Graphical generation method and system for block chain wallet private key fragment

Abstract

The invention provides a block chain wallet private key fragment graphical generation method and system. The method comprises the following steps: S1, segmenting a private key of a block chain wallet into a plurality of private key fragments; s2, generating a unique graphical representation for each private key segment by using an AIGC technology, and obtaining a graphical private key segment; s3, encrypting the graphical private key segments, and performing redundant backup storage; and S4, recovering the graphical private key segments through a multi-verification mechanism, and combining the graphical private key segments to restore a complete private key. According to the method, the security of the private key of the block chain wallet is effectively improved, the security risk caused by loss or leakage of the private key is prevented, and meanwhile, a private key storage and recovery scheme which is easy to operate and manage is provided for a user.

Description

Technical Field

[0001] This invention relates to the field of blockchain technology, specifically to a method and system for graphically generating private key shards for blockchain wallets, and more specifically to a method and system for graphically generating private key shards for blockchain wallets based on artificial intelligence-generated content technology. Background Technology

[0002] With the rapid development of blockchain technology, blockchain wallets have become a key tool for managing and protecting digital assets; traditional blockchain wallets rely on complex passwords and mnemonic phrases to protect private keys. However, with the development of information technology, traditional methods face the following challenges:

[0003] Poor user experience: The generation and management of private keys are complex, making it difficult for users to understand and operate correctly, which leads to the easy loss or leakage of private keys.

[0004] Insufficient security: A single method of storing private keys is at risk of being stolen or cracked, and is more easily exposed to attackers when used improperly.

[0005] Backup is difficult: Traditional mnemonic phrases or passwords require users to back them up manually, and users may lose their private keys due to memory errors or improper storage, which may lead to asset loss.

[0006] To improve the security and user experience of blockchain wallets, this invention proposes a method and system for graphically generating private key fragments for blockchain wallets based on AIGC technology. By fragmenting and graphically generating private keys, the security and convenience of private key management are improved. Summary of the Invention

[0007] To address the shortcomings of existing technologies, the purpose of this invention is to provide a graphical method and system for generating blockchain wallet private key shards.

[0008] A graphical method for generating blockchain wallet private key shards according to the present invention includes:

[0009] Step S1: Divide the private key of the blockchain wallet into multiple private key fragments;

[0010] Step S2: Use AIGC technology to generate a unique graphical representation for each private key fragment to obtain a graphical private key fragment;

[0011] Step S3: Encrypt the graphical private key fragments and then perform redundant backups and storage.

[0012] Step S4: Recover the graphical private key fragments through a multi-factor authentication mechanism and combine them to restore the complete private key.

[0013] Preferably, step S1 includes: dividing the private key of the blockchain wallet into n private key fragments using Shamir's Secret Sharing algorithm; wherein at least k private key fragments are required to recover the complete private key, k≤n;

[0014] The segmentation using Shamir's Secret Sharing algorithm includes: using the second-order polynomial P(x) = a0 + a1x + a2x 2 +...+a n-1 x n-1 Calculate the values ​​of n points (x) respectively. i ,P(x i )), n points correspond to n private key fragments; where a0 represents the private key value, and a1 and a2 are randomly generated coefficients.

[0015] Preferably, step S2 includes: generating a unique graphical representation of each private key fragment using generative adversarial networks and style transfer techniques;

[0016] The process of generating a unique graphical representation for each private key fragment using generative adversarial networks and style transfer techniques includes:

[0017] Step S2.1: Construct a generative adversarial network and train the constructed generative adversarial network to obtain the trained generative adversarial network;

[0018] Step S2.2: Use the trained generative adversarial network to generate a preliminary image based on each private key fragment;

[0019] Step S2.3: Process the generated image using style transfer technology to obtain an image that meets the preset requirements;

[0020] Step S2.4: Introduce random noise into the currently obtained image to ensure that the same input generates different graphics.

