Anonymous appeal reporting method and device, electronic equipment and storage medium

Abstract

The invention provides an anonymous appeal reporting method and device, electronic equipment and a storage medium, and relates to the technical field of communication. After a real mobile phone number of a user is obtained, an irreversibly encrypted anonymous identifier is generated based on the real mobile phone number and a dynamic parameter; and performing hash operation on an authorization protocol signed by a user and the generation information of the anonymous identifier to generate an authorization certificate and an anonymous identifier certificate, synchronizing the authorization certificate and the anonymous identifier certificate to a block chain certificate platform, accessing a number agent platform based on the anonymous identifier, dynamically binding a temporary number, and starting a voice processing service to establish anonymous call connection. And unbinding the temporary number after the call is ended, and synchronizing the call record and the unbinding state to the block chain evidence storage platform, so that the problems that in the prior art, the user privacy is easy to leak in the campus bullying appeal and report process, the subsequent dispute is difficult to arbitrate due to lack of a credible evidence storage mechanism, and the user experience is poor can be solved. And some anti-bullying technologies have the problems of false alarm, high implementation cost or incapability of realizing real-time appeal and report.

Description

Technical Field

[0001] This disclosure relates to the field of communication technology, and in particular to an anonymous complaint and reporting method and apparatus, electronic device and storage medium. Background Technology

[0002] Campus anti-bullying technology, as a crucial support in the field of educational safety, is widely applied in campus environment monitoring and behavioral intervention systems. With the development of mobile communication and artificial intelligence technologies, existing technologies, through the collaborative operation of acoustic sensors, visual analysis, and behavioral trajectory tracking, have constructed a comprehensive protection mechanism from risk identification to emergency response. Specifically, this technology system encompasses key aspects such as AI voice early warning, multimodal data fusion, and VR education. The AI ​​voice recognition system uses a sensitive word database and voiceprint algorithm to monitor abnormal behavior; the multimodal system integrates visual and emotion recognition technologies to build a comprehensive perception network; and the VR system enhances students' safety awareness through immersive scenarios. However, existing technologies, which directly employ traditional account systems or one-click login methods, lack an anonymous identification mechanism based on irreversible encryption, potentially leading to user privacy leaks. Specifically, AI voice recognition systems suffer from false alarms in noisy environments and require continuous recording and storage, raising privacy concerns; multimodal systems, due to the application of video surveillance and emotion recognition technologies, have deployment costs reaching hundreds of thousands of yuan and pose a risk of data misuse; while VR education systems have preventative value, they are limited by hardware dependence and scenario limitations, preventing dynamic monitoring and real-time intervention. Traditional anonymous identification technology lacks a collaborative mechanism with blockchain for evidence storage, which prevents authorization agreements and call records from forming a credible chain of evidence, thus affecting the legal validity of reported information. This technological limitation objectively condones the continued occurrence of school bullying. Summary of the Invention

[0003] This disclosure provides an anonymous complaint reporting method, apparatus, electronic device, and storage medium. Its main purpose is to at least partially address one of the technical problems in the related art.

[0004] According to the first aspect of this disclosure, an anonymous complaint and reporting method is provided, including: Obtain the user's real mobile phone number and generate an irreversibly encrypted anonymous identifier based on the real mobile phone number and dynamic parameters; The authorization agreement signed by the user is hashed with the information generated by the anonymous identifier to generate authorization certificate and anonymous identifier certificate, and the authorization certificate and anonymous identifier certificate are synchronized to the blockchain certificate platform. Based on the anonymous identifier access number proxy platform, a temporary number is dynamically bound and voice processing service is enabled to establish an anonymous call connection with the target hotline through the temporary number; After the call ends, the temporary number will be unbound, and the call record and unbinding status will be synchronized to the blockchain evidence storage platform.

[0005] Optional, dynamic parameters include device unique identifiers and business system identifiers; Anonymous identifiers that are irreversibly encrypted based on real mobile phone numbers and dynamic parameters include: A hash algorithm is used to encrypt the concatenated data of the real mobile phone number, the device's unique identifier, and the business system identifier, generating an irreversibly encrypted anonymous identifier.

[0006] Optionally, the generated information includes the timestamp of the anonymous identifier's generation and operator network parameters; The user-signed authorization agreement is hashed along with the information used to generate the anonymous identifier, including: Multiple hash operations are used to process the combined data of the authorization protocol text, generation timestamp, and operator network parameters, and a random disturbance factor is introduced during the operation.

[0007] Optionally, based on the anonymous identifier access number proxy platform, dynamically bind temporary numbers and enable voice processing services, including: Before binding a temporary number, verify the validity of anonymous identifier storage and authorized storage in the blockchain evidence storage platform; Upon successful verification, the anonymous identifier is bound to the temporary number, and the voice processing service is enabled. The voice processing service transforms the user's voice characteristics by adjusting the voice frequency and performing filtering.

[0008] Optionally, call records and unbinding status can be synchronized to a blockchain-based evidence storage platform, including: In response to the unbinding of the temporary number after the call ends, the unbinding status is obtained. The unbinding status includes the unbinding timestamp and the status code, where the difference between the unbinding timestamp and the call start timestamp meets a preset threshold. A hash algorithm is used to process the information contained in the call records to generate a digest value for evidence storage. The call records include temporary numbers, target hotline numbers, and call duration.

[0009] Optional, also includes: The risk verification module assists in the analysis of voice data from anonymous complaints and reports. The risk verification module calculates a comprehensive risk score based on the similarity of voice features and the matching degree of user behavior patterns.

