Intelligent and safe distribution method and system for digital media

Abstract

The invention discloses an intelligent and safe distribution method and system for digital media, and relates to the technical field of digital media data analysis, which comprises the following steps of: counting a digital media content category set of each user terminal on a use record of digital media service, analyzing the category and use condition of the digital media content involved by each user, and sending the digital media content to the user terminal; the demand index of the network digital media of the user terminal is better defined, and the user groups are divided by considering the similar situation of the digital media demands between the users. Performing security risk assessment on each user group to obtain a security risk level, formulating an encryption security policy, analyzing a distribution personalized demand of each user group, formulating a distribution policy, and formulating different encryption security policies and distribution policies according to demand conditions of different user groups. The accuracy and the adaptability of the security condition and the adaptation condition of intelligent distribution of digital media of different users are improved, and the digital media service experience requirements of different user groups are met to the maximum extent at the same time.

Description

Technical Field

[0001] The present invention relates to the technical field of digital media data analysis, and particularly to an intelligent and secure distribution method and system for digital media. Background Art

[0002] In the digital age, the content of digital media has grown rapidly, and users' demand for high-quality and high-speed content access has increased. Traditional content delivery networks (CDNs) are facing challenges. Multimedia content covers complex data types such as audio and video, and has higher requirements for transmission speed and latency. The growth of global network traffic has also increased the burden on CDNs. At the same time, the distribution of digital media content faces many security challenges, such as content tampering, privacy theft, illegal dissemination, etc. In this context, the intelligent multimedia content delivery network (IMCDN) has emerged. It integrates artificial intelligence, big data analysis, and network optimization technologies, and provides more intelligent and efficient distribution for multimedia content through means such as content recognition and analysis, and real-time optimization. IMCDN can also strengthen content security protection, including technologies such as content encryption and anti-leeching, meet the needs of modern network transmission, and provide users with a better content access experience.

[0003] In the prior art, the similarity of users' digital media content needs is not considered during the distribution process to divide user groups, resulting in poor accuracy and adaptability of the security and adaptation of the intelligent distribution of digital media for different users, and unable to meet the digital media service experience needs of different user groups at the same time.

[0004] Therefore, how to improve the accuracy and adaptability of the security and adaptation of the intelligent distribution of users' digital media is a technical problem to be solved at present. Summary of the Invention

[0005] The purpose of the present invention is to solve the problem in the prior art that due to the lack of consideration of the digital media needs of user groups, the accuracy and adaptability of the security and adaptation of the intelligent distribution of digital media for different users are poor, and an intelligent and secure distribution method for digital media is proposed. The method includes: Classify and define the characteristics of the digital media content involved on the platform, collect the usage records of the digital media services of the user terminals on the platform, and count the set of digital media content categories of each user terminal in the usage records of the digital media services; Define the demand index of the network digital media of the user terminal according to the set of digital media content categories of each user terminal, and divide the user terminals into groups based on the demand index of the network digital media; Conduct a security risk assessment on each user group to obtain a security risk level, formulate an encryption security policy, analyze the personalized distribution needs of each user group, and formulate a distribution policy. Apply the encryption security policy and the distribution policy to the encryption protection link after content production and the IoT distribution link in the transmission network respectively.

[0006] In some embodiments of the present application, classify and define the characteristics of digital media content involved in the platform, including, Conduct basic media classification on digital media content according to the business conditions involved in the platform; The characteristics of digital media content include four dimensions: timeliness, transmission sensitivity, cache applicability, and quality elasticity; Search for the description parameters involved in each dimension among the four dimensions of timeliness, transmission sensitivity, cache applicability, and quality elasticity; Integrate all the description parameters involved in the same dimension, define the timeliness index, transmission sensitivity index, cache applicability index, and quality elasticity index, so as to quantify the characteristics of the four dimensions of timeliness, transmission sensitivity, cache applicability, and quality elasticity respectively.

[0007] In some embodiments of the present application, count the digital media content category set of each user terminal based on the usage records of digital media services, including, Count the digital media content categories under each user terminal based on the usage records of digital media services, and intercept the corresponding record segments of the usage records of digital media services according to the digital media content categories; For multiple record segments of the same digital media content category, extract the first-class features, second-class features, and the fluctuation parameters of each feature of each record segment, determine the confidence level of each record segment by integrating the fluctuation parameters of the first-class features and the second-class features, and assign each standard weight according to the confidence level of each record segment, so as to perform weighted aggregation of the first-class features and the second-class features of multiple record segments, obtain the standard values of the first-class features and the second-class features, and mark the standard values, timeliness index, transmission sensitivity index, cache applicability index, and quality elasticity index on each digital media content category of each user terminal.

[0008] In some embodiments of the present application, determine the confidence level of each record segment by integrating the fluctuation parameters of the first-class features and the second-class features, including, Conduct a reliability evaluation on the first-class features to obtain a score, and calculate the confidence level of each record segment based on the score of the first-class features, the fluctuation parameters of the first-class features, and the fluctuation parameters of the second-class features.

