Dynamic audio content binding and anti-counterfeiting verification method for voice blind box product

Abstract

The invention relates to the technical field of dynamic audio content binding and anti-counterfeiting verification of a voice blind box product, in particular to a dynamic audio content binding and anti-counterfeiting verification method for the voice blind box product. The system comprises an audio content acquisition module, a hardware coding module, an encryption processing module, an identifier generation module, a decoding verification module and a cloud collaboration module. According to the invention, the unique identifier is generated through a hardware coding mapping mechanism and an encryption algorithm, the legality and security of the audio content are ensured in combination with a multi-stage verification mechanism, and cross-platform binding and verification are realized at the same time. According to the application, the security, the anti-counterfeiting capability and the system suitability of the audio content can be improved, and the efficient dynamic binding and real-time verification requirements of the voice blind box product in different scenes can be met.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of information security and digital content management, specifically a dynamic audio content binding and anti-counterfeiting verification method for voice blind box products. BACKGROUND

[0002] With the rapid development of voice interaction technology and dynamic audio content binding technology, voice blind box products have gradually become a new form of interactive entertainment. However, there is still room for improvement in existing technologies in terms of dynamic audio content binding and anti-counterfeiting verification, and the market's demand for high security and high user experience has not been fully met.

[0003] After searching, a patent with publication number CN116328309B proposes a game interaction method for high-level needs of visually impaired people in virtual agricultural tourism scenes, with a disclosure date of October 13, 2023. This technology generates an initial virtual agricultural tourism scene and dynamically updates the audio of target objects based on the matching degree of real and virtual paths. This solution can meet the multi-level needs of visually impaired people, but its dynamic audio binding mechanism relies mainly on path matching algorithms and does not involve audio content anti-counterfeiting verification functions. In addition, the application scenario of this solution is focused on virtual agricultural tourism scenes, and its universality is relatively limited, making it difficult to be directly applied to the dynamic audio binding and anti-counterfeiting needs of voice blind box products.

[0004] The above problems show that existing dynamic audio content binding technology still has room for improvement in terms of integration of anti-counterfeiting verification functions, universality of application scenarios, and hardware adaptation capabilities. Therefore, the present application provides a dynamic audio content binding and anti-counterfeiting verification method for voice blind box products, aiming to achieve efficient dynamic binding and unique verification of audio content, improve the security and user experience of voice blind box products, and meet the market's demand for high-quality voice interaction products. SUMMARY

[0005] The purpose of the present application is to provide a dynamic audio content binding and anti-counterfeiting verification method for voice blind box products to solve the problems raised in the background art.

[0006] To achieve the above-mentioned purpose, the present application provides the following technical solution: a dynamic audio content binding and anti-counterfeiting verification method for voice blind box products, the method comprising the following steps:

[0007] S01: obtaining the audio content to be bound from an external storage device or a cloud server through an audio content acquisition module;

[0008] S02: extracting and processing the key metadata of the audio content using a hardware encoding module, wherein the hardware encoding module includes a data extraction unit, an encryption processing unit, and an identification generation unit;

[0009] S03: The encryption processing module uses the Advanced Encryption Standard algorithm to encrypt the key metadata;

[0010] S04: The identification generation module generates an identifier corresponding uniquely to the hardware device and embeds the identifier in the audio content;

[0011] S05: The decoding verification module parses the identifier in the audio content and compares it with the encoding information of the hardware device to complete the legality verification;

[0012] S06: The cloud collaboration module receives the identifier of the audio content and the encoding information of the hardware device and performs legality verification thereon.

[0013] Preferably, the data extraction unit of the hardware encoding module extracts the timestamp, audio format, and sampling rate from the audio content as key metadata.

[0014] Preferably, the encryption processing module uses a symmetric encryption algorithm to encrypt the key metadata and generates a final unique identifier in combination with the encoding information of the hardware device.

[0015] Preferably, the identification generation module generates an identifier corresponding uniquely to the hardware device by a hash function and embeds the identifier in the audio content.

[0016] Preferably, the decoding verification module verifies the legality of the audio content through a multi-level verification mechanism, including three stages of preliminary verification, deep verification, and final confirmation.