[0010] According to a second aspect of this disclosure, an anonymous complaint and whistleblowing device is provided, comprising: The generation unit is used to obtain the user's real mobile phone number and generate an irreversibly encrypted anonymous identifier based on the real mobile phone number and dynamic parameters; The processing unit is used to perform hash operations on the authorization agreement signed by the user and the generation information of the anonymous identifier to generate authorization certificate and anonymous identifier certificate, and synchronize the authorization certificate and anonymous identifier certificate to the blockchain certificate platform. The binding unit is used to access the number agent platform based on anonymous identifiers, dynamically bind temporary numbers and enable voice processing services, and establish anonymous call connections with target hotlines through temporary numbers. The synchronization unit is used to unbind the temporary number after the call ends and synchronize the call record and unbinding status to the blockchain evidence storage platform.

[0011] Optional, dynamic parameters include device unique identifiers and business system identifiers; The generation unit is also used for: A hash algorithm is used to encrypt the concatenated data of the real mobile phone number, the device's unique identifier, and the business system identifier, generating an irreversibly encrypted anonymous identifier.

[0012] Optionally, the generated information includes the timestamp of the anonymous identifier's generation and operator network parameters; The arithmetic unit is also used for: Multiple hash operations are used to process the combined data of the authorization protocol text, generation timestamp, and operator network parameters, and a random disturbance factor is introduced during the operation.

[0013] Optionally, the binding unit is also used for: Before binding a temporary number, verify the validity of anonymous identifier storage and authorized storage in the blockchain evidence storage platform; Upon successful verification, the anonymous identifier is bound to the temporary number, and the voice processing service is enabled. The voice processing service transforms the user's voice characteristics by adjusting the voice frequency and performing filtering.

[0014] Optionally, the synchronization unit is also used for: In response to the unbinding of the temporary number after the call ends, the unbinding status is obtained. The unbinding status includes the unbinding timestamp and the status code, where the difference between the unbinding timestamp and the call start timestamp meets a preset threshold. A hash algorithm is used to process the information contained in the call records to generate a digest value for evidence storage. The call records include temporary numbers, target hotline numbers, and call duration.

[0015] Optional, also includes: The analysis unit is used to assist in the analysis of voice data from anonymous complaints and reports through the risk verification module. The risk verification module calculates a comprehensive risk score based on voice feature similarity and user behavior pattern matching.

[0016] According to a third aspect of this disclosure, an electronic device is provided, comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect above.

[0017] According to a fourth aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions, wherein the computer instructions are configured to cause the computer to perform the method described in the first aspect above.

[0018] According to a fifth aspect of this disclosure, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the method described in the first aspect above.

[0019] The anonymous complaint and reporting method, device, electronic device, and storage medium disclosed herein obtain a user's real mobile phone number and generate an irreversible encrypted anonymous identifier based on the real mobile phone number and dynamic parameters. The user-signed authorization agreement and the generation information of the anonymous identifier are hashed to generate authorization and anonymous identifier evidence, which is then synchronized to a blockchain evidence platform. Based on the anonymous identifier, a temporary number is dynamically bound to an access number proxy platform, and voice processing services are enabled to establish an anonymous call connection. After the call ends, the temporary number is unbound, and the call record and unbinding status are synchronized to the blockchain evidence platform. Therefore, this method solves the problems of existing technologies where user privacy is easily leaked during campus anti-bullying complaint and reporting, users are reluctant to report due to fear of retaliation after their identity is exposed, and the lack of a reliable evidence storage mechanism makes subsequent disputes difficult to arbitrate. Furthermore, some anti-bullying technologies suffer from false alarms, high implementation costs, or the inability to achieve real-time complaint and reporting. This method achieves anonymous and real-time complaint and reporting in campus anti-bullying scenarios while fully protecting user privacy and eliminating psychological pressure on users to file complaints and reports. Simultaneously, blockchain evidence storage provides reliable evidence for potential disputes, effectively promoting the early detection and prevention of bullying.

[0020] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0021] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein: Figure 1 A flowchart illustrating an anonymous complaint / reporting method provided in this embodiment of the disclosure; Figure 2This is a schematic diagram of the structure of an anonymous complaint and reporting device provided in an embodiment of this disclosure; Figure 3 A schematic block diagram of an example electronic device provided for embodiments of this disclosure. Detailed Implementation

[0022] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0023] The following description, with reference to the accompanying drawings, outlines an anonymous complaint reporting method, apparatus, electronic device, and storage medium according to embodiments of this disclosure.

[0024] Figure 1 This is a flowchart illustrating an anonymous complaint / reporting method provided in an embodiment of this disclosure.

[0025] like Figure 1 As shown, the method includes the following steps: Step 101: Obtain the user's real mobile phone number and generate an irreversibly encrypted anonymous identifier based on the real mobile phone number and dynamic parameters.

[0026] In this embodiment, in technical scenarios requiring anonymous interaction, to balance trusted user identity association with privacy protection, the user's real mobile phone number is first obtained to establish the identity foundation. This real mobile phone number serves as the core association information for generating anonymous identifiers, ensuring a unique correspondence between the anonymous identifier and the user without directly exposing the user's real identity. Subsequently, combined with dynamically changing parameters (the dynamic parameters can be set according to actual business needs to improve the uniqueness and unpredictability of the anonymous identifier), an encryption algorithm with irreversible operation characteristics is used to process the combined data of the real mobile phone number and dynamic parameters to generate an anonymous identifier for subsequent anonymous interaction. This irreversible encryption algorithm avoids the reverse derivation of the user's real mobile phone number through the generated anonymous identifier, thereby achieving privacy isolation while establishing the association between the identifier and the user. As one implementation method, in the scenario of anonymous appeals and reports against campus bullying, the user's real mobile phone number can be obtained through the number retrieval capability provided by the operator. The dynamic parameters may include the timestamp when the identifier is generated, control data that distinguishes different business scenarios, etc. A digest-type irreversible encryption algorithm (such as the MD5 algorithm) is used to operate on the combined data of the real mobile phone number and the above dynamic parameters to generate an anonymous identifier (such as UAID) for this scenario.

