspondence matching error rate to characterize the change relationship between the two.

[0064] In this embodiment of the invention, step S3 is the core step of the correlation analysis between the segment-level evidence storage time offset and the segment correspondence error rate obtained in step S2. Its purpose is to verify, based on historical evidence storage sample data, whether there is an objective pattern of matching error rate change caused by segment-level evidence storage time offset in the multi-platform distribution authorization scenario of the target government video archive, thereby providing a basis for subsequent regulation of the target government video archive.

[0065] Specifically, by analyzing the historical evidence samples obtained in step S1, the fragment-level evidence storage time offset corresponding to each historical evidence sample is used as the independent variable, and the corresponding fragment correspondence matching error rate is used as the dependent variable. The historical evidence samples are then sorted and mapped to construct the relationship between the fragment-level evidence storage time offset and the fragment correspondence matching error rate. In this embodiment, several historical evidence samples are first sorted from smallest to largest according to their fragment-level evidence storage time offset to obtain an ordered sample sequence. Then, the fragment correspondence matching error rate corresponding to each historical evidence sample in the ordered sample sequence is extracted, and a change curve is constructed based on the fragment-level evidence storage time offset and the corresponding fragment correspondence matching error rate to represent the relationship between the two in a visual or numerical form.

[0066] In the specific implementation process, the establishment of the changing relationship can employ common data analysis techniques in the field, such as scatter plot fitting, trend line fitting, piecewise regression analysis, or sliding window statistical analysis. Specifically, the overall changing trend can be identified by scatter plotting the error rate of the segment-level evidence storage time offset and segment correspondence, and then using a fitting algorithm to generate a trend curve. Furthermore, the changing curve can be analyzed using piecewise regression or inflection point detection methods to determine the locations where significant changes in the changing trend occur, thereby identifying the threshold inflection point. In some embodiments, the magnitude of the matching error rate change can be quantified by setting a change rate threshold, gradient change detection, or local fluctuation analysis to improve the accuracy and stability of threshold inflection point identification.

[0067] Based on the aforementioned relationship, the threshold inflection point corresponding to the fragment-level evidence storage time offset can be further determined. This threshold inflection point can be understood as the critical point where the fragment-level evidence storage time offset changes from "the range that can be compensated by the system itself" to "the range that exceeds the system's compensation capability." Below this threshold inflection point, the system can effectively absorb the impact of the time offset through existing time alignment, index correction, or matching fault tolerance mechanisms, keeping the fragment correspondence matching error rate stable or experiencing only minor fluctuations. Above this threshold inflection point, as the fragment-level evidence storage time offset further increases, the system's original compensation capability gradually becomes ineffective, leading to an upward trend in the fragment correspondence matching error rate.

[0068] The significance of step S3 lies in transforming the fragment-level evidence storage time offset, which was originally considered to be within the normal fluctuation range, into a quantifiable and verifiable control basis through historical data analysis. In other words, through the analysis and verification of historical evidence samples, this invention can confirm that in specific multi-platform distribution and authorization scenarios, there is indeed a non-linear correlation between the fragment-level evidence storage time offset and the segment correspondence matching error rate, and this correlation has a clear threshold turning point characteristic. Given the confirmation of this change pattern, the threshold turning point can be used as the basis for subsequent adjustment of the fragment-level redundant evidence storage strength of the target government video archives. This allows the system to perform pre-judgment and pre-adjustment based on this threshold before actual evidence collection, auditing, or liability determination evidence collection occurs when facing new target government video archives, thus preventing an adverse increase in the segment correspondence matching error rate in subsequent stages.

[0069] Furthermore, the blockchain-based copyright evidence management method also includes the following steps:

[0070] Step S4: Compare the current fragment-level evidence storage time offset with the threshold inflection point. When it exceeds the threshold inflection point, generate a corresponding correction factor based on the degree of excess, and correct the fragment-level redundant evidence storage strength of the target government video archive based on the correction factor.