[0017] Preferably, the preliminary verification stage checks the identifier of the audio content by a fast hash algorithm, the deep verification stage performs full comparison in combination with the encoding information of the hardware device, and the final confirmation stage performs secondary verification on the legality of the audio content by the cloud collaboration module.

[0018] Preferably, the audio content acquisition module further includes a data classification unit that classifies and stores the audio content according to its type, format, and purpose, and uses a primary classification standard to distinguish audio types, a secondary classification standard to distinguish audio formats, and a tertiary classification standard to distinguish audio purposes.

[0019] Preferably, the hardware encoding module supports dynamic update function and updates the encoding information of the hardware device in real time by receiving instructions from the cloud collaboration module.

[0020] Preferably, the cloud collaboration module comprises a data storage unit and a verification processing unit, the data storage unit is used for storing metadata of the audio content and encoding information of the hardware device, and the verification processing unit is used for judging the legality of the audio content according to a preset rule.

[0021] Preferably, the decoding verification module is connected with the hardware encoding module and the cloud collaboration module through a bidirectional data channel to ensure efficient data transmission required in the verification process.

[0022] Compared with the prior art, the method has the following beneficial effects:

[0023] 1. The method can realize efficient dynamic binding and anti-counterfeiting verification of the audio content without relying on a traditional path matching algorithm, and can generate a unique identifier through a hardware encoding mapping mechanism and an encryption algorithm, thereby improving the security and anti-counterfeiting capability of the audio content.

[0024] 2. The method can ensure the legality of the audio content through a multi-level verification mechanism, while shortening the verification time and improving the user experience.

[0025] 3. The method can realize cross-platform binding and verification of the audio content through the collaborative work of the cloud server and the hardware device, thereby improving the universality and adaptability of the system. BRIEF DESCRIPTION OF DRAWINGS

[0026] Figure 1 The figure is a schematic diagram of the system architecture of the application. DETAILED DESCRIPTION

[0027] The technical solutions in the embodiments of the application are described clearly and completely. Obviously, the described embodiments are only part of the embodiments of the application, not all. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the application.

[0028] Please refer to Figure 1 The application provides a technical solution: a dynamic audio content binding and anti-counterfeiting verification method for a voice blind box product, comprising an audio content acquisition module, a hardware encoding module, an encryption processing module, an identifier generation module, a decoding verification module and a cloud collaboration module. These modules are connected through data flow and logic to form a complete system architecture, have clear connection relationship and positional relationship with each other, and jointly complete the function of dynamic audio content binding and anti-counterfeiting verification.

[0029] The audio content acquisition module is the starting part of the system, and its main task is to obtain the audio content to be bound from external storage devices or cloud servers. The audio content acquisition module communicates with external devices through network interfaces or physical interfaces, receives audio files and transmits them to the hardware encoding module for subsequent processing. The audio content acquisition module internally contains a data classification unit, which classifies and stores audio files according to their type, format and purpose. The data classification unit uses multi-level classification standards, where the first-level classification standard is used to distinguish audio types, the second-level classification standard is used to distinguish audio formats, and the third-level classification standard is used to subdivide audio purposes. This classification mechanism ensures that the audio content has been standardized before entering the hardware encoding module, thereby providing a clear data basis for subsequent operations.

[0030] The hardware encoding module is one of the core components of the entire system, which is composed of a data extraction unit, an encryption processing unit and an identifier generation unit. The data extraction unit is responsible for extracting key metadata from the audio content, such as timestamp, audio format, sampling rate, etc. These metadata are extracted and passed to the encryption processing unit in a structured form, and the encryption processing unit uses the Advanced Encryption Standard (AES) algorithm to encrypt the extracted metadata, ensuring the security of the data during transmission and storage. The encrypted metadata are then passed to the identifier generation unit, which generates an identifier unique to the hardware device through a hash function and embeds it in the audio content. This process is completed through the collaborative work of the hardware encoding module and the encryption processing module, ensuring the uniqueness and irreversibility of the identifier. The hardware encoding module is located between the audio content acquisition module and the encryption processing module, and the data stream interaction between the two modules is realized through the internal bus.