[0027] This technical approach preserves the indirect link between the user's real identity and the anonymous identifier while preventing the risk of the anonymous identifier being reverse-engineered to obtain the real phone number through irreversible encryption. It provides reliable identifier support for subsequent anonymous interactions and fundamentally avoids the leakage of the user's real identity information, effectively eliminating the user's concerns about identity exposure and providing a basic guarantee for the security and privacy protection of interactions in anonymous scenarios.

[0028] Step 102: Perform a hash operation on the authorization agreement signed by the user and the generation information of the anonymous identifier to generate authorization certificate and anonymous identifier certificate, and synchronize the authorization certificate and anonymous identifier certificate to the blockchain certificate platform.

[0029] In this embodiment, to ensure the legitimacy of user authorization and the traceability of the anonymous identifier generation process during anonymous interaction, hash operations are performed on the user-signed authorization agreement (which provides the legal basis for subsequent anonymous operations and clarifies the scope of the user's authorization for anonymous services) and the anonymous identifier generation information (including associated parameters and generation time when the anonymous identifier is generated, used to verify the authenticity and uniqueness of the anonymous identifier's source). The hash operation ensures the integrity and immutability of the data after processing, thereby generating an authorization certificate corresponding to the authorization agreement and an anonymous identifier certificate corresponding to the anonymous identifier generation information. Subsequently, these two types of certificates are synchronized to a blockchain-based evidence storage platform. Utilizing the decentralized and tamper-proof characteristics of blockchain, long-term secure storage and reliable traceability of the evidence information are achieved. As one implementation method, in the scenario of anonymous appeal and reporting of campus bullying, the anonymous appeal and reporting authorization agreement text signed by the user can be subjected to MD5 hash operation to obtain authorization evidence, and the anonymous identifier (such as UAID) and the data string composed of its generation time can be subjected to MD5 hash operation to obtain anonymous identifier evidence. The two types of evidence are synchronized to the blockchain authorization evidence platform to provide a basis for possible authorization query or dispute arbitration in the future.

[0030] By ensuring the integrity of the authorization agreement and the generated anonymous identifier through hash calculation, and combined with the immutability of the blockchain evidence storage platform, the legality of the user's authorization and the validity of the generated anonymous identifier are effectively proven. This also avoids the risk of the evidence storage information being tampered with or lost. It provides authoritative and credible evidence for any disputes that may arise in the subsequent anonymous interaction process (such as the identification of malicious reports), and further strengthens the legal compliance and technical credibility of the anonymous service.

[0031] Step 103: Access the number agent platform based on the anonymous identifier, dynamically bind the temporary number and enable the voice processing service, and establish an anonymous call connection with the target hotline through the temporary number.

[0032] In this embodiment, in anonymous interaction scenarios, to achieve privacy isolation and legitimate connection at the call level, an anonymous identifier is generated to access a number proxy platform (which has the capability to allocate, bind, and manage temporary numbers, and can provide a communication medium not directly associated with the user's real number). After identity verification is completed through the anonymous identifier, the number proxy platform dynamically allocates and binds a temporary number. This temporary number serves as an intermediary medium for communication between the user and the target hotline, preventing the direct exposure of the user's real number. Simultaneously, a voice processing service is enabled (this service can process the characteristics of the call voice, reducing the risk of identity recognition due to personal voice characteristics). Finally, using the temporary number as the communication carrier, an anonymous call connection is established with the target hotline (i.e., the designated communication terminal receiving anonymous information or requests), ensuring that the user's identity information is not obtained by the target hotline during the call. As one implementation method, in the scenario of anonymous appeals and reports against campus bullying, the number proxy platform can be an operator's intermediate number platform, the temporary number can be an X number allocated by the platform, the voice processing service can be a voice changing service, and the target hotline can be set as the anti-bullying hotline of the target school. A call is established with this hotline through the X number to complete the anonymous appeal and report.

[0033] By isolating users' real communication information with temporary numbers and further shielding personal identity features with voice processing services, while ensuring the legitimacy of access with anonymous identifiers, this approach not only achieves an effective communication connection between users and the target hotline, but also eliminates the risk of identity leakage from both the communication carrier and voice characteristics perspectives. It completely eliminates users' concerns about not being willing to initiate anonymous interactions due to fear of identity exposure, and provides secure and reliable technical support for real-time communication needs in anonymous scenarios.

[0034] Step 104: After the call ends, unbind the temporary number and synchronize the call record and unbinding status to the blockchain evidence storage platform.

[0035] In this embodiment, after an anonymous call is completed using a temporary number, to avoid privacy risks due to the temporary number being continuously associated with user information, the association between the temporary number and the user's anonymous identifier and real communication information must be terminated promptly after the call ends. This means completing the unbinding operation of the temporary number to ensure that it will not be used again to associate with any anonymous interaction scenario of the current user, thus eliminating the risk of identity tracing due to number reuse or residual association. At the same time, to achieve traceability and data integrity throughout the anonymous interaction process, the call records generated during this anonymous call (including key information that can characterize the validity of the call, such as call time and call duration) and the unbinding status information of the temporary number must be synchronized to the blockchain evidence storage platform. By utilizing the decentralized and tamper-proof core characteristics of blockchain technology, the key data in this step is securely stored and solidified to form a complete chain of anonymous interaction evidence. As one implementation method, in the scenario of anonymous appeal and reporting of campus bullying, after the call ends, the previously bound X number can be unbound from the operator's intermediate number platform, and then the call record of this anonymous appeal and report (such as the start and end time of the call) and the unbinding status of the X number can be synchronized to the blockchain authorized evidence storage platform to complete the final data storage of this appeal and report process.

[0036] By promptly unbinding the temporary number after a call, the association between the temporary number and the user is completely severed, avoiding privacy and security risks caused by number abuse. At the same time, the call record and unbinding status are synchronized to the blockchain for evidence storage, completing the evidence chain of the entire anonymous interaction process. This not only ensures the immutability and traceability of the data, but also provides credible data support for any subsequent disputes (such as verification of complaint content and confirmation of the validity of the unbinding operation), further improving the security and compliance of the anonymous service.