[0009] In some embodiments of the present application, define the demand index of the network digital media of the user terminal according to the digital media content category set of each user terminal, including, Integrate the standard values, timeliness indicators, transmission sensitivity indicators, cache applicability indicators, and quality elasticity indicators of a type of feature and a second type of feature for all digital media content categories of the same user terminal respectively, to obtain the range intervals of the standard values, timeliness indicators, transmission sensitivity indicators, cache applicability indicators, and quality elasticity indicators of the type of feature and the second type of feature respectively; Determine the demand index of the standard value, timeliness indicator, transmission sensitivity indicator, cache applicability indicator, and quality elasticity indicator of the type of feature and the second type of feature respectively according to the range intervals of the standard value, timeliness indicator, transmission sensitivity indicator, cache applicability indicator, and quality elasticity indicator of the type of feature and the second type of feature, so as to define the demand index of the network digital media of each user terminal.

[0010] In some embodiments of the present application, perform a security risk assessment on each user group to obtain a security risk level, and formulate an encryption security policy, including, Perform a security risk assessment on the behaviors and digital media content of the user group respectively, combine the behaviors and digital media content of the user group to obtain a security risk level, and map the encryption security policy of each user group through the security risk level.

[0011] In some embodiments of the present application, analyze the distribution personalization requirements of each user group, including, Construct the digital media content preference of each user group, perform personalized digital media content recommendation according to the digital media content preference of each user group, and classify the digital media content into old digital media content and new digital media content; Combine the old digital media content and the new digital media content to determine the distribution personalization requirements of the user group.

[0012] In some embodiments of the present application, formulate a distribution strategy, including, Determine the range of the distribution strategy level according to the distribution personalization requirements of the user group. Within the range of the distribution strategy level, determine the specific distribution strategy level through the specific distribution personalization requirements of each user under the user group.

[0013] Correspondingly, the present application also provides an intelligent security distribution system for digital media, including, The first module is used to classify and define the characteristics of the digital media content involved in the platform, collect the usage records of the digital media services of the user terminals on the platform, and count the digital media content category sets of each user terminal on the usage records of the digital media services; The second module is used to define the demand index of the network digital media of the user terminal according to the digital media content category set of each user terminal, and divide the user terminals into groups by virtue of the demand index of the network digital media; The third module is used to conduct security risk assessments for each user group, obtain security risk levels, formulate encryption security policies, analyze the distribution personalization requirements of each user group, and formulate distribution policies; The fourth module is used to apply the encryption security policy and the distribution policy to the encryption protection link after content production and the IoT distribution link in the transmission network respectively.

[0014] The encryption security policy and the distribution policy in the above steps can be assisted in implementation to a certain extent through media. The media (such as intelligent physical media like USB flash drives) can store digital media content, encryption keys, identity authentication information, etc. The media mainly undertakes the functions of data storage and transmission, providing a basic data carrier for the application of these policies. It is divided into three links: media production, media transmission, and media use.

[0015] Media production link Content classification and feature definition: In the content production stage, according to the classification and feature definition of digital media content on the platform, targeted encryption processing is carried out on different types of digital media content. For example, more advanced encryption algorithms are used for highly confidential film and television content. These classification information and encryption parameters can be stored in the media and distributed together with the content.

[0016] Application of encryption security policy: According to the formulated encryption security policy, use the corresponding encryption key to encrypt the digital media content, and securely store the encryption key in the media (such as the encrypted storage area of intelligent physical media). At the same time, write the encryption algorithm and related security parameters into the media for decryption operations in the subsequent media use link. The encryption policy includes content encryption, content signature, identity key writing, etc. Write the encrypted content, content ID, content signature, content signature public key certificate, etc. (collectively referred to as content media) into the intelligent physical media. In this way, the intelligent physical media stores the encrypted and signed digital media content and its related information.

[0017] For example, content encryption (performed according to the encryption security policy): Assign a content ID to high-quality digital media content, encrypt the content using the content key according to the ChinaDRM technology, calculate the content Hash value for the encrypted content, and store the content key in the ChinaDRM service. This step ensures the security of digital media content during storage and transmission. Through encryption and Hash value calculation, it prevents the content from being tampered with or illegally obtained.

[0018] Content signature: Use the content signature private key to sign the content ID, content Hash value, and other data related to the content that needs to be signed to obtain the content signature. The role of signature is to verify the integrity of the content and the legality of the source, ensuring that the receiving party can confirm that the content has not been tampered with and comes from a legitimate sender.

[0019] Writing the physical medium identity key: Write the physical medium identity private key and public key certificate into the intelligent physical medium, which can provide an interface for signing data using the physical medium identity private key and an interface for obtaining the physical medium identity certificate. This step endows the intelligent physical medium with a unique identity identifier, facilitating subsequent identity authentication and authorization operations.

[0020] Medium transmission link Distribution strategy application: The distribution strategy formulated according to the personalized distribution needs of different user groups can be reflected during the medium transmission process. For example, for some urgent or high-priority digital media content, the medium storing this content can be delivered to users through a faster and more reliable logistics channel. At the same time, during the medium transmission process, encryption security policies can be combined to ensure the physical security and data security of the medium during transportation, preventing the loss of the medium or data leakage.

[0021] Medium usage link Demand index and group division application: When the user terminal uses the medium, the content category information stored in the medium can be combined with the usage records of the user terminal to further verify and update the digital media content category set of each user terminal. According to the group to which the user terminal belongs, the medium can provide corresponding digital media services. For example, for user groups with a high demand index, the medium can provide higher-quality digital media content or more value-added services.

