A method and system for intelligent and secure distribution of digital media

Abstract

The present invention discloses a method and system for intelligent and secure distribution of digital media, which relates to the field of digital media data analysis technology. The method comprises: collecting statistics on the digital media content category set of each user terminal in the usage record of digital media services, analyzing the category and usage of the digital media content involved by each user, thereby better defining the network digital media demand index of the user terminal, and dividing user groups by considering the similarity of digital media demand between users. The method also performs a security risk assessment on each user group to obtain a security risk level, formulates an encryption security strategy, analyzes the personalized distribution needs of each user group, formulates a distribution strategy, and formulates different encryption security strategies and distribution strategies based on the needs of different user groups. The method improves the accuracy and adaptability of the security and adaptation of the intelligent distribution of digital media for different users, thereby simultaneously meeting the digital media service experience needs of different user groups to the greatest extent possible.

Description

Technical Field

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

[0002] In the digital age, digital media content is rapidly growing, and users are increasingly demanding high-quality, high-speed access to content. This poses challenges to traditional content delivery networks (CDNs). Multimedia content encompasses complex data types such as audio and video, requiring higher transmission speeds and latency. The growth of global network traffic is also increasing the burden on CDNs. Furthermore, the distribution of digital media content faces numerous security challenges, such as content tampering, privacy theft, and illegal dissemination. Against this backdrop, the Intelligent Multimedia Content Delivery Network (IMCDN) has emerged. It integrates artificial intelligence, big data analytics, and network optimization technologies to provide smarter and more efficient delivery of multimedia content through content identification and analysis, as well as real-time optimization. IMCDN also enhances content security, including encryption and hotlink prevention, to meet the demands of modern network transmission and provide users with a superior content access experience.

[0003] In the existing technology, the distribution process does not consider the similarity of users' digital media content needs to divide user groups, resulting in poor accuracy and adaptability of the security and adaptation of intelligent distribution of digital media for different users, and cannot simultaneously meet the digital media service experience needs of different user groups.

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

[0005] The purpose of the present invention is to solve the problem in the prior art that the security and accuracy of the adaptation of digital media for different users are poor due to the failure to consider the digital media needs of the user group. A method for intelligent and secure distribution of digital media is proposed, which includes:

[0006] Classify and define the characteristics of digital media content involved in the platform, collect usage records of digital media services of user terminals on the platform, and count the digital media content category set of each user terminal in the usage records of digital media services;

[0007] Defining the network digital media demand index of each user terminal according to the set of digital media content categories of each user terminal, and dividing the user terminals into groups based on the network digital media demand index;

[0008] Conduct security risk assessments on each user group, determine their security risk levels, formulate encryption security strategies, analyze the personalized distribution needs of each user group, and formulate distribution strategies;

[0009] The encryption security strategy and distribution strategy are applied to the encryption protection link after content production and the IoT distribution link in the transmission network respectively.

[0010] In some embodiments of the present application, the digital media content involved in the platform is classified and characterized, including:

[0011] Conduct basic media classification of digital media content based on the business conditions involved in the platform;

[0012] The characteristics of digital media content include four dimensions: timeliness, transmission sensitivity, cache applicability, and quality elasticity;

[0013] Search out the descriptive parameters involved in each of the four dimensions of timeliness, transmission sensitivity, cache applicability, and quality elasticity;

[0014] By integrating all descriptive parameters involved in the same dimension, we define timeliness index, transmission sensitivity index, cache applicability index and quality elasticity index to quantify the characteristics of the four dimensions of timeliness, transmission sensitivity, cache applicability and quality elasticity respectively.

[0015] In some embodiments of the present application, statistics of the digital media content category set of each user terminal in the usage record of the digital media service include:

[0016] Counting the digital media content categories of each user terminal in the usage records of the digital media service, and intercepting the corresponding record segments of the usage records of the digital media service according to the digital media content categories;

[0017] For multiple recording segments of the same digital media content category, the first-class features, second-class features and fluctuation parameters of each feature of each recording segment are extracted, and the confidence of each recording segment is determined by combining the fluctuation parameters of the first-class features and the second-class features. The weight of each standard is allocated according to the confidence of each recording segment, so as to perform weighted aggregation of the first-class features and the second-class features of multiple recording segments to obtain the standard values ​​of the first-class features and the second-class features. The standard value, timeliness index, transmission sensitivity index, cache applicability index and quality elasticity index are marked on each digital media content category of each user terminal.

[0018] In some embodiments of the present application, the confidence level of each recording segment is determined by integrating the fluctuation parameters of the first and second types of features, including:

[0019] The reliability of the first-class features is evaluated to obtain a score, and the confidence of each record segment is calculated based on the score of the first-class features, the fluctuation parameter of the first-class features, and the fluctuation parameter of the second-class features.

[0020] In some embodiments of the present application, the network digital media demand index of each user terminal is defined according to the digital media content category set of each user terminal, including:

[0021] The standard values, timeliness index, transmission sensitivity index, cache suitability index, and quality elasticity index of the first and second category features under all digital media content categories of the same user terminal are integrated to obtain the ranges of the standard values, timeliness index, transmission sensitivity index, cache suitability index, and quality elasticity index of the first and second category features respectively;

[0022] The demand index of the first-class characteristics, the second-class characteristics, the standard values, the timeliness index, the transmission sensitivity index, the cache applicability index and the quality elasticity index are determined according to their respective range intervals, thereby defining the demand index of the network digital media of each user terminal.