[0037] The anonymous complaint and reporting method disclosed herein obtains the user's real mobile phone number and generates an irreversible encrypted anonymous identifier based on the real mobile phone number and dynamic parameters. The user-signed authorization agreement and the generated information of the anonymous identifier are hashed to generate authorization and anonymous identifier evidence, which are then synchronized to a blockchain evidence platform. Based on the anonymous identifier, a temporary number is dynamically bound to a number proxy platform, and voice processing services are enabled to establish an anonymous call connection. After the call ends, the temporary number is unbound, and the call record and unbinding status are synchronized to the blockchain evidence platform. Therefore, this method can solve the problems of existing technologies where user privacy is easily leaked during campus anti-bullying complaint and reporting, users are reluctant to report due to fear of retaliation for identity exposure, and the lack of a reliable evidence storage mechanism makes subsequent disputes difficult to arbitrate. Furthermore, some anti-bullying technologies suffer from false alarms, high implementation costs, or the inability to achieve real-time complaint and reporting. This method achieves anonymous and real-time complaint and reporting in campus anti-bullying scenarios while fully protecting user privacy and eliminating the psychological pressure on users to file complaints and reports. Simultaneously, blockchain evidence storage provides reliable evidence for potential disputes, effectively promoting the early detection and prevention of bullying.

[0038] Within the technical framework disclosed in step 101, the dynamic parameters include a unique device identifier and a business system identifier; generating an irreversibly encrypted anonymous identifier based on the real mobile phone number and dynamic parameters can be further specified as follows: using a hash algorithm to perform encryption calculation on the concatenated data of the real mobile phone number, the unique device identifier, and the business system identifier to generate an irreversibly encrypted anonymous identifier.

[0039] Specifically, within the technical framework of storing monitoring configuration information in step 101 mentioned above, the configuration of dynamic parameters and the generation of anonymous identifiers are implemented as follows: First, the device unique identifier and the business system identifier are used as supplementary attributes of the monitoring configuration information and stored together with the target server identifier, monitoring component type, and corresponding attribute parameters. The device unique identifier uses the hardware unique identifier of the target server, such as the server motherboard UUID (e.g., "550e8400-e29b-41d4-a716-446655440000") or the network card MAC address (e.g., "00:1B:44:11:3A:B7"), to ensure that it can uniquely associate with the monitored device. The business system identifier uses the exclusive code of the business deployed on the target server, such as "ORDER_SYS_001" when deploying e-commerce order business and "LOGISTICS_SYS_002" when deploying logistics scheduling business, to achieve precise binding between monitoring data and business scenarios. Next, the anonymous identifier generation process is executed: First, the real mobile phone number to be processed (e.g., "138XXXX1234") is obtained, and concatenated into a complete string (e.g., "138XXXX1234550e8400 - e29b - 41d4 - a716- 446655440000ORDER_SYS_001") according to a preset fixed order (e.g., "real mobile phone number + device unique identifier + business system identifier"). Then, a hash calculation tool in the Linux environment (e.g., openssl) is called to perform encryption operation on the concatenated string using the SHA-256 hash algorithm to generate a fixed-length, irreversible hash value. This hash value is the anonymous identifier of the target associated entity. Finally, the anonymous identifier is associated with and stored with the monitoring configuration information of the corresponding target server for locating the associated entity when tracing monitoring data in the future, while avoiding direct exposure of the real mobile phone number.

[0040] The concatenated data of real mobile phone number and dynamic parameters is encrypted by hash algorithm. The irreversible nature of hash algorithm effectively eliminates the risk of real mobile phone number being cracked, thus protecting user privacy and security. The device unique identifier and business system identifier are included in the encryption dimension, so that the anonymous identifier can accurately correspond to specific devices and business scenarios, avoiding the confusion of identifiers between different monitored objects. Moreover, the whole process is realized by relying on the monitoring configuration information storage system in step 101, without the need to build an additional independent storage structure, which reduces the complexity of system deployment and maintenance.

[0041] Within the technical framework disclosed in step 102, the generated information includes the generation timestamp of the anonymous identifier and the operator network parameters; the hash operation of the user-signed authorization agreement and the generation information of the anonymous identifier can be further specified as follows: multiple hash operations are performed on the combined data of the authorization agreement text, the generation timestamp and the operator network parameters, and a random disturbance factor is introduced during the operation.

[0042] Specifically, within the technical framework of dynamically generating executable collection scripts based on monitoring configuration information in step 102, the acquisition and hash operation processing of relevant generated information are implemented as follows: First, the "generation timestamp of the anonymous identifier" in the generated information is obtained by a lightweight program on the target server (such as the auxiliary logic associated with the watchdog script) calling the Linux system's `date +%s%3N` command when generating the anonymous identifier to obtain a timestamp accurate to the millisecond level (e.g., "1740960825123"). This timestamp corresponds one-to-one with the anonymous identifier and is used to record the creation sequence of the anonymous identifier; the "carrier network parameters" are obtained through Linux system network tools, such as executing `ip route show` to extract the carrier gateway IP (e.g., "10.150.20.1"), executing `cat`... ` / etc / resolv.conf` retrieves the ISP's DNS server address (e.g., "202.97.224.68"), and combines these parameters into a string format "Gateway IP:10.150.20.1;DNS:202.97.224.68", which serves as the specific content of the ISP's network parameters.