[0022] Security risk assessment and strategy application: During the medium usage process, relying on the identity authentication information and encryption keys stored in the medium, combined with the security risk assessment results of the user terminal by the background server, corresponding encryption security policies are implemented. For example, for user groups with a higher security risk, more strict identity verification and key verification are required when decrypting the digital media content in the medium. At the same time, according to the distribution strategy, the medium can control the usage permissions and methods of digital media content, such as restricting the number of playbacks, playback time, etc.

[0023] The present invention has the following beneficial effects: 1. Classify and define the characteristics of the digital media content involved in the platform, thereby quantifying the characteristics of each type of basic digital media content, providing a reliable basis for the subsequent digital media needs of users and the division of user groups. Statistically analyze the digital media content category set of each user terminal based on the usage records of digital media services, analyze the categories and usage situations of the digital media content involved by each user, to better define the demand index of the network digital media of the user terminal, and consider the similarity of digital media needs among users to divide user groups, so as to formulate content security encryption policies and distribution strategies during the subsequent distribution for better users.

[0024] 2. Conduct a security risk assessment for each user group to obtain the security risk level, formulate an encryption security policy, analyze the personalized distribution requirements of each user group, formulate a distribution policy, and formulate different encryption security policies and distribution policies according to the requirements of different user groups, so as to improve the accuracy and adaptability of the security and adaptation of the intelligent distribution of digital media for different users, and maximize the satisfaction of the digital media service experience needs of different user groups at the same time. Brief Description of the Drawings

[0025] Figure 1 It is a schematic flowchart of an intelligent security distribution method for digital media proposed by the present invention; Figure 2 It is a schematic structural diagram of an intelligent security distribution system for digital media proposed by the present invention. Detailed Embodiments

[0026] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments.

[0027] Refer to Figure 1 , an intelligent security distribution method for digital media, including the following steps: Step S101, classify and define the characteristics of the digital media content involved on the platform, collect the usage records of the digital media services of the user terminals on the platform, and count the digital media content category sets of each user terminal based on the usage records of the digital media services.

[0028] In this embodiment, the digital media content is classified, and according to the platform business scenario, the digital media content is divided into the following basic categories: Video category: Long videos (UHD movies, TV series), short videos (Douyin, Kuaishou), live broadcasts (sports events, concerts).

[0029] Audio category: Music, podcasts, audiobooks.

[0030] Graphic and text category: News, blogs, comics.

[0031] Interactive category: Games, VR / AR content.

[0032] The above several categories of digital media content can be further divided according to specific application scenarios, and the content characteristics are quantified from four dimensions: Timeliness: The requirement of the content for real-time (such as live broadcast > news > movie).

[0033] Transmission sensitivity: The risk of the content being tampered with during transmission (such as financial data > ordinary video).

[0034] Cache applicability: Whether the content is suitable for caching (e.g., popular movies are suitable for caching, while real-time news is not).

[0035] Quality flexibility: The tolerance of the content to picture / sound quality (e.g., short videos can accept low resolution, while movies require high resolution).

[0036] Statistically classify the digital media content categories of user terminals (e.g., user A has accessed movies, music, and news).

[0037] Collect the usage records of digital media services on user terminals on the platform, and intercept the record segments of each type of content (e.g., the record segment of user A accessing the movie "xxx" is "2023-10-01 20:00-22:00").

[0038] In some embodiments of the present application, classify and define the characteristics of digital media content involved on the platform, including Conduct basic media classification of digital media content according to the business situation involved in the platform; The characteristics of digital media content include four dimensions: timeliness, transmission sensitivity, cache applicability, and quality flexibility; Search for the description parameters involved in each of the four dimensions of timeliness, transmission sensitivity, cache applicability, and quality flexibility; Integrate all the description parameters involved in the same dimension, and define the timeliness index, transmission sensitivity index, cache applicability index, and quality flexibility index, so as to quantify the characteristics of the four dimensions of timeliness, transmission sensitivity, cache applicability, and quality flexibility respectively.

[0039] In this embodiment, search for the description parameters involved in each of the four dimensions of timeliness, transmission sensitivity, cache applicability, and quality flexibility, specifically: The timeliness dimension reflects the degree of time sensitivity of digital media content, and the description parameters mainly include: Content update frequency Describe the time interval for content update. For example, news may be refreshed every 5-10 minutes, while movies are usually released once and have a low update frequency.

[0040] User access interval Reflect the access frequency of users to the content. For example, popular movies may be accessed weekly, while real-time news may be accessed multiple times a day.

[0041] Expiration time Describe the time from the release of the content to its loss of value. For example, weather forecasts are usually valid within 24 hours after release.

[0042] Real-time requirement Users' expectations for the real-time nature of content, such as live broadcasts requiring millisecond-level latency, while on-demand content has lower requirements for real-time performance.

[0043] The transmission sensitivity dimension reflects the requirements for speed and stability during the transmission of digital media content. The main description parameters include: Transmission bandwidth requirement Describes the minimum bandwidth required for content transmission. For example, high-definition videos may require more than 10 Mbps, while text news only needs a few Kbps.

[0044] Transmission latency tolerance The degree of tolerance of users to transmission latency. For example, online games require low latency (<50 ms), while email transmission is not sensitive to latency.

[0045] Packet loss rate tolerance The degree of tolerance of users to packet loss. For example, video calls allow a small amount of packet loss, while financial transactions have zero tolerance for packet loss.