[0023] In some embodiments of the present application, a security risk assessment is performed on each user group to obtain a security risk level and formulate an encryption security strategy, including:

[0024] Security risk assessments are conducted on the behaviors of user groups and digital media content respectively, and security risk levels are obtained by combining the behaviors of user groups and digital media content. The encryption security strategy for each user group is mapped out through the security risk levels.

[0025] In some embodiments of the present application, analyzing the distribution personalization needs of each user group includes:

[0026] Constructing the digital media content preferences of each user group, making personalized digital media content recommendations based on the digital media content preferences of each user group, and classifying digital media content into old digital media content and new digital media content;

[0027] Combine old digital media content and new digital media content to determine the distribution personalization needs of user groups.

[0028] In some embodiments of the present application, a distribution strategy is formulated, including:

[0029] The distribution strategy level range is determined based on the distribution personalized needs of the user group. Within the distribution strategy level range, the specific distribution strategy level is determined based on the specific distribution personalized needs of each user in the user group.

[0030] Correspondingly, the present application also provides an intelligent and secure distribution system for digital media, comprising:

[0031] The first module is used to classify and define the characteristics of digital media content involved in the platform, collect usage records of digital media services of user terminals on the platform, and count the digital media content category set of each user terminal in the usage records of digital media services;

[0032] The second module is used to define the network digital media demand index of each user terminal according to the digital media content category set of each user terminal, and to divide the user terminals into groups based on the network digital media demand index;

[0033] The third module is used to conduct security risk assessment for each user group, obtain the security risk level, formulate encryption security strategy, analyze the distribution personalized needs of each user group, and formulate distribution strategy;

[0034] The fourth module is used to apply encryption security strategies and distribution strategies to the encryption protection link after content production and the Internet of Things distribution link in the transmission network.

[0035] The encryption security and distribution strategies described in the preceding steps can be implemented to a certain extent through media. Media (such as smart physical media like USB flash drives) can store digital media content, encryption keys, and identity authentication information. Media primarily handles data storage and transmission, providing the fundamental data carrier for the application of these strategies. This process involves three steps: media production, media transmission, and media use.

[0036] Media production process

[0037] Content Classification and Feature Definition: During the content production phase, targeted encryption is performed on different types of digital media content based on the platform's classification and feature definition. For example, a higher-level encryption algorithm is used for highly confidential film and television content. This classification information and encryption parameters can be stored on the media and distributed along with the content.

[0038] Encryption security policy application: According to the established encryption security policy, digital media content is encrypted using the corresponding encryption key and securely stored on the media (e.g., the encrypted storage area of ​​the smart physical media). Simultaneously, the encryption algorithm and related security parameters are written to the media for decryption during subsequent media use. Encryption policies include content encryption, content signing, and identity key writing. The encrypted content, content ID, content signature, and content signature public key certificate (collectively referred to as the content medium) are written to the smart physical media. This way, the smart physical media stores the encrypted and signed digital media content and related information.

[0039] For example, content encryption (performed in accordance with encryption security policies) involves assigning a content ID to high-quality digital media content, encrypting the content using a content key in accordance with ChinaDRM technology, calculating a content hash value for the encrypted content, and storing the content key in the ChinaDRM service. This step ensures the security of digital media content during storage and transmission, preventing content tampering or illegal access through encryption and hash value calculation.

[0040] Content Signature: This private key is used to sign the content ID, content hash, and other content-related data. This signature verifies the integrity of the content and the legitimacy of its source, ensuring that the recipient can verify that the content has not been tampered with and comes from a legitimate sender.

[0041] Writing the physical media identity key: The physical media identity private key and public key certificate are written to the smart physical media. The smart physical media then provides an interface for signing data using the physical media identity private key and for obtaining the physical media identity certificate. This step gives the smart physical media a unique identity, facilitating subsequent authentication and authorization operations.

[0042] Media transmission link

[0043] Distribution Strategy Application: Distribution strategies tailored to the personalized needs of different user groups can be implemented during media transport. For example, urgent or high-priority digital media content can be delivered to users via faster and more reliable logistics channels. Furthermore, encryption security policies can be incorporated into media transport to ensure both physical and data security during transport, preventing media loss or data leakage.

[0044] Media usage

[0045] Demand Index and Group Segmentation Application: When a user terminal uses media, the content category information stored in the media can be combined with the user terminal's usage history to further verify and update the digital media content category set for each user terminal. Based on the user terminal's group, the media can provide corresponding digital media services. For example, for user groups with a high demand index, the media can provide higher-quality digital media content or more value-added services.

[0046] Security Risk Assessment and Policy Application: During media use, the corresponding encryption security policy is implemented based on the identity authentication information and encryption keys stored in the media, combined with the backend server's security risk assessment of the user terminal. For example, for user groups with higher security risks, stricter identity authentication and key verification are required when decrypting digital media content stored in the media. Furthermore, based on the distribution policy, the media can control the access rights and methods of digital media content, such as limiting the number of plays and playback time.

[0047] The present invention has the following beneficial effects:

[0048] 1. Classify and define the characteristics of digital media content on the platform, thereby quantifying the characteristics of each basic digital media content category and providing a reliable basis for subsequent user digital media needs and user group segmentation. Based on the usage records of digital media services, the digital media content category set of each user terminal is counted, and the categories and usage of digital media content involved by each user are analyzed to better define the network digital media demand index of the user terminal. User groups are divided based on the similarities in digital media needs between users, thereby better formulating content security encryption strategies and distribution strategies during the subsequent user distribution process.