[0043] Next, the system processes the hash operation of the user-signed authorization agreement and the generated information: First, it obtains the signed authorization agreement text (e.g., "The user authorizes this system to collect application service monitoring data from the target server, with the authorization period from 2025-01-01 to 2026-01-01; data collection beyond the authorized scope is invalid"). Then, it concatenates this data into a combined data string in a fixed order of "authorization agreement text + generation timestamp + operator network parameters" (e.g., "The user authorizes this system... 2026-01-01|1740960825123|gateway IP:10.150.20.1;DNS:202.97.224.68"). Following this, it performs the first hash operation, calling the `sha256sum` tool in the Linux environment to encrypt the combined data string, obtaining the first hash result. Finally, it reads the Linux system's ` / dev / urandom` device file (e.g., `head -c 32 / dev / urandom | ...`). A 32-bit random perturbation factor is generated using base64. The first hash result is concatenated with the random perturbation factor, and a second `sha256sum` hash operation is performed to obtain the final irreversible hash value. Finally, the final hash value, the random perturbation factor, and the corresponding anonymous identifier are associated and stored, and recorded synchronously with the generation logic of the executable collection script to ensure the relevance of the subsequent traceable authorization agreement and the generated information.

[0044] By processing combined data through multiple hash operations, the anti-cracking capability of the data is greatly improved compared to a single hash, effectively preventing the authorization protocol and generation information from being reverse-engineered. The introduction of a random perturbation factor further avoids the risk of collisions where the same combination of data generates the same hash value, ensuring data uniqueness. At the same time, binding the authorization protocol and the anonymous identifier generation information to hash ensures the compliance and traceability of user authorization, while avoiding the direct exposure of the original authorization protocol and sensitive network parameters, thus balancing compliance and data security.

[0045] Within the technical framework disclosed in step 103, the method of dynamically binding a temporary number and enabling voice processing service based on the anonymous identifier access number proxy platform can be further specified as follows: before binding the temporary number, verify the validity of the anonymous identifier storage and authorization storage in the blockchain storage platform; in response to the successful verification, bind the anonymous identifier with the temporary number and enable the voice processing service, which transforms the user's voice characteristics by adjusting the voice frequency and filtering.

[0046] Specifically, within the technical framework of executing the executable collection script and reporting monitoring data in step 103, the specific process of accessing the number agent platform based on the anonymous identifier and completing the temporary number binding and voice processing service activation is as follows: First, before initiating the temporary number binding request, the system accesses the blockchain evidence storage platform through a preset API interface. This interface needs to carry the anonymous identifier to be verified (such as the irreversible hash value generated in steps 101-102) and the corresponding request identifier. After receiving the request, the blockchain evidence storage platform first retrieves the evidence storage record matching the anonymous identifier (i.e., anonymous identifier evidence storage, including the hash value and creation time when the anonymous identifier was generated), and then queries the corresponding authorized evidence storage (such as the hash evidence storage generated after the user signs the authorization agreement, including the authorization validity period and authorization scope). By calling the platform's built-in verification logic (such as comparing the anonymous identifier hash in the request with the evidence storage hash, and checking whether the authorized evidence storage is in a "valid" state and has not expired), the validity of the two types of evidence storage is determined.

[0047] After the blockchain evidence storage platform returns a "verification passed" result, the system uses the anonymous identifier as the unique identity credential and accesses the dynamic binding interface of the number agent platform via HTTPS protocol. The interface request carries the anonymous identifier and the verified evidence storage credential (such as the transaction ID of the blockchain evidence storage). After verifying the legality of the credential, the number agent platform allocates an unused temporary number (such as "170XXXX5678") from the temporary number resource pool (maintained by the number management service based on the Linux system) and establishes a "anonymous identifier-temporary number" mapping relationship in the platform database to complete the dynamic binding. At the same time, it returns a notification of successful binding and the validity period of the temporary number (such as 24 hours).

[0048] Subsequently, the system activates the speech processing service, which is deployed in a Linux environment and relies on the FFmpeg audio processing tool and Python audio processing libraries (such as librosa) to achieve its functions: First, the system acquires the user's original speech data through the audio acquisition module (sampling rate set to 16kHz, bit depth 16bit), and then transforms the speech fundamental frequency through the frequency adjustment module (for example, shifting the original speech fundamental frequency by 12% within the 200-300Hz range to ensure that the transformed speech still conforms to human hearing habits but cannot trace the original features); then, the Butterworth low-pass filtering algorithm is used to filter the adjusted speech to remove high-frequency noise above 8kHz, and at the same time, frequency domain masking technology is used to slightly perturb the characteristic frequency bands in the speech spectrum (such as the formant frequencies reflecting personal voiceprints); finally, the transformed speech data is output, ensuring that the speech processing service completely hides the user's original speech features without affecting speech intelligibility.

[0049] By verifying the validity of anonymous identifiers and authorizations through a blockchain-based evidence storage platform, it is ensured that temporary number binding operations are based on legitimate and compliant identities and authorizations, eliminating the risk of number resource abuse or privacy leaks caused by unauthorized binding. The dynamic binding of anonymous identifiers and temporary numbers avoids the direct exposure of real numbers, protecting user communication privacy. The voice processing service transforms voice characteristics through frequency adjustment and filtering, further severing the association between voice data and the user's real identity, forming a three-layer privacy protection mechanism of "identity-number-voice," significantly improving the security of user data during application service monitoring.

[0050] Under the technical solution framework disclosed in step 104, synchronizing the call record and unbinding status to the blockchain evidence storage platform can be further specified as follows: in response to unbinding the temporary number after the call ends, the unbinding status is obtained, which includes an unbinding timestamp and a status code, wherein the difference between the unbinding timestamp and the call start timestamp meets a preset threshold; a digest value is generated by performing a hash algorithm on the information contained in the call record for evidence storage, wherein the call record includes the temporary number, the target hotline number, and the call duration.