[0046] Transmission security requirements Describes the requirements for encryption and authentication during content transmission. For example, bank transfers require high-strength encryption, while public videos can accept lower security.

[0047] Transmission protocol requirements Describes the type of protocol required for content transmission. For example, real-time videos require the UDP protocol, while file downloads can use the TCP protocol.

[0048] The cache applicability dimension reflects whether digital media content is suitable for caching to improve access efficiency. The main description parameters include: Content access popularity Describes the frequency of content access. For example, popular movies are accessed frequently and are suitable for caching; while unpopular content has a low access frequency and low caching value.

[0049] Content size Describes the storage space requirements of content. For example, high-definition movies may reach 10 GB, with high caching costs; while short videos may only be 100 MB and are suitable for caching.

[0050] Content update frequency Content with a high update frequency has low caching value, such as real-time news; while content with a slow update frequency (such as movies) has high caching value.

[0051] User access pattern Describes the regularity of users' access to content. For example, content accessed at fixed times (such as daily news) is suitable for pre-caching.

[0052] Cache hit rate Measure the probability that cached content will be accessed again. Content with a high hit rate is suitable for caching.

[0053] The quality elasticity dimension reflects the tolerance of digital media content to quality changes. The main description parameters include: Resolution tolerance Describe the user's acceptance of content resolution changes. For example, short video users can accept a lower resolution (such as 480P), while movie users expect high definition (such as 1080P).

[0054] Frame rate tolerance The user's acceptance of video frame rate changes. For example, game live broadcasts require a high frame rate (such as 60fps), while surveillance videos can accept a low frame rate (such as 15fps).

[0055] Bitrate tolerance The user's acceptance of content bitrate changes. For example, music streaming can automatically reduce the bitrate under low bandwidth, while professional audio production requires a lossless bitrate.

[0056] Picture / sound quality loss tolerance Describe the user's acceptance of content quality loss. For example, real-time video calls can accept slight picture quality loss, while movie playback requires high quality.

[0057] Network bandwidth adaptability Describe the adaptive ability of content under different bandwidths. For example, adaptive bitrate technology (ABR) can dynamically adjust the quality according to the bandwidth.

[0058] The description parameters of the above four dimensions are only partial listings, not exhaustive. By integrating the description parameters under each dimension, the timeliness index, transmission sensitivity index, cache applicability index, and quality elasticity index can be defined by weighted summation or weighted averaging after normalization or standardization.

[0059] In some embodiments of the present application, on the usage records of digital media services, count the set of digital media content categories of each user terminal, including: On the usage records of digital media services, count the digital media content categories under each user terminal, and intercept the corresponding record segments of the usage records of digital media services according to the digital media content categories. For multiple record segments of the same digital media content category, extract a type of feature, a second type of feature for each record segment, and the fluctuation parameters of each feature. Combine the fluctuation parameters of the first type of feature and the second type of feature to determine the confidence level of each record segment. Allocate each standard weight according to the confidence level of each record segment, so as to perform weighted aggregation of the first type of feature and the second type of feature of multiple record segments, obtain the standard values of the first type of feature and the second type of feature, and mark the standard value, timeliness index, transmission sensitivity index, cache applicability index, and quality elasticity index on each digital media content category of each user terminal.

[0060] In this embodiment, the usage records of the digital media service are intercepted corresponding to record segments according to the digital media content category, and partial record segments on the usage records are intercepted in units of the digital media content category.

[0061] The first type of feature: the attributes of the content itself (such as duration, number of times, resolution, etc.). The second type of feature: the attributes of user behavior (such as playback completion rate, experience feedback evaluation, skip rate, etc.). The fluctuation parameters of the two types of features can be parameters that can describe fluctuations, such as change rate, frequency, standard deviation, etc. Combine the score of the first type of feature, the fluctuation parameters of the first type of feature, and the fluctuation parameters of the second type of feature (because the second type of feature is the relevant evaluation and feedback of the user experience, only the stability needs to be considered) to determine the confidence level. The possible situations of multiple record segments of the same digital media content category may be relatively complex (the data volume of the first type of feature and the second type of feature is large) and vary greatly. It is necessary to determine the confidence level of each record segment, and calculate the standard values of the first type of feature and the second type of feature based on this. The standard value is a relatively common and representative value or interval of the feature corresponding to the media content. Mark the standard value, timeliness index, transmission sensitivity index, cache applicability index, and quality elasticity index on the content category of the user terminal. The digital media content category set of the user terminal includes the digital media content category and these parameters such as the standard value, timeliness index, transmission sensitivity index, cache applicability index, and quality elasticity index under each category.

[0062] In some embodiments of the present application, combining the fluctuation parameters of the first type of feature and the second type of feature to determine the confidence level of each record segment includes Conduct a reliability evaluation on the first type of feature to obtain a score, and calculate the confidence level of each record segment based on the score of the first type of feature, the fluctuation parameters of the first type of feature, and the fluctuation parameters of the second type of feature.

[0063] In this embodiment, the first type of feature usually refers to the attributes directly related to the content itself (such as resolution, bit rate, duration, etc.), and its reliability evaluation needs to be quantitatively analyzed from multiple dimensions. It can be analyzed from the following dimensions: Stability: The degree of change of the feature value in time or space.