[0049] 2. Conduct security risk assessments on each user group to obtain security risk levels, formulate encryption security strategies, analyze the personalized distribution needs of each user group, formulate distribution strategies, and formulate different encryption security strategies and distribution strategies based on the needs of different user groups. This will improve the accuracy and adaptability of the security and adaptation of intelligent distribution of digital media for different users, and maximize the digital media service experience needs of different user groups at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 A schematic diagram of the flow of a method for intelligent and secure distribution of digital media proposed by the present invention;

[0051] Figure 2 This is a structural diagram of an intelligent and secure digital media distribution system proposed by the present invention. DETAILED DESCRIPTION

[0052] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0053] Reference Figure 1 , a method for intelligent and secure distribution of digital media, comprising the following steps:

[0054] Step S101 , classify and define characteristics of digital media content involved in the platform, collect usage records of digital media services of user terminals on the platform, and count the digital media content category set of each user terminal in the usage records of digital media services.

[0055] In this embodiment, digital media content is classified into the following basic categories based on platform service scenarios:

[0056] Video categories: long videos (UHD movies, TV series), short videos (TikTok, Kuaishou), live broadcasts (sports events, concerts).

[0057] Audio: Music, podcasts, audiobooks.

[0058] Graphics and text: news, blogs, and comics.

[0059] Interactive: games, VR / AR content.

[0060] The above categories of digital media content can be further divided according to specific application scenarios, and the content characteristics can be quantified from four dimensions:

[0061] Timeliness: The content’s requirement for real-time performance (e.g. live broadcast > news > movies).

[0062] Transmission sensitivity: The risk of content being tampered with during transmission (e.g., financial data > ordinary video).

[0063] Cache suitability: Whether the content is suitable for caching (e.g., popular movies are suitable for caching, but real-time news is not).

[0064] Quality flexibility: The content's tolerance for image and sound quality (e.g., short videos can accept low resolution, while movies require high resolution).

[0065] Count the categories of digital media content on user terminals (for example, user A accesses movies, music, and news).

[0066] The usage records of digital media services of user terminals on the collection platform are intercepted, and the record segments of each type of content are intercepted (for example, the record segment of user A accessing the movie "xxx" is "2023-10-01 20:00-22:00").

[0067] In some embodiments of the present application, the digital media content involved in the platform is classified and characterized, including:

[0068] Conduct basic media classification of digital media content based on the business conditions involved in the platform;

[0069] The characteristics of digital media content include four dimensions: timeliness, transmission sensitivity, cache applicability, and quality elasticity;

[0070] Search out the descriptive parameters involved in each of the four dimensions of timeliness, transmission sensitivity, cache applicability, and quality elasticity;

[0071] By integrating all descriptive parameters involved in the same dimension, we define timeliness index, transmission sensitivity index, cache applicability index and quality elasticity index to quantify the characteristics of the four dimensions of timeliness, transmission sensitivity, cache applicability and quality elasticity respectively.

[0072] In this embodiment, the description parameters involved in each of the four dimensions of timeliness, transmission sensitivity, cache applicability, and quality elasticity are searched out, specifically:

[0073] The timeliness dimension reflects the degree to which digital media content is time-sensitive. The descriptive parameters mainly include:

[0074] Content update frequency

[0075] Describes the time interval for content updates. For example, news may be updated every 5-10 minutes, while movies are usually released all at once and updated less frequently.

[0076] User access interval

[0077] Reflects the frequency of users accessing content. For example, popular movies may be accessed weekly, while real-time news may be accessed multiple times a day.

[0078] Expiration time

[0079] Describes the time from when content is published to when it loses its value, such as a weather forecast is usually valid for 24 hours after publication.

[0080] Real-time requirements

[0081] Users have expectations for real-time content. For example, live streaming requires millisecond-level latency, while on-demand content has lower real-time requirements.

[0082] The transmission sensitivity dimension reflects the speed and stability requirements of digital media content during transmission. The descriptive parameters mainly include:

[0083] Transmission bandwidth requirements

[0084] Describes the minimum bandwidth required for content transmission. For example, high-definition video may require a bandwidth of more than 10 Mbps, while text news only requires a few Kbps.

[0085] Transmission delay tolerance

[0086] The user's tolerance for transmission delay. For example, online games require low latency (<50ms), while email transmission is not sensitive to delay.

[0087] Packet loss rate tolerance

[0088] The user's tolerance for packet loss. For example, video calls allow a small amount of packet loss, while financial transactions have zero tolerance for packet loss.

[0089] Transmission security requirements

[0090] Describe the encryption and authentication requirements for content transmission. For example, bank transfers require strong encryption, while public videos can accept lower security.

[0091] Transport protocol requirements

[0092] Describes the protocol type required for content transmission, such as UDP protocol is required for real-time video, while TCP protocol can be used for file download.

[0093] The cache suitability dimension reflects whether digital media content is suitable for caching to improve access efficiency. The descriptive parameters mainly include:

[0094] Content access popularity

[0095] Describes the frequency with which content is accessed. For example, popular movies are frequently accessed and are therefore suitable for caching. However, unpopular content is less frequently accessed and therefore has low caching value.