[0051] Specifically, within the technical framework of step 104, the specific operation process for synchronizing call records and unbinding status to the blockchain evidence storage platform is as follows: First, in response to the call end event, the system triggers the temporary number unbinding logic—by accessing the unbinding interface of the number agent platform, carrying the bound temporary number (such as "170XXXX5678") and the corresponding anonymous identifier, a request is made to perform the unbinding operation; after the unbinding operation is completed, the system extracts the unbinding status from the result returned by the number agent platform. This status contains two core pieces of information: one is through the Linux system `date` The +%s%3N command obtains a millisecond-precise unbinding timestamp (e.g., "1740961250345"). It also provides a status code representing the unbinding result (e.g., "200" for successful unbinding, "500" for unbinding failure, and "404" for the temporary number not existing). Simultaneously, the system verifies the difference between the unbinding timestamp and the call start timestamp (obtained using the same `date` command when the call is initiated, e.g., "1740961200123") to ensure that this difference meets a preset threshold (e.g., a threshold set to "3600000" milliseconds, or 1 hour, to avoid anomalies caused by unbinding exceeding the time limit or premature unbinding).

[0052] Next, the system extracts key record information from this call: including the unbound temporary number, the target hotline number dialed by the user (e.g., "400XXXX8888"), and the call duration obtained through the call duration statistics module (based on the Linux system's `time` tool or audio recording duration calculation) (e.g., "120" seconds, or 2 minutes). This information is then concatenated into a string using the fixed order of "temporary number + target hotline number + call duration" (e.g., "170XXXX5678400XXXX8888120"). Subsequently, it calls `openssl` in the Linux environment. The `sha256sum` tool performs a SHA-256 hash operation on the concatenated string, generating a fixed-length irreversible digest value (e.g., "c2d3e4f5a6b7c8d9e0f1a2b3c4d5e6f7a8b9c0d1e2f3a4b5c6d7e8f9a0b1c2d3"). This digest value is used as the core evidence data for call records, preventing the original call information from being directly exposed.

[0053] Finally, the system initiates a notarization request to the blockchain notarization platform through a pre-defined blockchain notarization API interface. The request parameters include: unbinding status (unbinding timestamp, status code), hash digest value of the call record, corresponding anonymous identifier, and notarization timestamp (obtained synchronously with the unbinding timestamp). After receiving the request, the blockchain notarization platform verifies the legality of the parameters (such as the digest value format and the validity of the anonymous identifier), writes the data into a blockchain block, and generates a unique notarization transaction ID (such as "block-20250802-10001"). At the same time, it returns a response indicating successful notarization. The system associates and stores this transaction ID with the corresponding call record and unbinding status, facilitating subsequent querying of blockchain notarization information by transaction ID and completing the entire synchronization process.

[0054] By verifying the difference between the unbinding timestamp and the call start timestamp, the correlation between the unbinding operation and the call behavior can be ensured, avoiding abnormal scenarios such as "unbinding without a call" or "unbinding before the call ended," thus ensuring the integrity of the business process. A hash algorithm is used to generate a digest value for the call records for notarization. This avoids the privacy risks caused by directly storing sensitive information such as the original phone number in the blockchain, and relies on the uniqueness and irreversibility of the hash value to ensure that the call records are not tampered with. The data is synchronized to the blockchain notarization platform, leveraging the decentralized and immutable characteristics of blockchain to provide credible evidence for call records and unbinding status. Subsequent traceability can be quickly achieved through the transaction ID, enhancing the credibility and traceability of the data.

[0055] Within the technical framework disclosed in the foregoing embodiments, this application embodiment further includes: using a risk verification module to perform auxiliary analysis on the voice data of anonymous complaints and reports, and the risk verification module calculates a comprehensive risk score based on voice feature similarity and user behavior pattern matching degree.

[0056] Specifically, within the technical framework of the aforementioned embodiments, the specific process for assisting in the analysis of anonymous complaint and report voice data through the risk verification module is implemented based on the Linux system environment and the existing monitoring data system, as follows: First, the risk verification module is deployed on a Linux server and establishes a data interaction channel with the data collection module and the time-series database. The module first receives the voice data submitted by the anonymous complaint and report (in WAV or MP3 format, with a sampling rate of 16kHz and a bit depth of 16bit, compatible with the output format of the aforementioned voice processing service). At the same time, it obtains the anonymous identifier associated with the anonymous complaint from the data collection module (used to associate with historical monitoring data), and retrieves the historical user behavior data corresponding to the anonymous identifier from the time-series database (such as the initiation time, frequency, type of reported object, and historical voice processing records of past complaints and reports, all of which are time-series data already stored in the aforementioned monitoring process).

[0057] For speech feature similarity calculation: The module calls the FFmpeg tool in the Linux environment to preprocess the received speech data (removing background noise, using the Butterworth filtering algorithm, consistent with the filtering logic of the aforementioned speech processing service), and then extracts speech feature parameters (including Mel-frequency cepstral coefficients MFCC, speech fundamental frequency F0, formant frequencies, etc., matching the basic parameter dimensions of feature transformation in the speech processing service) through the librosa audio processing library; then it retrieves the speech feature library of the anonymous identifier's historical complaints and reports from the time-series database (feature data stored after processing by the aforementioned speech processing service), and uses the cosine similarity algorithm to calculate the similarity value between the current speech feature and the historical features (the value ranges from 0 to 1, with 1 representing a complete match). If the anonymous identifier has no historical speech records, the similarity value is temporarily set to 0.5.

[0058] For calculating the matching degree of user behavior patterns: The module first defines the behavioral pattern dimensions (including the distribution of complaint and report initiation time, initiation frequency (e.g., number of times in the last 30 days), the business system type of the reported object (e.g., MySQL service failure report, Tomcat log anomaly report, associated with the monitoring component type in step 101), and the keyword matching degree of the complaint content). It extracts and quantifies the historical behavior data of the anonymous identifier from the time series database (e.g., the overlap between the initiation time and the historical time is set to 0-1 points, the deviation of the frequency from the mean is set to 0-1 points, the matching of the business system type is set to 0-1 points, and the matching of keywords is set to 0-1 points). The weighted Euclidean distance algorithm is used to calculate the matching degree value between the current behavior and the historical behavior pattern (the value range is 0-1, where 1 represents a high degree of consistency in behavior). The weight allocation is set according to the business priority (e.g., the weight of frequency and business system type is 0.3 each, and the weight of time period and keyword is 0.2 each).