[0071] Specifically, Figure 2 The flowchart illustrates the process of correcting the fragment-level redundancy evidence strength of the target government video archive.

[0072] The process involves comparing the current fragment-level evidence storage time offset with a threshold inflection point. When the offset exceeds the threshold, a corresponding correction factor is generated based on the degree of excess. The fragment-level redundant evidence storage strength of the target government video archive is then corrected based on this correction factor. Specifically, this includes the following steps:

[0073] Step S41: Obtain the fragment-level copyright registration time offset generated during the current fragment-level copyright registration process, and compare the fragment-level copyright registration time offset with the threshold inflection point;

[0074] Step S42: When the current fragment-level evidence storage time offset does not exceed the threshold inflection point, maintain the current fragment-level redundant evidence storage strength unchanged;

[0075] Step S43: When the current fragment-level evidence storage time offset exceeds the threshold turning point, a corresponding correction factor is generated according to the degree of exceeding the threshold turning point, and the fragment-level redundant evidence storage strength of the target government video archive is improved based on the correction factor to improve the stability of fragment-level copyright evidence storage data.

[0076] The improved correction includes at least one or more of the following: increasing the multi-node confirmation level of critical segments, increasing the frequency of segment-level metadata synchronization, and increasing the number of redundant backups of segment authorization records.

[0077] When improving the evidence strength of fragment-level redundancy in target government video archives, a preset segmented correction function is used, which includes:

[0078] ;

[0079] in, This refers to the corrected fragment-level redundancy evidence strength. This refers to the initial fragment-level redundancy evidence strength. This refers to the upper limit of the value of fragment-level redundancy evidence strength. This refers to the current fragment-level evidence storage time offset. This refers to the threshold inflection point. This refers to exceeding the limit. This refers to the preset control correction strength coefficient, and it satisfies... Greater than 0, This refers to the correction factor.

[0080] In this embodiment of the invention, step S4 is an implementation step for closed-loop control of the fragment-level copyright evidence preservation process of the current target government video archive based on the threshold inflection point determined in step S3. Its core is that even if it is not yet certain whether the target government video archive will be subject to evidence collection, auditing or liability determination evidence collection in the future, the fragment-level evidence preservation time offset is judged in real time and an improvement correction is made when it exceeds the threshold inflection point, thereby realizing a pre-emptive prevention mechanism. This achieves higher stability and accuracy in the subsequent evidence collection, auditing or liability determination comparison stage with a small additional cost.

[0081] Specifically, in step S41, the storage time information of each government video archive segment at different storage nodes or distribution platforms is collected in real time during the segment-level copyright storage process, and the current segment-level storage time offset is calculated according to the method described in step S2; then, the segment-level storage time offset is compared with the threshold inflection point determined in step S3. This process can be implemented by setting a time acquisition module and an offset calculation module in the storage system. The relevant technical means include timestamp recording, node log reading, and simple difference calculation, all of which are conventional technologies that can be directly implemented in this field.

[0082] In step S42, as long as the current fragment-level evidence storage time offset does not exceed the threshold inflection point, the current fragment-level redundant evidence storage strength remains unchanged. The technical implication is that when the time offset is within the system's tolerable range, the system's existing time alignment mechanism, index compensation mechanism, and matching fault tolerance mechanism can effectively absorb the offset without introducing additional redundant resources, thereby avoiding unnecessary resource consumption.

[0083] In step S43, when the current fragment-level evidence storage time offset exceeds the threshold inflection point, a corresponding correction factor is generated based on the degree of exceeding the threshold inflection point, and the fragment-level redundant evidence storage strength of the target government video archive is improved based on the correction factor. Specifically, the correction factor can be calculated by the control module according to the ratio between the "difference between the current offset and the threshold inflection point" and the threshold inflection point, and parameters such as the multi-node confirmation level, fragment-level metadata synchronization frequency, and authorized record redundant backup count can be dynamically adjusted accordingly. This process can be implemented through parameter scheduling algorithms, strategy engines, or rule configuration modules, and has a clear engineering implementation path.