[0096] Content size

[0097] Describes the storage space requirements of the content. For example, a high-definition movie may be 10GB, which has a high caching cost; while a short video may only be 100MB, which is suitable for caching.

[0098] Content update frequency

[0099] Content that is updated frequently has low cache value, such as real-time news; while content that is updated slowly (such as movies) has high cache value.

[0100] User access mode

[0101] Describes the regularity of user access to content. For example, content accessed at fixed times (such as daily news) is suitable for pre-caching.

[0102] Cache hit rate

[0103] Measures the probability of cached content being accessed again. Content with a high hit rate is suitable for caching.

[0104] The quality elasticity dimension reflects the tolerance of digital media content to quality changes. The descriptive parameters mainly include:

[0105] Resolution tolerance

[0106] Describes the user's acceptance of changes in content resolution. For example, short video users can accept lower resolutions (such as 480P), while movie users expect high resolution (such as 1080P).

[0107] Frame rate tolerance

[0108] The user's acceptance of changes in video frame rate. For example, game live streaming requires a high frame rate (such as 60fps), while surveillance video can accept a low frame rate (such as 15fps).

[0109] Bit rate tolerance

[0110] Users' acceptance of changes in content bitrates. For example, music streaming can automatically reduce the bitrate under low bandwidth, while professional audio production requires lossless bitrates.

[0111] Tolerance for image / sound quality loss

[0112] Describes the user's acceptance of content quality loss. For example, a slight loss of image quality is acceptable for real-time video calls, while high quality is required for movie playback.

[0113] Network bandwidth adaptability

[0114] Describes the content's adaptability to different bandwidths. For example, Adaptive Bitrate (ABR) technology can dynamically adjust quality based on bandwidth.

[0115] The descriptive parameters of the above four dimensions are only partially listed and are not exhaustive. The descriptive parameters under each dimension can be integrated through normalization or standardization and then weighted summation or weighted averaging to define the timeliness index, transmission sensitivity index, cache applicability index, and quality elasticity index.

[0116] In some embodiments of the present application, statistics of the digital media content category set of each user terminal in the usage record of the digital media service include:

[0117] Counting the digital media content categories of each user terminal in the usage records of the digital media service, and intercepting the corresponding record segments of the usage records of the digital media service according to the digital media content categories;

[0118] For multiple recording segments of the same digital media content category, the first-class features, second-class features and fluctuation parameters of each feature of each recording segment are extracted, and the confidence of each recording segment is determined by combining the fluctuation parameters of the first-class features and the second-class features. The weight of each standard is allocated according to the confidence of each recording segment, so as to perform weighted aggregation of the first-class features and the second-class features of multiple recording segments to obtain the standard values ​​of the first-class features and the second-class features. The standard value, timeliness index, transmission sensitivity index, cache applicability index and quality elasticity index are marked on each digital media content category of each user terminal.

[0119] In this embodiment, corresponding record segments are intercepted from the usage record of the digital media service according to the digital media content category, and part of the record segments on the usage record are intercepted based on the digital media content category.

[0120] Category 1 features: content attributes (such as duration, number of plays, and resolution). Category 2 features: user behavior attributes (such as play completion rate, experience feedback, and skip rate). Fluctuation parameters for both categories of features can be parameters that describe fluctuations, such as rate of change, frequency, and standard deviation. Confidence is determined by combining the score of the category 1 feature, its fluctuation parameters, and the fluctuation parameters of the category 2 features (since category 2 features represent user experience feedback and only require stability). Multiple recording segments for the same digital media content category may be complex (due to large amounts of data for category 1 and category 2 features) and exhibit significant variation. Therefore, it is necessary to determine the confidence level for each recording segment. This confidence level is then used to calculate standard values ​​for the category 1 and category 2 features. The standard values ​​represent the most common and representative values ​​or ranges for the features corresponding to the media content. The standard values, timeliness index, transmission sensitivity index, cache suitability index, and quality resilience index are tagged with the content category of the user terminal. The digital media content category set for the user terminal includes the digital media content category and the standard values, timeliness index, transmission sensitivity index, cache suitability index, and quality resilience index for each category.

[0121] In some embodiments of the present application, the confidence level of each recording segment is determined by integrating the fluctuation parameters of the first and second types of features, including:

[0122] The reliability of the first-class features is evaluated to obtain a score, and the confidence of each record segment is calculated based on the score of the first-class features, the fluctuation parameter of the first-class features, and the fluctuation parameter of the second-class features.

[0123] In this embodiment, a type of feature generally refers to attributes directly related to the content itself (such as resolution, bit rate, duration, etc.), and its reliability evaluation requires quantitative analysis from multiple dimensions. The following dimensions can be used for analysis:

[0124] Stability: The degree to which a characteristic value varies over time or space.

[0125] Conformity: The degree to which a characteristic value conforms to an expected or standard value.

[0126] Predictability: Whether the feature value can be predicted through historical data or models.

[0127] Completeness: Whether the feature values ​​are complete (e.g., no missing or outliers).

[0128] Rating of a type of feature: reflects the reliability of content attributes.

[0129] Fluctuation parameters of a type of feature: reflecting the degree of change in content attributes in time or space (such as the standard deviation of resolution).