[0059] Finally, the module calculates a comprehensive risk score according to preset weights: the voice feature similarity weight is set to 0.6, and the user behavior pattern matching weight is set to 0.4. The final score (range 0-1) is obtained by the formula "Comprehensive Risk Score = Voice Feature Similarity × 0.6 + User Behavior Pattern Matching × 0.4". A scoring threshold is set (e.g., 0.7 is low risk, 0.5-0.7 is medium risk, and below 0.5 is high risk). The scoring results and calculation basis are synchronized to the data collection module to help determine the authenticity and risk level of the complaint.

[0060] It should be noted that the embodiments of this disclosure may include multiple steps. For ease of description, these steps are numbered, but these numbers are not a limitation on the execution time slots or execution order between the steps; these steps can be implemented in any order, and the embodiments of this disclosure do not limit this.

[0061] Corresponding to the aforementioned anonymous complaint and reporting method, this disclosure also proposes an anonymous complaint and reporting device. Since the device embodiment of this disclosure corresponds to the aforementioned method embodiment, details not disclosed in the device embodiment can be referred to the aforementioned method embodiment, and will not be repeated here.

[0062] Figure 2 This is a schematic diagram of the structure of an anonymous complaint and reporting device provided in an embodiment of this disclosure, as shown below. Figure 2 As shown, it includes: The generation unit 21 is used to obtain the user's real mobile phone number and generate an irreversibly encrypted anonymous identifier based on the real mobile phone number and dynamic parameters. The operation unit 22 is used to perform a hash operation on the authorization agreement signed by the user and the generation information of the anonymous identifier to generate authorization certificate and anonymous identifier certificate, and synchronize the authorization certificate and anonymous identifier certificate to the blockchain certificate platform. Binding unit 23 is used to access the number agent platform based on anonymous identifiers, dynamically bind temporary numbers and enable voice processing services, and establish anonymous call connections with target hotlines through temporary numbers; Synchronization unit 24 is used to unbind the temporary number after the call ends and synchronize the call record and unbinding status to the blockchain evidence storage platform.

[0063] The anonymous complaint and reporting device disclosed herein obtains the user's real mobile phone number and generates an irreversible encrypted anonymous identifier based on the real mobile phone number and dynamic parameters. It then performs a hash operation on the user-signed authorization agreement and the generated information of the anonymous identifier to generate authorization and anonymous identifier evidence, which is synchronized to a blockchain evidence platform. Based on the anonymous identifier, it accesses a number proxy platform to dynamically bind a temporary number and enables voice processing services to establish an anonymous call connection. After the call ends, it unbinds the temporary number and synchronizes the call record and unbinding status to the blockchain evidence platform. Therefore, it can solve the problems in existing technologies where user privacy is easily leaked during campus anti-bullying complaint and reporting, users are reluctant to report due to fear of retaliation after their identity is exposed, and the lack of a reliable evidence storage mechanism makes subsequent disputes difficult to arbitrate. Furthermore, some anti-bullying technologies suffer from false alarms, high implementation costs, or the inability to achieve real-time complaint and reporting. This device achieves anonymous and real-time complaint and reporting in campus anti-bullying scenarios while fully protecting user privacy and eliminating the psychological pressure of users to file complaints and reports. Simultaneously, it provides reliable evidence for potential disputes through blockchain evidence storage, effectively promoting the early detection and prevention of bullying.

[0064] Furthermore, in one possible implementation of this embodiment, the dynamic parameters include a device unique identifier and a business system identifier; The generating unit 21 is also used for: A hash algorithm is used to encrypt the concatenated data of the real mobile phone number, the device's unique identifier, and the business system identifier, generating an irreversibly encrypted anonymous identifier.

[0065] Furthermore, in one possible implementation of this embodiment, the generated information includes the generation timestamp of the anonymous identifier and operator network parameters; The arithmetic unit 22 is also used for: Multiple hash operations are used to process the combined data of the authorization protocol text, generation timestamp, and operator network parameters, and a random disturbance factor is introduced during the operation.

[0066] Furthermore, in one possible implementation of this embodiment, the binding unit 23 is also used for: Before binding a temporary number, verify the validity of anonymous identifier storage and authorized storage in the blockchain evidence storage platform; Upon successful verification, the anonymous identifier is bound to the temporary number, and the voice processing service is enabled. The voice processing service transforms the user's voice characteristics by adjusting the voice frequency and performing filtering.

[0067] Furthermore, in one possible implementation of this embodiment, the synchronization unit 24 is also used for: In response to the unbinding of the temporary number after the call ends, the unbinding status is obtained. The unbinding status includes the unbinding timestamp and the status code, where the difference between the unbinding timestamp and the call start timestamp meets a preset threshold. A hash algorithm is used to process the information contained in the call records to generate a digest value for evidence storage. The call records include temporary numbers, target hotline numbers, and call duration.

[0068] Furthermore, in one possible implementation of this embodiment, such as Figure 2 As shown, it also includes: Analysis unit 25 is used to assist in the analysis of voice data of anonymous complaints and reports through the risk verification module. The risk verification module calculates a comprehensive risk score based on voice feature similarity and user behavior pattern matching degree.

[0069] It should be noted that the foregoing explanation of the method embodiments also applies to the apparatus of this embodiment, and the principle is the same, so it is not limited in this embodiment.

[0070] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0071] Figure 3 A schematic block diagram of an example electronic device 300 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0072] like Figure 3 As shown, the electronic device 300 includes a computing unit 301, which can perform various appropriate actions and processes based on a computer program stored in ROM (Read-Only Memory) 302 or a computer program loaded from storage unit 308 into RAM (Random Access Memory) 303. The RAM 303 may also store various programs and data required for the operation of the electronic device 300. The computing unit 301, ROM 302, and RAM 303 are interconnected via a bus 304. An I / O (Input / Output) interface 305 is also connected to the bus 304.