[0031] The main task of the encryption processing module is to further secure the metadata of the audio content. The encryption processing module uses a symmetric encryption algorithm to encrypt the metadata, and combines the encoding information of the hardware device to generate the final unique identifier. The encryption processing module is directly connected to the hardware encoding module through a data channel, ensuring seamless integration of the encryption processing process and the identifier generation process of the hardware encoding module. The encryption processing module also supports dynamic update function, which can adjust the encryption algorithm parameters in real time according to the instructions of the cloud collaborative module, so as to adapt to the audio content binding requirements in different scenarios. In addition, the encryption processing module communicates with the identifier generation module through a special data link, ensuring that the encrypted data can be efficiently transmitted to the identifier generation module.

[0032] The task of the identification generation module is to generate an identifier that corresponds uniquely to the hardware device and embed it in the audio content. The identification generation module processes the data passed by the encryption processing module through a hash function to generate a unique identifier. This identifier not only contains the key metadata of the audio content, but also combines the encoding information of the hardware device, ensuring the uniqueness and tamper resistance of the identifier. The identification generation module is connected to the hardware encoding module and the encryption processing module through a high-speed data channel, ensuring the real-time and accuracy of data transmission. After the identifier generated by the identification generation module is embedded in the audio content, the audio content will be passed to the decoding verification module for legality verification.

[0033] The decoding verification module is responsible for parsing the unique identifier in the audio content and comparing it with the encoding information of the hardware device. The decoding verification module completes this process through a multi-level verification mechanism, including preliminary verification, deep verification and final confirmation. The preliminary verification stage checks the identifier of the audio content through a fast hash algorithm to ensure the basic legality of the identifier. The deep verification stage combines the encoding information of the hardware device to compare the identifier in full, ensuring that the identifier is completely consistent with the encoding information of the hardware device. The final confirmation stage performs a second verification of the legality of the audio content through the cloud collaborative module to ensure the authenticity and security of the audio content. The decoding verification module is connected to the hardware encoding module and the cloud collaborative module through a bidirectional data channel to ensure efficient transmission of the data required in the verification process.

[0034] The cloud collaborative module, as the remote support part of the system, its main task is to communicate with the hardware device through network connection, receive the identifier of the audio content and the encoding information of the hardware device, and verify its legality. The cloud collaborative module includes a data storage unit and a verification processing unit, the data storage unit is responsible for storing the metadata of the audio content and the encoding information of the hardware device, and the verification processing unit judges the legality of the audio content according to the preset rules. The cloud collaborative module is connected to the decoding verification module through a network interface to ensure that the verification result can be fed back to the hardware device in a timely manner. The cloud collaborative module also supports dynamic update function, which can adjust the verification rules and parameters according to the actual demand, so as to improve the flexibility and expansibility of the system.

[0035] In practical application scenarios, the voice blind box device completes the whole process of dynamic audio content binding and anti-counterfeiting verification through the cooperative work of the above modules. First, the user obtains the audio content to be bound from the external storage device or the cloud server through the audio content acquisition module of the voice blind box device. The audio content acquisition module transmits the audio file to the hardware encoding module, the hardware encoding module extracts the key metadata of the audio content through the data extraction unit, and encrypts the metadata through the encryption processing unit. The encrypted metadata is transmitted to the identifier generation unit, which generates a unique identifier and embeds it in the audio content. The audio content with the embedded identifier is then transmitted to the decoding verification module, which verifies the legality of the audio content through a multi-level verification mechanism. If the verification is passed, the audio content is determined to be legal; otherwise, the audio content is determined to be illegal. Throughout the process, the cloud collaboration module communicates with the hardware device through network connection, providing remote support and secondary verification services to ensure the authenticity and security of the audio content.

[0036] Through the close cooperation and efficient collaboration of the above modules, the present application realizes the whole process operation of dynamic audio content binding and anti-counterfeiting verification. The connection relationship and position relationship between the modules are carefully designed to ensure efficient data flow transmission and accuracy of logical processing. At the same time, the mutual cooperation relationship between the modules is realized through special data channels and network interfaces to ensure the stability and reliability of the system.

[0037] In order to better enable relevant persons in the art to fully understand and implement the present application, the following further supplements the specific implementation principles of the present application in conjunction with a specific application scenario.