[0130] Fluctuation parameter of the second-category feature: reflects the degree of change in user behavior attributes (such as the standard deviation of the playback completion rate). The confidence of each recording segment is calculated based on the score of the first-category feature, the fluctuation parameter of the first-category feature, and the fluctuation parameter of the second-category feature. The specific calculation formula is as follows:

[0131] ;

[0132] in, For the The confidence level of each recorded segment, The confidence conversion coefficient for scoring a class of features, For the A class of feature scores for each record segment, 、 are the combined weights of the fluctuation parameters of the first and second types of features, 、 Respectively The fluctuation parameters of the first and second characteristics of each recording segment, For the The first constant of the record segment, It represents the correction of the first-class feature score due to the fluctuation of the first-class feature and the second-class feature. The first constant is used to balance the size of the correction function. The first-class feature and the second-class feature can be a representative single feature among multiple features, or a combination of multiple features.

[0133] Step S102 : defining a network digital media demand index of each user terminal according to a set of digital media content categories of each user terminal, and dividing the user terminals into groups based on the network digital media demand index.

[0134] In this embodiment, each user's demand for network digital media is defined based on the user's digital media content category and the standard value of the category, timeliness index, transmission sensitivity index, cache applicability index and quality elasticity index, and user groups are divided according to the differences in the network digital media demand index of different users.

[0135] In some embodiments of the present application, the network digital media demand index of each user terminal is defined according to the digital media content category set of each user terminal, including:

[0136] The standard values, timeliness index, transmission sensitivity index, cache suitability index, and quality elasticity index of the first and second category features under all digital media content categories of the same user terminal are integrated to obtain the ranges of the standard values, timeliness index, transmission sensitivity index, cache suitability index, and quality elasticity index of the first and second category features respectively;

[0137] The demand index of the first-class characteristics, the second-class characteristics, the standard values, the timeliness index, the transmission sensitivity index, the cache applicability index and the quality elasticity index are determined according to their respective range intervals, thereby defining the demand index of the network digital media of each user terminal.

[0138] In this embodiment, the ranges of the standard values ​​for the first and second category features, the timeliness index, the transmission sensitivity index, the cache suitability index, and the quality elasticity index represent the full range of these parameters for all digital media content for a single user. The demand index for different parameters can be determined using evaluation or entropy weighting methods. The specific calculation formula for defining the demand index for network digital media for each user terminal is as follows:

[0139] ;

[0140] in, For the The demand index of network digital media for user terminals, There are four indicators: timeliness index, transmission sensitivity index, cache applicability index and quality elasticity index. The first among the four The combined weights corresponding to the indicators are: For the The first user terminal The demand index of the indicator, 、 are the contribution coefficients of the first-class features and the second-class features, 、 2 is the number of first-class features and second-class features, 、 Respectively The first-class features and The combined weight of the two-class features, 、 Respectively The first user terminal The first-class features and The demand index of each of the two characteristics is For the The second constant of the user terminal, It represents the correction of the average values ​​of the timeliness index, transmission sensitivity index, cache applicability index, and quality elasticity index based on the combination of the first and second feature requirements. The second constant is used to balance the size of the correction function.

[0141] Step S103 , performing security risk assessment on each user group, obtaining a security risk level, formulating an encryption security strategy, analyzing the personalized distribution needs of each user group, and formulating a distribution strategy.

[0142] In this embodiment, the goal of security risk assessment is to identify potential security threats of user groups and classify security risk levels. These risks are often associated with users' digital media needs, so risk assessment is performed on a user group basis.

[0143] In some embodiments of the present application, a security risk assessment is performed on each user group to obtain a security risk level and formulate an encryption security strategy, including:

[0144] Security risk assessments are conducted on the behaviors of user groups and digital media content respectively, and security risk levels are obtained by combining the behaviors of user groups and digital media content. The encryption security strategy for each user group is mapped out through the security risk levels.

[0145] In this embodiment, the evaluation dimensions include the following two aspects:

[0146] User behavior risks:

[0147] Abnormal access patterns (e.g., frequent login failures, access at unusual times).

[0148] Malicious behavior (such as content tampering and DDoS attacks).

[0149] Content Risks:

[0150] Sensitive content (e.g., involving politics, violence).

[0151] Content copyright (such as the risk of dissemination of pirated content).

[0152] Security risk level classification

[0153] Low risk: User behavior is normal and the content is of low sensitivity.

[0154] Medium Risk: Occasional unusual behavior or moderately sensitive content.

[0155] High risk: Frequent unusual behavior or highly sensitive content.

[0156] The three risk levels above can be further divided into more detailed categories. For low risk, basic encryption is used, suitable for low-sensitivity content and normal user behavior. Technical implementation includes AES-128 encryption and the HTTPS transmission protocol. For medium risk, enhanced encryption is used, suitable for moderately sensitive content or occasional abnormal behavior. Technical implementation includes enhanced encryption, suitable for moderately sensitive content or occasional abnormal behavior. Technical implementation includes AES-256 encryption, TLS 1.3 protocol, and digital signature verification. For high risk, military-grade or membership-level encryption is used, suitable for highly sensitive content or frequent abnormal behavior. Technical implementation includes AES-256 + digital watermarking, end-to-end encryption (E2EE), zero-knowledge proof, and blockchain evidence storage.

[0157] In some embodiments of the present application, analyzing the distribution personalization needs of each user group includes:

[0158] Constructing the digital media content preferences of each user group, making personalized digital media content recommendations based on the digital media content preferences of each user group, and classifying digital media content into old digital media content and new digital media content;

[0159] Combine old digital media content and new digital media content to determine the distribution personalization needs of user groups.