[0073] Multiple components in electronic device 300 are connected to I / O interface 305, including: input unit 306, such as keyboard, mouse, etc.; output unit 307, such as various types of displays, speakers, etc.; storage unit 308, such as disk, optical disk, etc.; and communication unit 309, such as network card, modem, wireless transceiver, etc. Communication unit 309 allows electronic device 300 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0074] The computing unit 301 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, CPUs (Central Processing Units), GPUs (Graphics Processing Units), various special-purpose AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, DSPs (Digital Signal Processors), and any suitable processor, controller, microcontroller, etc. The computing unit 301 performs the various methods and processes described above, such as anonymous complaint reporting methods. For example, in some embodiments, the anonymous complaint reporting method may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 308. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 300 via ROM 302 and / or communication unit 309. When the computer program is loaded into RAM 303 and executed by the computing unit 301, one or more steps of the methods described above may be performed. Alternatively, in other embodiments, the computing unit 301 may be configured to perform the aforementioned anonymous complaint reporting method by any other suitable means (e.g., by means of firmware).

[0075] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application-Specific Standard Products), SOCs (System-on-Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0076] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0077] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, RAM, ROM, EPROM (Electrically Programmable Read-Only Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0078] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0079] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include LANs (Local Area Networks), WANs (Wide Area Networks), the Internet, and blockchain networks.

[0080] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. A server can be a cloud server, also known as a cloud computing server or cloud host, a hosting product within the cloud computing service system that addresses the shortcomings of traditional physical hosts and VPS (Virtual Private Server) services, such as high management difficulty and weak business scalability. Servers can also be servers for distributed systems or servers incorporating blockchain technology.

[0081] It's important to note that artificial intelligence (AI) is the study of enabling computers to simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, and planning). It encompasses both hardware and software technologies. AI hardware technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, and big data processing. AI software technologies primarily include computer vision, speech recognition, natural language processing, machine learning / deep learning, big data processing, and knowledge graph technologies.

[0082] The various numerical designations such as "first," "second," etc., used in this disclosure are merely for ease of description and are not intended to limit the scope of the embodiments of this disclosure, nor do they indicate a sequential order.

[0083] At least one of the features described in this disclosure can also be described as one or more, and multiple features can be two, three, four or more, and this disclosure does not impose any limitations. In the embodiments of this disclosure, for a technical feature, the technical features in that technical feature are distinguished by "first", "second", "third", "A", "B", "C" and "D", etc., and there is no sequential order or size order among the technical features described by "first", "second", "third", "A", "B", "C" and "D".

[0084] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0085] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A method for anonymous complaint and reporting, characterized in that, include: Obtain the user's real mobile phone number, and generate an irreversibly encrypted anonymous identifier based on the real mobile phone number and dynamic parameters; The user-signed authorization agreement is hashed with the generation information of the anonymous identifier to generate authorization certificate and anonymous identifier certificate, and the authorization certificate and anonymous identifier certificate are synchronized to the blockchain certificate platform. Based on the anonymous identifier access number proxy platform, a temporary number is dynamically bound and voice processing service is enabled to establish an anonymous call connection with the target hotline through the temporary number; After the call ends, the temporary number is unbound, and the call record and unbinding status are synchronized to the blockchain evidence storage platform.

2. The method according to claim 1, characterized in that, The dynamic parameters include a unique device identifier and a business system identifier; The generation of an irreversibly encrypted anonymous identifier based on the real mobile phone number and dynamic parameters includes: A hash algorithm is used to encrypt the concatenated data of the real mobile phone number, the device's unique identifier, and the business system identifier to generate the anonymous identifier that is irreversibly encrypted.

3. The method according to claim 1, characterized in that, The generated information includes the timestamp of the anonymous identifier's generation and operator network parameters; The step of performing a hash operation between the user-signed authorization agreement and the generation information of the anonymous identifier includes: The combined data of the authorization protocol text, the generation timestamp, and the operator network parameters are processed by multiple hash operations, and a random disturbance factor is introduced during the operation.

4. The method according to claim 1, characterized in that, The method of dynamically binding a temporary number and enabling voice processing services based on the anonymous identifier access number proxy platform includes: Before binding a temporary number, verify the validity of the anonymous identifier storage and the authorized storage in the blockchain storage platform; Upon successful verification, the anonymous identifier is bound to the temporary number, and the voice processing service is activated. The voice processing service transforms the user's voice characteristics by adjusting the voice frequency and performing filtering.

5. The method according to claim 1, characterized in that, The step of synchronizing call records and unbinding status to the blockchain evidence storage platform includes: In response to unbinding the temporary number after the call ends, the unbinding status is obtained. The unbinding status includes an unbinding timestamp and a status code, wherein the difference between the unbinding timestamp and the call start timestamp meets a preset threshold. The call records contain temporary numbers, target hotline numbers, and call durations. A hash algorithm is used to generate a digest value for evidence storage.

6. The method according to claim 1, characterized in that, Also includes: The risk verification module assists in the analysis of voice data from anonymous complaints and reports. The risk verification module calculates a comprehensive risk score based on voice feature similarity and user behavior pattern matching.

7. An anonymous complaint and reporting device, characterized in that, include: The generation unit is used to obtain the user's real mobile phone number and generate an irreversibly encrypted anonymous identifier based on the real mobile phone number and dynamic parameters; The processing unit is used to perform a hash operation on the authorization agreement signed by the user and the generation information of the anonymous identifier to generate authorization certificate and anonymous identifier certificate, and synchronize the authorization certificate and the anonymous identifier certificate to the blockchain certificate platform. The binding unit is used to access the number agent platform based on the anonymous identifier, dynamically bind a temporary number and enable voice processing services, and establish an anonymous call connection with the target hotline through the temporary number. The synchronization unit is used to unbind the temporary number after the call ends and synchronize the call record and unbinding status to the blockchain evidence storage platform.

8. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-6.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method according to any one of claims 1-6.

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