[0038] In the actual operation process of the voice blind box device, first, the audio content to be bound is obtained from the external storage device or the cloud server through the audio content acquisition module. The audio content acquisition module establishes a connection with the cloud server through the network interface and uses its internal data classification unit to perform multi-level classification processing on the received audio file. For example, the first level of classification classifies the files into music, voice or other categories according to the audio type; the second level of classification distinguishes different formats such as MP3, WAV, etc. according to the audio format; and the third level of classification further subdivides the audio use into entertainment, education or advertising, etc. This classification mechanism ensures that the audio content has been standardized before entering the hardware encoding module, thereby providing a clear data basis for subsequent operations.

[0039] Subsequently, the audio content is passed to the hardware encoding module for processing. The data extraction unit in the hardware encoding module is responsible for extracting key metadata from the audio content, such as timestamp, audio format, and sampling rate, etc. These metadata are passed to the encryption processing unit in a structured form, which uses the Advanced Encryption Standard (AES) algorithm to encrypt the metadata. The encrypted metadata are passed to the identifier generation unit, which generates an identifier unique to the hardware device through a hash function and embeds it in the audio content. This process is completed through the collaborative work of the hardware encoding module and the encryption processing module, ensuring the uniqueness and irreversibility of the identifier. For example, the hash function uses the SHA-256 algorithm to calculate the encrypted metadata and the encoding information of the hardware device to generate a fixed-length unique identifier. This identifier not only contains the key metadata of the audio content, but also combines the encoding information of the hardware device, ensuring its uniqueness and tamper resistance.

[0040] Next, the encryption processing module further processes the metadata of the audio content. The encryption processing module uses a symmetric encryption algorithm to encrypt the metadata, and combines the encoding information of the hardware device to generate the final unique identifier. The encryption processing module supports dynamic update function, which can adjust the encryption algorithm parameters in real time according to the instructions of the cloud collaborative module. For example, in a specific scenario, the cloud collaborative module sends instructions to the encryption processing module through the network interface, requiring to adjust the key length of the AES algorithm to adapt to higher security requirements. The encryption processing module and the identifier generation module communicate through a dedicated data link, ensuring that the encrypted data can be efficiently transmitted to the identifier generation module.

[0041] The task of the identifier generation module is to generate a unique identifier and embed it in the audio content. The identifier generation module receives data from the encryption processing module through a high-speed data channel, and generates a unique identifier using a hash function. For example, the identifier generation module uses the MD algorithm to process the data, generates a fixed-length identifier, and embeds it in the metadata area of the audio content. This process is completed through the collaborative work of the hardware encoding module and the encryption processing module, ensuring the uniqueness and irreversibility of the identifier.

[0042] The audio content embedded with the identifier is then passed to the decoding verification module for legitimacy verification. The decoding verification module completes this process through a multi-level verification mechanism. The preliminary verification stage checks the identifier of the audio content through a fast hash algorithm to ensure the basic legitimacy of the identifier. For example, the decoding verification module uses the CRC algorithm to quickly check the identifier, and if the check result is consistent with the preset value, it enters the deep verification stage. The deep verification stage combines the encoding information of the hardware device to perform a full comparison of the identifier, ensuring that the identifier is completely consistent with the encoding information of the hardware device. For example, the decoding verification module compares the unique code of the hardware device with the hardware information field in the identifier to determine whether they match. The final confirmation stage performs a second verification of the legitimacy of the audio content through the cloud collaboration module. For example, the decoding verification module sends the identifier and the encoding information of the hardware device to the cloud collaboration module through the network interface, and the verification processing unit in the cloud collaboration module judges the legitimacy of the audio content according to the preset rules and feeds back the verification result to the decoding verification module.

[0043] Throughout the process, the cloud collaboration module communicates with the hardware device through network connection, providing remote support and secondary verification services. The data storage unit in the cloud collaboration module is responsible for storing the metadata of the audio content and the encoding information of the hardware device, and the verification processing unit judges the legitimacy of the audio content according to the preset rules. For example, the verification processing unit compares the list of legal identifiers stored in the cloud with the received identifier to determine the legitimacy of the audio content. The cloud collaboration module also supports dynamic updating function, which can adjust the verification rules and parameters according to actual needs, thereby improving the flexibility and expandability of the system.