[0064] Consistency: The degree of conformity of the eigenvalue with the expected or standard value.

[0065] Predictability: Whether the eigenvalue can be predicted through historical data or models.

[0066] Integrity: Whether the eigenvalue is complete (e.g., without missing or outlier values).

[0067] The score of a type of feature: Reflects the reliability of the content attribute.

[0068] The fluctuation parameter of a type of feature: Reflects the degree of change of the content attribute in time or space (e.g., the standard deviation of the resolution).

[0069] The fluctuation parameter of the second type of feature: Reflects the degree of change of the user behavior attribute (e.g., the standard deviation of the play completion rate). Calculate the confidence level of each record segment based on the score of the first type of feature, the fluctuation parameter of the first type of feature, and the fluctuation parameter of the second type of feature. The specific calculation formula is as follows: ; Among them, is the confidence level of the th record segment, is the confidence conversion coefficient of the score of the first type of feature, is the score of the first type of feature of the th record segment, , are the combined weights of the fluctuation parameters of the first type of feature and the second type of feature respectively, , are the fluctuation parameters of the first type of feature and the second type of feature of the th record segment respectively, is the first constant of the th record segment, represents the correction of the score of the first type of feature by the fluctuation conditions of the first type of feature and the second type of feature. The first constant is used to balance the magnitude of the correction function. The above first type of feature and second type of feature can be a single representative feature among multiple features or a combination of multiple features.

[0070] Step S102, define the demand index of the network digital media of the user terminal according to the digital media content category set of each user terminal, and group the user terminals by virtue of the demand index of the network digital media.

[0071] In this embodiment, the demand situation of each user for network digital media is defined according to the digital media content category of the user, the standard value, timeliness index, transmission sensitivity index, cache applicability index, and quality elasticity index on the category. The user groups are divided by the differences in the demand indexes of different users' network digital media.

[0072] In some embodiments of the present application, a demand index of network digital media for a user terminal is defined according to the set of digital media content categories of each user terminal, including Integrate the standard values, timeliness indicators, transmission sensitivity indicators, cache applicability indicators, and quality elasticity indicators of a type of feature and a second type of feature for all digital media content categories of the same user terminal respectively, to obtain the range intervals of the standard values, timeliness indicators, transmission sensitivity indicators, cache applicability indicators, and quality elasticity indicators of the type of feature and the second type of feature respectively; Determine the demand index of the standard value, timeliness indicator, transmission sensitivity indicator, cache applicability indicator, and quality elasticity indicator of the type of feature and the second type of feature respectively according to the range intervals of the standard value, timeliness indicator, transmission sensitivity indicator, cache applicability indicator, and quality elasticity indicator of the type of feature and the second type of feature respectively, so as to define the demand index of network digital media for each user terminal.

[0073] In this embodiment, the range intervals of the standard values, timeliness indicators, transmission sensitivity indicators, cache applicability indicators, and quality elasticity indicators of the type of feature and the second type of feature respectively. This interval represents all possible ranges of these parameters of all digital media content under a single user. The demand index of different parameters can be determined by evaluation or the entropy weight method. The specific calculation formula for defining the demand index of network digital media for each user terminal is as follows: ; Wherein, is the demand index of network digital media for the th user terminal, are the timeliness indicator, transmission sensitivity indicator, cache applicability indicator, and quality elasticity indicator, is the combined weight corresponding to the th indicator among the four, is the th user terminal's th indicator's demand index, , are the contribution coefficients of the type of feature and the second type of feature respectively, , 2 are the quantities of the type of feature and the second type of feature respectively, , are the combined weights of the th type of feature and the th second type of feature respectively, , are the th user terminal's th type of feature and the th second type of feature's respective demand indexes, is the second constant for the th user terminal, indicating the correction of the average value of the timeliness index, transmission sensitivity index, cache applicability index, and quality elasticity index by the combination of the first-class features and the second-class feature requirements. The second constant is used to balance the magnitude of the correction function.

[0074] Step S103: Perform a security risk assessment on each user group to obtain a security risk level, formulate an encryption security policy, analyze the personalized distribution requirements of each user group, and formulate a distribution policy.

[0075] In this embodiment, the goal of the security risk assessment is to identify potential security threats of user groups and classify the security risk levels. These risks are often associated with the digital media needs of users. Therefore, the risk assessment is carried out in units of user groups.

[0076] In some embodiments of the present application, a security risk assessment is performed on each user group to obtain a security risk level, and an encryption security policy is formulated, including performing a security risk assessment on the behaviors and digital media contents of the user group respectively, obtaining a security risk level by combining the behaviors and digital media contents of the user group, and mapping an encryption security policy for each user group through the security risk level.

[0077] In this embodiment, the evaluation dimensions include the following two aspects: User behavior risk: Abnormal access patterns (such as frequent login failures, access at abnormal times).

[0078] Malicious behaviors (such as content tampering, DDoS attacks).

[0079] Content risk: Content sensitivity (such as involving politics, violence).

[0080] Content copyright (such as the risk of pirated content dissemination).

[0081] Security risk level classification Low risk: Normal user behavior and low content sensitivity.

[0082] Medium risk: Occasional abnormal behaviors or medium-sensitivity content.

[0083] High risk: Frequent abnormal behaviors or high-sensitivity content.