[0084] The use of "generating correction factors based on the degree of exceedance" in step S43 is of great significance. Compared to the simple approach of "uniformly increasing redundancy intensity when exceeding a threshold," this invention introduces the degree of exceedance, allowing the correction intensity to match the level of risk. When the fragment-level evidence storage time offset only slightly exceeds the threshold inflection point, only a small increase is needed; however, when the offset significantly exceeds the threshold inflection point, a higher level of redundancy configuration is implemented, thereby achieving fine-grained control. This approach avoids the waste of resources caused by excessive redundancy while providing sufficient protection under high-risk conditions, achieving a balance between cost and effectiveness.

[0085] The segmented correction method used in this invention is intuitive and effective: no adjustment is made within the threshold range; after exceeding the threshold, the fragment-level redundant evidence storage strength is gradually increased according to the excess ratio, and an upper limit is set to prevent infinite growth. This method can clearly reflect the relationship between the fragment-level evidence storage time offset and the redundancy strategy, facilitating system implementation and parameter tuning. It should be noted that, in addition to the above-mentioned calculation method based on proportional relationships, in other embodiments, segmented linear growth, exponential growth, or discrete mapping methods based on empirical lookup tables can also be used to determine the correction factor. For example, the offset can be divided into multiple levels according to a preset interval, and a corresponding redundant evidence storage strength can be configured for each level, thereby achieving control strategies with different levels of precision and complexity.

[0086] The following is a specific example to illustrate the overall implementation process of the present invention. Assume that in a multi-platform distribution authorization scenario, for a segment of a target government video archive, the corresponding storage times on the three distribution platforms are 100 milliseconds, 104 milliseconds, and 109 milliseconds, respectively. Then, the segment-level storage time offset for this segment is 109 minus 100, which is 9 milliseconds. Assuming the threshold inflection point determined in step S3 is 6 milliseconds, the current offset has exceeded the threshold inflection point, and the degree of excess is 9 minus 6 divided by 6, which is 0.5. If the preset correction coefficient is 1, then the correction factor is 0.5. Assuming the current segment-level redundant storage strength is 10, and the upper limit is 20, then the corrected redundant storage strength is 10 multiplied by 1 plus 0.5, which is 15. This does not exceed the upper limit, so 15 is ultimately adopted as the new redundant storage strength. Based on this strength, the number of multi-node confirmations for this fragment can be increased from 2 to 3, the metadata synchronization frequency can be increased from 1 per second to 2 per second, and an additional authorization record backup can be added, thereby enhancing the evidence preservation stability of this fragment.

[0087] Through the above steps, this invention can proactively intervene in potential risks based on the changing patterns summarized from historical evidence samples, before actual evidence collection, auditing, or liability determination of the target government video archives occurs. This prevents the segment correspondence matching error rate from adversely increasing in subsequent stages. Compared with existing technologies, this invention not only identifies the threshold transition relationship between segment-level evidence storage time offset and matching error rate in multi-platform distribution and authorization scenarios, but also proposes a solution for dynamic adjustment based on this threshold, thus effectively addressing the aforementioned core research issues.

[0088] The overall beneficial effects of this invention are as follows: by introducing the intermediate variable of fragment-level evidence storage time offset and combining it with historical evidence samples to establish the relationship between the error rate of matching the corresponding fragments, a shift from "post-event correction" to "pre-event prevention" is achieved; by setting threshold inflection points and correction factors based on the degree of excess, fine-grained control over the strength of fragment-level redundant evidence storage is achieved; while ensuring the accuracy of subsequent evidence collection, auditing, or liability determination, the system resource consumption is effectively controlled, resulting in a "low-cost, high-impact" technical effect.

[0089] Furthermore, this invention is applicable to various application scenarios, including government video archive platforms, content distribution networks, and digital rights management systems, and is particularly suitable for content ecosystems with multi-platform distribution and authorization requirements. Given the current widespread dissemination of government video archive content and the increasing demand for evidence collection, auditing, or liability determination, this invention has promising application prospects and significant promotional value.