[0044] Through the close cooperation and efficient collaboration of the above modules, the voice blind box device realizes the whole process operation of dynamic audio content binding and anti-counterfeiting verification. For example, when the user starts the voice blind box device, the system downloads an audio file from the cloud server through the audio content acquisition module and processes it for classification. Then, the hardware encoding module extracts the key metadata of the audio file and generates a unique identifier through the encryption processing module. The identifier generation module embeds the identifier into the audio content, and the decoding verification module verifies the legitimacy of the audio content through a multi-level verification mechanism. If the verification is passed, the audio content is determined to be legal; otherwise, the audio content is determined to be illegal. Throughout the process, the cloud collaboration module communicates with the hardware device through network connection, providing remote support and secondary verification services, ensuring the authenticity and security of the audio content.

[0045] The contents not described in the specification are all the prior art known by the skilled in the art, and the model parameters of the electric appliances are not specifically limited, and the conventional equipment can be used. In the technical solution, the electric appliance control elements not mentioned belong to the prior art, and therefore are not shown in the drawings, and will not be described here.

[0046] Although the present application has been described in detail with reference to the foregoing embodiments, the skilled in the art can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part of the technical features, and any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A dynamic audio content binding and anti-counterfeiting verification method for voice blind box products, characterized in that: The method comprises the following steps: S01: obtaining the audio content to be bound from an external storage device or a cloud server through an audio content acquisition module; S02: extracting and processing the key metadata of the audio content using a hardware encoding module, wherein the hardware encoding module includes a data extraction unit, an encryption processing unit, and an identifier generation unit; S03: encrypting the key metadata using an advanced encryption standard algorithm through an encryption processing module; S04: generating an identifier corresponding uniquely to the hardware device using an identifier generation module and embedding the identifier into the audio content; S05: parsing the identifier in the audio content through a decoding verification module and comparing it with the encoding information of the hardware device to complete the legality verification; S06: receiving the identifier of the audio content and the encoding information of the hardware device through a cloud collaboration module and verifying their legality.

2. The dynamic audio content binding and anti-counterfeiting verification method for voice blind box products according to claim 1, characterized in that: The data extraction unit of the hardware encoding module extracts the timestamp, audio format, and sampling rate from the audio content as key metadata.

3. The dynamic audio content binding and anti-counterfeit verification method for voice blind box products according to claim 1, characterized in that: The encryption processing module uses a symmetric encryption algorithm to encrypt the key metadata and generates a final unique identifier in combination with the encoding information of the hardware device.

4. The dynamic audio content binding and anti-counterfeit verification method for voice blind box products according to claim 1, characterized in that: The identifier generation module generates an identifier corresponding uniquely to the hardware device through a hash function and embeds the identifier into the audio content.

5. The dynamic audio content binding and anti-counterfeit verification method for voice blind box products according to claim 1, characterized in that: The decoding verification module verifies the legality of the audio content through a multi-level verification mechanism, including three stages of preliminary verification, deep verification, and final confirmation.

6. The dynamic audio content binding and anti-counterfeit verification method for voice blind box products according to claim 5, characterized in that: The preliminary verification stage checks the identifier of the audio content through a fast hash algorithm, the deep verification stage conducts full comparison in combination with the encoding information of the hardware device, and the final confirmation stage conducts secondary verification of the legality of the audio content through the cloud collaboration module.

7. The dynamic audio content binding and anti-counterfeit verification method for voice blind box products according to claim 1, characterized in that: The audio content acquisition module further includes a data classification unit that classifies and stores the audio content according to its type, format, and purpose, and uses a one-level classification standard to distinguish audio types, a two-level classification standard to distinguish audio formats, and a three-level classification standard to distinguish audio purposes.

8. The dynamic audio content binding and anti-counterfeit verification method for voice blind box products according to claim 1, characterized in that: The hardware encoding module supports dynamic updating function and updates the encoding information of the hardware device in real time through the instructions received from the cloud collaboration module.

9. The dynamic audio content binding and anti-counterfeit verification method for voice blind box products according to claim 1, characterized in that: The cloud collaboration module includes a data storage unit and a verification processing unit, the data storage unit is used to store the metadata of the audio content and the encoding information of the hardware device, and the verification processing unit is used to judge the legality of the audio content according to the preset rules.

10. The dynamic audio content binding and anti-counterfeit verification method for voice blind box products according to claim 1, characterized in that: The decoding verification module is connected with the hardware encoding module and the cloud collaboration module through a bidirectional data channel to ensure efficient data transmission during the verification process.

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