[0160] In some embodiments of the present application, a distribution strategy is formulated, including:

[0161] The distribution strategy level range is determined based on the distribution personalized needs of the user group. Within the distribution strategy level range, the specific distribution strategy level is determined based on the specific distribution personalized needs of each user in the user group.

[0162] In this embodiment, digital media content preferences are constructed:

[0163] Data source:

[0164] User historical behavior data (such as click-through rate, playback time, and collection behavior).

[0165] Content metadata (e.g., category, duration, resolution).

[0166] Analytical methods:

[0167] Collaborative filtering: recommending content based on user similarity.

[0168] Deep learning models: Use neural networks (such as the Wide & Deep model) to predict user preferences.

[0169] Personalized content recommendations

[0170] Recommended logic:

[0171] Old content recommendation: Recommend classic content based on historical playback records.

[0172] New content recommendation: Recommend new content based on trends and similar user behaviors.

[0173] Distribution strategy levels include basic distribution, standard distribution, priority distribution, advanced distribution, etc., including the following examples:

[0174] (1) Basic Distribution (Level 1)

[0175] Applicable scenarios: low-sensitivity, low-value content, or scenarios with low user demand.

[0176] Strategy content:

[0177] Transport protocol: Use HTTP (non-encrypted) or basic HTTPS.

[0178] Storage method: ordinary cloud storage (such as AWS S3 standard storage).

[0179] Distribution method: Single-source CDN distribution, no redundant backup.

[0180] Cache policy: No cache or basic cache (shorter TTL).

[0181] Fault tolerance mechanism: None or basic retry mechanism.

[0182] Example:

[0183] Free news short videos, low-resolution images.

[0184] (2) Standard Distribution (Level 2)

[0185] Applicable scenarios: general user needs, moderately sensitive content.

[0186] Strategy content:

[0187] Transport protocol: Use standard HTTPS (TLS 1.2+).

[0188] Storage method: Encrypted cloud storage (such as AWS S3-Intelligent Tiering).

[0189] Distribution method: multi-source CDN distribution, basic redundant backup.

[0190] Caching strategy: Edge caching (moderate TTL).

[0191] Fault tolerance mechanism: basic retry mechanism (such as 3 retries).

[0192] Example:

[0193] Regular movies, TV shows, music.

[0194] (3) Priority Distribution (Level 3)

[0195] Applicable scenarios: high-demand content, or scenarios where users are sensitive to latency.

[0196] Strategy content:

[0197] Transport protocol: Use HTTP / 2 or QUIC protocol to optimize transmission efficiency.

[0198] Storage method: high-performance storage (such as AWS EBS gp3).

[0199] Distribution method: P2P+CDN hybrid distribution, dynamic load balancing.

[0200] Caching strategy: Deep edge caching (longer TTL), preloading popular content.

[0201] Fault tolerance mechanism: intelligent retry mechanism (such as exponential backoff algorithm).

[0202] Example:

[0203] Popular live broadcasts, sports events, and short videos with high click-through rates.

[0204] (4) Advanced Distribution (Level 4)

[0205] Applicable scenarios: high-value content, or scenarios where users are extremely sensitive to latency.

[0206] Strategy content:

[0207] Transport protocol: Use HTTP / 3 (based on QUIC) and support 0-RTT handshake.

[0208] Storage method: low-latency storage (such as AWS EBS io1 / io2).

[0209] Distribution method: edge computing + CDN distribution, dynamic path optimization.

[0210] Caching strategy: global cache (TTL is dynamically adjusted based on content popularity), multi-level cache.

[0211] Fault-tolerance mechanisms: multi-path transmission (such as MP-TCP), fast failover.

[0212] Example:

[0213] 4K / 8K movies, VR content, and real-time financial data.

[0214] Within the distribution strategy level range (including multiple distribution strategy levels), the strategy level is dynamically adjusted based on the specific needs of each user in the user group, and the adjustment rules are as follows:

[0215] If the user's real-time click-through rate is high, upgrade the distribution strategy level (for example, from "medium demand" to "high demand").

[0216] If the user's network status is poor, lower the distribution strategy level (for example, downgrade from "high demand" to "medium demand").

[0217] In step S104, the encryption security policy and the distribution policy are applied to the encryption protection link after content production and the Internet of Things distribution link in the transmission network respectively.

[0218] In this embodiment, the distribution process of digital media content can be divided into the following six key steps:

[0219] Content production and coding

[0220] Original content (such as video and audio) is edited and encoded to generate distributable media files.

[0221] Content encryption protection

[0222] Encrypt media files to prevent the content from being stolen or tampered with during transmission or storage.

[0223] Content storage and caching

[0224] The encrypted content is stored in a centralized or distributed storage system and may be cached at edge nodes.

[0225] Transmission network distribution

[0226] Distribute content to user terminals through Internet of Things (IoT) devices or traditional networks.

[0227] User terminal decryption and playback

[0228] The user terminal receives the encrypted content, decrypts it using the legal key, and then plays it.

[0229] User behavior feedback

[0230] Collect user playback behavior data (such as playback duration and click-through rate) to optimize subsequent distribution strategies.

[0231] Encryption security policies are mainly used in content encryption protection to ensure the security of content during storage and transmission. The following are specific applications:

[0232] (1) Content encryption protection

[0233] Encryption target:

[0234] Prevent content from being stolen or tampered with during storage or transmission.