[0090] Furthermore, Figure 3 An application architecture diagram of the system provided in an embodiment of the present invention is shown.

[0091] In another preferred embodiment of the present invention, a blockchain-based copyright evidence management system includes:

[0092] The sample screening module 100 is used to retrieve a preset copyright certificate database and select several historical certificate samples that correspond to the current copyright certificate status when the current segment-level copyright certificate of the identified target government video archive is in a multi-platform distribution and authorization scenario.

[0093] Furthermore, the blockchain-based copyright evidence management system also includes:

[0094] The parameter calculation module 200 is used to determine the fragment-level evidence storage time offset generated by each historical evidence sample during the multi-node writing and cross-platform synchronization of fragment-level evidence storage data, as well as the fragment correspondence matching error rate in subsequent fragment evidence collection, auditing, or liability determination comparison stages.

[0095] Furthermore, the blockchain-based copyright evidence management system also includes:

[0096] The inflection point determination module 300 is used to determine the threshold inflection point corresponding to the fragment-level evidence storage time offset and the segment correspondence matching error rate based on the changing relationship between the fragment-level evidence storage time offset and the fragment correspondence matching error rate of each historical evidence storage sample. Below the threshold inflection point, the segment correspondence matching error rate remains stable, while above the threshold inflection point, the segment correspondence matching error rate shows an upward trend.

[0097] Furthermore, the blockchain-based copyright evidence management system also includes:

[0098] The correction control module 400 is used to compare the current fragment-level evidence storage time offset with the threshold inflection point. When it exceeds the threshold inflection point, a corresponding correction factor is generated according to the degree of excess, and the fragment-level redundant evidence storage strength of the target government video archive is corrected based on the correction factor.

[0099] It should be understood that although the steps in the flowcharts of the various embodiments of the present invention are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the various embodiments may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0100] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0101] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0102] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

[0103] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A copyright evidence management method based on blockchain, characterized in that, The method includes: S1. When the current segment-level copyright certificate of the target government video archive is under the multi-platform distribution and authorization scenario, retrieve the preset copyright certificate database and select several historical certificate samples corresponding to the current copyright certificate status. S2. Determine the fragment-level evidence storage time offset generated during the multi-node writing and cross-platform synchronization of fragment-level evidence storage data for each historical evidence storage sample, as well as the fragment correspondence matching error rate in subsequent fragment evidence collection, auditing, or liability determination comparison stages. S3. Based on the changing relationship between the fragment-level evidence storage time offset and the fragment correspondence matching error rate of each historical evidence storage sample, determine the threshold inflection point corresponding to the fragment-level evidence storage time offset according to the changing relationship; below the threshold inflection point, the fragment correspondence matching error rate remains stable, and above the threshold inflection point, the fragment correspondence matching error rate shows an upward trend. S4. Compare the current fragment-level evidence storage time offset with the threshold inflection point. When it exceeds the threshold inflection point, generate a corresponding correction factor based on the degree of excess, and correct the fragment-level redundant evidence storage strength of the target government video archive based on the correction factor.

2. The copyright evidence management method based on blockchain according to claim 1, characterized in that, The fragment-level copyright registration data generated during the fragment-level copyright registration process includes at least the government video archive fragment identifier, fragment metadata, distribution platform identifier, and authorization record.

3. The copyright evidence management method based on blockchain according to claim 2, characterized in that, The phrase "corresponding to the current copyright evidence preservation status" specifically refers to the fact that historical evidence preservation samples and current target government video archives are the same as or within a preset similarity range in at least one of the following: specific evidence preservation data type, number of distribution platforms, number of segments, node load status, and authorization synchronization frequency.

4. The copyright evidence management method based on blockchain according to claim 2, characterized in that, The specific calculation process of the segment-level evidence storage time offset includes: extracting the evidence storage time information of the same government video archive segment at different evidence storage nodes or distribution platforms, determining the maximum and minimum time values ​​in the evidence storage time information, and using the difference between the maximum and minimum time values ​​as the segment-level evidence storage time offset.