[0084] The above three risk levels can be further divided in more detail. For low risk, basic encryption is applicable to low-sensitivity content and normal user behavior. Technical implementation: AES-128 encryption, HTTPS transmission protocol. For medium risk, enhanced encryption is applicable to medium-sensitivity content or occasional abnormal behavior. Technical implementation: enhanced encryption, applicable to medium-sensitivity content or occasional abnormal behavior. Technical implementation: AES-256 encryption, TLS 1.3 protocol, digital signature verification. For high risk, military-grade or membership-level encryption is applicable to high-sensitivity content or frequent abnormal behavior. Technical implementation: AES-256 + digital watermark, end-to-end encryption (E2EE), zero-knowledge proof, blockchain forensics.

[0085] In some embodiments of the present application, analyze the personalized distribution needs of each user group, including Construct the digital media content preferences of each user group, make personalized digital media content recommendations according to the digital media content preferences of each user group, and classify digital media content into old digital media content and new digital media content; Combine the old digital media content and the new digital media content to determine the personalized distribution needs of the user group.

[0086] In some embodiments of the present application, formulate a distribution strategy, including Determine the range of intervals of the distribution strategy level according to the personalized distribution needs of the user group. Within the range of intervals of the distribution strategy level, determine the specific distribution strategy level through the specific personalized distribution needs of each user in the user group.

[0087] In this embodiment, construct digital media content preferences: Data sources: User historical behavior data (such as click-through rate, play duration, favorite behavior).

[0088] Content metadata (such as category, duration, resolution).

[0089] Analysis methods: Collaborative filtering: Recommend content based on user similarity.

[0090] Deep learning model: Use neural networks (such as Wide & Deep model) to predict user preferences.

[0091] Personalized content recommendation Recommendation logic: Old content recommendation: Recommend classic content based on historical play records.

[0092] New content recommendation: Recommend new content based on trends and similar user behavior.

[0093] The distribution strategy levels include basic distribution, standard distribution, priority distribution, premium distribution, etc., and include the following examples: (1)Basic distribution (Level 1) Applicable scenarios: Low-sensitivity, low-value content, or scenarios with low user requirements.

[0094] Policy content: Transport protocol: Use HTTP protocol (non-encrypted) or basic HTTPS.

[0095] Storage method: Ordinary cloud storage (such as AWS S3 standard storage).

[0096] Distribution method: Single-source CDN distribution, without redundant backup.

[0097] Caching policy: No caching or basic caching (short TTL).

[0098] Fault tolerance mechanism: None or basic retry mechanism.

[0099] Examples: Free news short videos, low-resolution pictures.

[0100] (2)Standard distribution (Level 2) Applicable scenarios: General user needs, medium-sensitivity content.

[0101] Policy content: Transport protocol: Use standard HTTPS (TLS 1.2+).

[0102] Storage method: Encrypted cloud storage (such as AWS S3-Intelligent Tiering).

[0103] Distribution method: Multi-source CDN distribution, with basic redundant backup.

[0104] Caching policy: Edge caching (moderate TTL).

[0105] Fault tolerance mechanism: Basic retry mechanism (such as 3 retries).

[0106] Examples: Ordinary movies, TV series, music.

[0107] (3)Priority distribution (Level 3) Applicable scenarios: High-demand content, or scenarios where users are sensitive to latency.

[0108] Policy content: Transport protocol: Use HTTP / 2 or QUIC protocol to optimize transmission efficiency.

[0109] Storage method: High-performance storage (such as AWS EBS gp3).

[0110] Distribution method: P2P + CDN hybrid distribution, dynamic load balancing.

[0111] Caching policy: Deep edge caching (longer TTL), preloading popular content.

[0112] Fault tolerance mechanism: Intelligent retry mechanism (such as exponential backoff algorithm).

[0113] Example: Popular live broadcasts, sports events, short videos with high click-through rates.

[0114] (4) Advanced distribution (Level 4) Applicable scenarios: High-value content, or scenarios where users are extremely sensitive to latency.

[0115] Policy content: Transport protocol: Use HTTP / 3 (based on QUIC), support 0-RTT handshake.

[0116] Storage method: Low-latency storage (such as AWS EBS io1 / io2).

[0117] Distribution method: Edge computing + CDN distribution, dynamic path optimization.

[0118] Caching policy: Global caching (TTL dynamically adjusted according to content popularity), multi-level caching.

[0119] Fault tolerance mechanism: Multi-path transmission (such as MP-TCP), fast failover.

[0120] Example: 4K / 8K movies, VR content, real-time financial data.

[0121] Within the distribution policy level range (including multiple distribution policy levels), dynamically adjust the policy level according to the specific needs of each user in the user group. Adjustment rules: If the user has a high real-time click-through rate, upgrade the distribution policy level (such as upgrading from "medium demand" to "high demand").

[0122] If the user's network status is poor, lower the distribution policy level (such as downgrading from "high demand" to "medium demand").

[0123] In step S104, apply the encryption security policy and the distribution policy to the encryption protection link after content production and the IoT distribution link in the transmission network respectively.

[0124] In this embodiment, the distribution process of digital media content can be divided into the following six key steps: Content Production and Encoding The original content (such as videos, audio) is edited and encoded to generate distributable media files.

[0125] Content Encryption Protection The media files are encrypted to prevent the content from being stolen or tampered with during transmission or storage.