[0235] Encryption policy selection:

[0236] Choose encryption strength based on content sensitivity and user risk level.

[0237] Low-risk content: AES-128 encryption (like regular movies).

[0238] High-risk content: AES-256+ digital watermark (e.g., unreleased movies).

[0239] Key Management:

[0240] Low risk: Centralized key management (such as provided by cloud service providers).

[0241] High risk: Distributed key management (such as HSM hardware security modules) or zero-knowledge proofs.

[0242] (2) User terminal decryption and playback

[0243] Decryption target:

[0244] Ensure that only legitimate users can decrypt content.

[0245] Decryption strategy:

[0246] Low risk: The user terminal directly decrypts the AES-128 content.

[0247] High risk: The user terminal must pass biometric authentication (such as fingerprint) to decrypt AES-256 content.

[0248] Distribution strategies are mainly used in the transmission network distribution link to ensure that content is efficiently and securely transmitted to user terminals. The following are specific applications:

[0249] (1) Transmission network distribution link

[0250] Distribution Target:

[0251] Optimize content transmission efficiency, reduce latency, and improve user experience.

[0252] Distribution strategy selection:

[0253] Select the distribution strategy level based on content requirements and user network environment.

[0254] Low-demand content: Basic distribution (such as HTTP protocol, single-source CDN).

[0255] High-demand content: Advanced delivery (such as HTTP / 3 + edge computing).

[0256] Distribution method:

[0257] Basic distribution: single-source CDN distribution, no redundant backup.

[0258] Advanced distribution: P2P + CDN hybrid distribution, dynamic load balancing.

[0259] Example:

[0260] News short videos (low demand): Basic distribution, transmitted through a single-source CDN.

[0261] 4K movies (high demand): Advanced distribution, real-time distribution through edge computing nodes.

[0262] (2) Content storage and caching

[0263] Cache target:

[0264] Reduce transmission delay and improve playback smoothness.

[0265] Caching strategy:

[0266] Low-demand content: no cache or basic cache (short TTL).

[0267] High-demand content: Deep edge caching (longer TTL) to preload popular content.

[0268] Example:

[0269] Ordinary TV series (low demand): basic cache, TTL is 1 day.

[0270] Popular live broadcasts (high demand): Deep edge caching, 7-day TTL, and preloading.

[0271] Correspondingly, this application also provides an intelligent and secure distribution system for digital media, such as Figure 2 Shown, including,

[0272] The first module is used to classify and define the characteristics of digital media content involved in the platform, collect usage records of digital media services of user terminals on the platform, and count the digital media content category set of each user terminal in the usage records of digital media services;

[0273] The second module is used to define the network digital media demand index of each user terminal according to the digital media content category set of each user terminal, and to divide the user terminals into groups based on the network digital media demand index;

[0274] The third module is used to conduct security risk assessment for each user group, obtain the security risk level, formulate encryption security strategy, analyze the distribution personalized needs of each user group, and formulate distribution strategy;

[0275] The fourth module is used to apply encryption security strategies and distribution strategies to the encryption protection link after content production and the Internet of Things distribution link in the transmission network.

[0276] The present invention has the following beneficial effects:

[0277] 1. Classify and define the characteristics of digital media content on the platform, thereby quantifying the characteristics of each basic digital media content category and providing a reliable basis for subsequent user digital media needs and user group segmentation. Based on the usage records of digital media services, the digital media content category set of each user terminal is counted, and the categories and usage of digital media content involved by each user are analyzed to better define the network digital media demand index of the user terminal. User groups are divided based on the similarities in digital media needs between users, thereby better formulating content security encryption strategies and distribution strategies during the subsequent user distribution process.

[0278] 2. Conduct security risk assessments on each user group to obtain security risk levels, formulate encryption security strategies, analyze the personalized distribution needs of each user group, formulate distribution strategies, and formulate different encryption security strategies and distribution strategies based on the needs of different user groups. This will improve the accuracy and adaptability of the security and adaptation of intelligent distribution of digital media for different users, and maximize the digital media service experience needs of different user groups at the same time.

[0279] Through the above description of the embodiments, those skilled in the art will clearly understand that the present invention can be implemented via hardware or via software combined with a necessary general-purpose hardware platform. Based on this understanding, the technical solution of the present invention can be embodied in the form of a software product. This software product can be stored on a non-volatile storage medium (such as a CD-ROM, USB flash drive, or external hard drive) and includes instructions for enabling a computer device (such as a personal computer, server, or network device) to execute the methods described in various implementation scenarios of the present invention.

[0280] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of a preferred implementation scenario, and the modules or processes in the accompanying drawings are not necessarily required to implement the present invention.

[0281] Those skilled in the art will appreciate that the modules in the system of the implementation scenario can be distributed in the system of the implementation scenario according to the implementation scenario description, or can be modified accordingly and located in one or more systems different from the implementation scenario. The modules of the above implementation scenario can be combined into one module or further divided into multiple submodules.