5. The copyright evidence management method based on blockchain according to claim 1, characterized in that, The historical evidence samples are limited to those that have undergone subsequent fragment evidence collection, auditing, or liability determination comparison processes, and that generate fragment correspondence matching results during the comparison process.

6. The copyright evidence management method based on blockchain according to claim 5, characterized in that, The specific calculation process for the segment correspondence matching error rate includes: performing segment-level matching between historical government video archive segments of historical evidence samples and corresponding evidence collection, auditing, or liability determination comparison video segments; counting the number of historical government video archive segments that failed to match; and determining the segment correspondence matching error rate as the ratio of the number of historical government video archive segments that failed to match to the total number of historical government video archive segments that participated in the matching.

7. The copyright evidence management method based on blockchain according to claim 1, characterized in that, The process of establishing the change relationship includes: Several historical evidence samples are sorted in ascending order of fragment-level evidence time offset to obtain an ordered sample sequence; Extract the segment correspondence matching error rate corresponding to each historical evidence sample in the ordered sample sequence, and construct a change curve based on the segment-level evidence storage time offset and the corresponding segment correspondence matching error rate to characterize the change relationship between the two.

8. The copyright evidence management method based on blockchain according to claim 1, characterized in that, Step S4 specifically includes: Obtain the fragment-level copyright registration time offset generated during the current fragment-level copyright registration process, and compare the fragment-level copyright registration time offset with the threshold inflection point; When the current fragment-level evidence storage time offset does not exceed the threshold inflection point, the current fragment-level redundant evidence storage strength remains unchanged; When the current fragment-level evidence storage time offset exceeds the threshold inflection point, a corresponding correction factor is generated according to the degree of exceeding the threshold inflection point, and the fragment-level redundant evidence storage strength of the target government video archive is improved based on the correction factor to improve the stability of fragment-level copyright evidence storage data. The improved correction includes at least one or more of the following: increasing the multi-node confirmation level of critical segments, increasing the frequency of segment-level metadata synchronization, and increasing the number of redundant backups of segment authorization records.

9. The copyright evidence management method based on blockchain according to claim 8, characterized in that, When improving the evidence strength of fragment-level redundancy in target government video archives, a preset segmented correction function is used, which includes: ； in, This refers to the corrected fragment-level redundancy evidence strength. This refers to the initial fragment-level redundancy evidence strength. This refers to the upper limit of the value of fragment-level redundancy evidence strength. This refers to the current fragment-level evidence storage time offset. This refers to the threshold inflection point. This refers to exceeding the limit. This refers to the preset control correction strength coefficient, and it satisfies... Greater than 0, This refers to the correction factor.

10. A blockchain-based copyright evidence storage and management system, characterized in that, The system includes: The sample screening module is used to retrieve a preset copyright certificate database when the current segment-level copyright certificate of the identified target government video archive is in a multi-platform distribution and authorization scenario, and to screen out a number of historical certificate samples that correspond to the current copyright certificate status. The parameter calculation module is used to determine the fragment-level evidence storage time offset generated by each historical evidence sample during the multi-node writing and cross-platform synchronization of fragment-level evidence storage data, as well as the fragment correspondence matching error rate in the subsequent fragment evidence collection, auditing or liability determination comparison stages. The inflection point determination module is used to determine the threshold inflection point corresponding to the fragment-level evidence storage time offset and the fragment correspondence matching error rate based on the changing relationship between the fragment-level evidence storage time offset and the fragment correspondence matching error rate of each historical evidence storage sample. Below the threshold inflection point, the fragment correspondence matching error rate remains stable, while above the threshold inflection point, the fragment correspondence matching error rate shows an upward trend. The correction control module is used to compare the current fragment-level evidence storage time offset with the threshold inflection point. When it exceeds the threshold inflection point, a corresponding correction factor is generated according to the degree of excess, and the fragment-level redundant evidence storage strength of the target government video archive is corrected based on the correction factor.

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