[0126] Content Storage and Caching The encrypted content is stored in a centralized or distributed storage system and may be cached to edge nodes.

[0127] Transmission Network Distribution The content is distributed to user terminals through Internet of Things (IoT) devices or traditional networks.

[0128] User Terminal Decryption and Playback The user terminal receives the encrypted content and plays it after decrypting it with a legitimate key.

[0129] User Behavior Feedback Collect user playback behavior data (such as playback duration, click-through rate) for optimizing subsequent distribution strategies.

[0130] The encryption security policy is mainly applied to the content encryption protection link to ensure the security of the content during storage and transmission. The following are the specific applications: (1) Content Encryption Protection Link Encryption Target: Prevent the content from being stolen or tampered with during storage or transmission.

[0131] Encryption Policy Selection: Select the encryption strength according to the content sensitivity and user risk level.

[0132] Low-risk content: AES-128 encryption (such as ordinary movies).

[0133] High-risk content: AES-256 + digital watermark (such as unreleased movies).

[0134] Key Management: Low-risk: Centralized key management (provided by cloud service providers).

[0135] High-risk: Distributed key management (such as HSM hardware security modules) or zero-knowledge proof.

[0136] (2) User Terminal Decryption and Playback Link Decryption Target: Ensure that only legitimate users can decrypt the content.

[0137] Decryption Policy: Low risk: The user terminal directly decrypts the AES-128 content.

[0138] High risk: The user terminal needs to decrypt the AES-256 content after biometric verification (such as fingerprint).

[0139] The distribution strategy is mainly applied to the transmission network distribution link to ensure the efficient and secure transmission of content to the user terminal. The following are the specific applications: (1) Transmission network distribution link Distribution target: Optimize the content transmission efficiency, reduce latency, and improve the user experience.

[0140] Distribution strategy selection: Select the distribution strategy level according to the content requirements and the user's network environment.

[0141] Low-demand content: Basic distribution (such as HTTP protocol, single-source CDN).

[0142] High-demand content: Advanced distribution (such as HTTP / 3 + edge computing).

[0143] Distribution method: Basic distribution: Single-source CDN distribution, without redundant backup.

[0144] Advanced distribution: P2P + CDN hybrid distribution, dynamic load balancing.

[0145] Example: News short video (low demand): Basic distribution, transmitted through a single-source CDN.

[0146] 4K movie (high demand): Advanced distribution, real-time distribution through edge computing nodes.

[0147] (2) Content storage and caching link Caching target: Reduce transmission latency and improve playback smoothness.

[0148] Caching strategy: Low-demand content: No caching or basic caching (short TTL).

[0149] High-demand content: Deep edge caching (long TTL), preload popular content.

[0150] Example: Ordinary TV series (low demand): Basic caching, TTL is 1 day.

[0151] Popular live broadcast (high demand): Deep edge caching, TTL is 7 days, and preload.

[0152] Correspondingly, the present application also provides an intelligent security distribution system for digital media, as Figure 2 shown, including A first module, configured to classify and define the characteristics of digital media content involved on the platform, collect the usage records of digital media services of user terminals on the platform, and count the digital media content category sets of each user terminal based on the usage records of digital media services; A second module, configured to define the demand index of the network digital media of the user terminal according to the digital media content category sets of each user terminal, and divide the user terminals into groups based on the demand index of the network digital media; A third module, configured to perform a security risk assessment on each user group to obtain a security risk level, formulate an encryption security policy, analyze the personalized distribution requirements of each user group, and formulate a distribution policy; A fourth module, configured to apply the encryption security policy and the distribution policy to the encryption protection link after content production and the Internet of Things distribution link in the transmission network respectively.

[0153] The present invention has the following beneficial effects: 1. Classify and define the characteristics of digital media content involved on the platform, thereby quantifying the characteristics of each type of basic digital media content, providing a reliable basis for the subsequent digital media demand situation of users and the division of user groups. Count the digital media content category sets of each user terminal based on the usage records of digital media services, analyze the categories and usage situations of digital media content involved by each user, so as to better define the demand index of the network digital media of the user terminal, and consider the similarity of digital media demands among users to divide user groups, thereby formulating content security encryption policies and distribution policies for better users during the subsequent distribution process.

[0154] 2. Perform a security risk assessment on each user group to obtain a security risk level, formulate an encryption security policy, analyze the personalized distribution requirements of each user group, and formulate a distribution policy. Different encryption security policies and distribution policies are formulated according to the demand situations of different user groups, improving the accuracy and adaptability of the security situation and adaptability of the intelligent distribution of digital media for different users, and maximizing the satisfaction of the digital media service experience needs of different user groups at the same time.

[0155] Through the description of the above embodiments, those skilled in the art can clearly understand that the present invention can be implemented through hardware or by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.), including several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in various implementation scenarios of the present invention.

[0156] Those skilled in the art can understand that the drawings are only schematic diagrams of a preferred implementation scenario, and the modules or processes in the drawings are not necessarily essential for implementing the present invention.

[0157] Those skilled in the art can understand that the modules in the system in the implementation scenario can be distributed in the system of the implementation scenario according to the description of the implementation scenario, or can be correspondingly changed and located in one or more systems different from this implementation scenario. The modules in the above implementation scenario can be combined into one module, or can be further split into multiple sub-modules.