[0282] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. A method for intelligent and secure distribution of digital media, characterized in that: include, Classify and define the characteristics of digital media content involved in the platform, collect usage records of digital media services of user terminals on the platform, and count the digital media content category set of each user terminal in the usage records of digital media services; Defining the network digital media demand index of each user terminal according to the set of digital media content categories of each user terminal, and dividing the user terminals into groups based on the network digital media demand index; Conduct security risk assessments on each user group, determine their security risk levels, formulate encryption security strategies, analyze the personalized distribution needs of each user group, and formulate distribution strategies; Apply encryption security strategies and distribution strategies to the encryption protection link after content production and the IoT distribution link in the transmission network respectively; in, The digital media content category set of each user terminal is counted in the usage record of the digital media service, including: Counting the digital media content categories of each user terminal in the usage records of the digital media service, and intercepting the corresponding record segments of the usage records of the digital media service according to the digital media content categories; For multiple recording segments of the same digital media content category, extract the first-category features, second-category features, and fluctuation parameters of each feature from each recording segment. Determine the confidence level of each recording segment by combining the fluctuation parameters of the first-category features and the second-category features. Assign each standard weight according to the confidence level of each recording segment, thereby performing weighted aggregation of the first-category features and the second-category features of the multiple recording segments to obtain standard values ​​for the first-category features and the second-category features. The standard values, timeliness index, transmission sensitivity index, cache applicability index, and quality elasticity index are marked on each digital media content category of each user terminal. The demand index of network digital media of each user terminal is defined according to the digital media content category set of each user terminal, including: The standard values, timeliness index, transmission sensitivity index, cache suitability index, and quality elasticity index of the first and second category features under all digital media content categories of the same user terminal are integrated to obtain the ranges of the standard values, timeliness index, transmission sensitivity index, cache suitability index, and quality elasticity index of the first and second category features respectively; Determining the demand index of the first-category feature, the second-category feature, the standard value, the timeliness index, the transmission sensitivity index, the cache applicability index, and the quality elasticity index based on their respective ranges, thereby defining the demand index of the network digital media of each user terminal; The standard values ​​of the first and second type characteristics, the timeliness index, the transmission sensitivity index, the cache applicability index and the quality elasticity index are determined by evaluation or entropy weight method; The specific calculation formula for defining the demand index of network digital media for each user terminal is as follows: ; in, For the The demand index of network digital media for user terminals, There are four indicators: timeliness index, transmission sensitivity index, cache applicability index and quality elasticity index. The first among the four The combined weights corresponding to the indicators are: For the The first user terminal The demand index of the indicator, 、 are the contribution coefficients of the first-class features and the second-class features, 、 are the number of first-class features and second-class features, 、 Respectively The first-class features and The combined weight of the two-class features, 、 Respectively The first user terminal The first-class features and The demand index of each of the two characteristics is For the The second constant of the user terminal, It represents the correction of the average values ​​of the timeliness index, transmission sensitivity index, cache applicability index, and quality elasticity index based on the combination of the first and second feature requirements. The second constant is used to balance the size of the correction function.

2. The method for intelligent and secure distribution of digital media according to claim 1, wherein: Classify and characterize the digital media content on the platform, including: Conduct basic media classification of digital media content based on 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 out the descriptive parameters involved in each of the four dimensions of timeliness, transmission sensitivity, cache applicability, and quality elasticity; By integrating all descriptive parameters involved in the same dimension, we define timeliness index, transmission sensitivity index, cache applicability index and quality elasticity index to quantify the characteristics of the four dimensions of timeliness, transmission sensitivity, cache applicability and quality elasticity respectively.

3. The method for intelligent and secure distribution of digital media according to claim 1, wherein: The confidence of each record segment is determined by combining the fluctuation parameters of the first and second class features, including: The reliability of the first-class features is evaluated to obtain a score, and the confidence of each record segment is calculated based on the score of the first-class features, the fluctuation parameter of the first-class features, and the fluctuation parameter of the second-class features.

4. The method for intelligent and secure distribution of digital media according to claim 1, wherein: Conduct security risk assessment for each user group, obtain security risk level, and formulate encryption security strategy, including, Security risk assessments are conducted on the behaviors of user groups and digital media content respectively, and security risk levels are obtained by combining the behaviors of user groups and digital media content. The encryption security strategy for each user group is mapped out through the security risk levels.

5. The method for intelligent and secure distribution of digital media according to claim 1, wherein: Analyze the distribution personalized needs of each user group, include, Constructing the digital media content preferences of each user group, making personalized digital media content recommendations based on the digital media content preferences of each user group, and classifying digital media content into old digital media content and new digital media content; Combine old digital media content and new digital media content to determine the distribution personalization needs of user groups.

6. The method for intelligent and secure distribution of digital media according to claim 5, characterized in that: Develop a distribution strategy, including, The distribution strategy level range is determined based on the distribution personalized needs of the user group. Within the distribution strategy level range, the specific distribution strategy level is determined based on the specific distribution personalized needs of each user in the user group.

7. An intelligent and secure distribution system for digital media, characterized in that: A method for implementing the intelligent and secure distribution of digital media according to any one of claims 1 to 6, wherein the system comprises: The first module is used to classify and define the characteristics of digital media content involved in the platform, collect usage records of digital media services of user terminals on the platform, and count the digital media content category set of each user terminal in the usage records of digital media services; The second module is used to define the network digital media demand index of each user terminal according to the digital media content category set of each user terminal, and to divide the user terminals into groups based on the network digital media demand index; The third module is used to conduct security risk assessment for each user group, obtain the security risk level, formulate encryption security strategy, analyze the distribution personalized needs of each user group, and formulate distribution strategy; The fourth module is used to apply encryption security strategies and distribution strategies to the encryption protection link after content production and the Internet of Things distribution link in the transmission network.

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