[0158] As mentioned above, the above are only the preferred specific implementation manners 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 of the present invention and its inventive concept, makes equivalent substitutions or changes, and should be covered within the protection scope of the present invention.

Claims

1. An intelligent and secure distribution method for digital media, characterized in that, including classifying and defining the characteristics of digital media content involved on the platform, collecting the usage records of digital media services of user terminals on the platform, and counting the set of digital media content categories of each user terminal based on the usage records of digital media services; defining the demand index of network digital media for user terminals according to the set of digital media content categories of each user terminal, and dividing user terminals into groups based on the demand index of network digital media; conducting security risk assessments for each user group to obtain security risk levels, formulating encryption security policies, analyzing the personalized distribution needs of each user group, and formulating distribution policies; applying the encryption security policy and the distribution policy to the encryption protection link after content production and the Internet of Things distribution link in the transmission network respectively.

2. The intelligent and secure distribution method of digital media according to claim 1, characterized in that, classifying and defining the characteristics of digital media content involved on the platform, including conducting basic media classification of digital media content according to the business situation involved in the platform; the characteristics of digital media content include four dimensions: timeliness, transmission sensitivity, cache applicability, and quality elasticity; searching for the description parameters involved in each dimension among the four dimensions of timeliness, transmission sensitivity, cache applicability, and quality elasticity; integrating all the description parameters involved in the same dimension, defining the timeliness index, transmission sensitivity index, cache applicability index, and quality elasticity index, so as to quantify the characteristics of the four dimensions of timeliness, transmission sensitivity, cache applicability, and quality elasticity respectively.

3. The intelligent and secure distribution method of digital media according to claim 1, characterized in that, counting the set of digital media content categories of each user terminal based on the usage records of digital media services, including counting the digital media content categories under each user terminal from the usage records of digital media services, and intercepting the corresponding record segments of the usage records of digital media services according to the digital media content categories; for multiple record segments of the same digital media content category, extracting the first-class features, second-class features, and the fluctuation parameters of each feature of each record segment, determining the confidence level of each record segment by integrating the fluctuation parameters of the first-class features and the second-class features, and assigning each standard weight according to the confidence level of each record segment, so as to perform weighted aggregation of the first-class features and the second-class features of multiple record segments to obtain the standard values of the first-class features and the second-class features, and marking the standard values, timeliness index, transmission sensitivity index, cache applicability index, and quality elasticity index on each digital media content category of each user terminal.

4. The intelligent and secure distribution method of digital media according to claim 3, wherein determining the confidence level of each record segment by integrating the fluctuation parameters of the first-class features and the second-class features, including evaluating the reliability of the first-class features to obtain a score, and calculating the confidence level of each record segment based on the score of the first-class features, the fluctuation parameters of the first-class features, and the fluctuation parameters of the second-class features.

5. The intelligent and secure distribution method of digital media according to claim 3, wherein defining the demand index of network digital media for user terminals according to the set of digital media content categories of each user terminal, including integrating the standard values of the first-class features and the second-class features, the timeliness index, the transmission sensitivity index, the cache applicability index, and the quality elasticity index under all digital media content categories of the same user terminal respectively to obtain the range intervals of the standard values of the first-class features and the second-class features, the timeliness index, the transmission sensitivity index, the cache applicability index, and the quality elasticity index respectively; Determine the demand indices of the first-class features, second-class features, timeliness indicators, transmission sensitivity indicators, cache applicability indicators, and quality elasticity indicators respectively according to their respective range intervals, so as to define the demand index of the network digital media for each user terminal.

6. The intelligent and secure distribution method of digital media according to claim 1, characterized in that Conduct a security risk assessment for each user group to obtain the security risk level, and formulate an encryption security policy, including Conduct a security risk assessment on the behaviors and digital media content of the user group respectively, combine the behaviors and digital media content of the user group to obtain the security risk level, and map out the encryption security policy for each user group through the security risk level.

7. The intelligent and secure distribution method of digital media according to claim 1, characterized in that, Analyze the personalized distribution needs of each user group. including Construct the digital media content preferences of each user group, make personalized digital media content recommendations according to the digital media content preferences of each user group, and classify the digital media content into old digital media content and new digital media content; Combine the old digital media content and the new digital media content to determine the personalized distribution needs of the user group.

8. The intelligent and secure distribution method of digital media according to claim 7, characterized in that Formulate a distribution strategy, including Determine the range of the distribution strategy level according to the personalized distribution needs of the user group. Within the range of the distribution strategy level, determine the specific distribution strategy level through the specific personalized distribution needs of each user under the user group.

9. An intelligent and secure distribution system for digital media, characterized in that, including The first module is used to classify and define the characteristics of the digital media content involved on the platform, collect the usage records of the digital media services of the user terminals on the platform, and count the digital media content category sets of each user terminal in the usage records of the digital media services; The second module is used to define the demand index of the network digital media of the user terminal according to the digital media content category set of each user terminal, and divide the user terminals into groups by virtue of the demand index of the network digital media; The third module is used to conduct a security risk assessment on each user group to obtain the security risk level, formulate an encryption security policy, analyze the personalized distribution needs of each user group, and formulate a distribution strategy; The fourth module is used to apply the encryption security policy and the distribution strategy to the encryption protection link after content production and the Internet of Things distribution link in the transmission network respectively.

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