[0021] Preferably, step S3 includes: encrypting the graphical private key fragment using AES-256 and then redundantly backing it up and storing it on different devices or locations.

[0022] Preferably, step S4 includes: obtaining at least k graphical private key fragments, obtaining at least k graphical private key fragments through multiple verifications, and then using Shamir's Secret Sharing algorithm to recover the complete private key.

[0023] The multiple verifications include biometric verification and two-factor verification.

[0024] A graphical generation system for blockchain wallet private key sharding provided by the present invention includes:

[0025] Module M1: Divides the private key of the blockchain wallet into multiple private key fragments;

[0026] Module M2: Utilizes AIGC technology to generate a unique graphical representation for each private key fragment, thus obtaining a graphical private key fragment;

[0027] Module M3: Encrypts the graphical private key fragments and performs redundant backups and storage.

[0028] Module M4: Recovers and combines graphical private key fragments through a multi-factor authentication mechanism to restore the complete private key.

[0029] Preferably, module M1 includes: segmenting the private key of the blockchain wallet using Shamir's Secret Sharing algorithm to obtain n private key fragments; wherein at least k private key fragments are required to recover the complete private key, k≤n;

[0030] The segmentation using Shamir's Secret Sharing algorithm includes: using the second-order polynomial P(x) = a0 + a1x + a2x 2 +...+a n-1 x n-1 Calculate the values ​​of n points (x) respectively. i ,P(x i )), n points correspond to n private key fragments; where a0 represents the private key value, and a1 and a2 are randomly generated coefficients.

[0031] Preferably, module M2 includes: generating a unique graphical representation of each private key fragment using generative adversarial networks and style transfer techniques;

[0032] The process of generating a unique graphical representation for each private key fragment using generative adversarial networks and style transfer techniques includes:

[0033] Module M2.1: Construct a generative adversarial network (GAN) and train the constructed GAN to obtain the trained GAN;

[0034] Module M2.2: Generates a preliminary image based on each private key fragment using the trained generative adversarial network;

[0035] Module M2.3: Uses style transfer technology to process the generated image to obtain an image that meets preset requirements;

[0036] Module M2.4: Introduces random noise into the currently acquired image to ensure that the same input generates different graphics.

[0037] Preferably, the module M3 includes: encrypting the graphical private key fragment using AES-256 and then redundantly backing it up and storing it in different devices or locations.

[0038] Preferably, module M4 includes: acquiring at least k graphical private key fragments, acquiring at least k graphical private key fragments through multiple verifications, and then using Shamir's Secret Sharing algorithm to recover the complete private key.

[0039] The multiple verifications include biometric verification and two-factor verification.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] 1. This invention uses private key sharding algorithms such as Shamir's Secret Sharing to divide the private key of a blockchain wallet into multiple independent fragments. Only when the user collects a sufficient number of fragments can the complete private key be recovered. This greatly improves the security of the private key. Even if a single fragment is leaked, attackers cannot obtain the complete private key, thereby effectively preventing the theft or cracking of the private key.

[0042] 2. This invention innovatively utilizes AIGC (Artificial Intelligence Generated Content) technology to generate unique graphical representations for each private key fragment. These graphics are both aesthetically pleasing and complex, making it difficult to derive the private key fragments through reverse engineering, thus further enhancing security. At the same time, users can intuitively manage and identify these private key fragments in a graphical manner, simplifying the traditionally complex private key management process. Compared with traditional private key management methods, this invention greatly simplifies the user operation process. Through graphical representation and intuitive recovery process, users do not need to remember complex mnemonic phrases or passwords, nor do they need to worry about losing private key fragments, thus improving the user experience.

[0043] 3. This invention proposes a distributed storage method, which stores graphical private key fragments on different devices or in the cloud; even if a device is lost or damaged, the user can still recover the complete private key through other devices; the distributed storage design reduces the risk of single point of failure and ensures the long-term security of the private key.

[0044] 4. This invention introduces a multi-factor authentication mechanism to ensure that only authorized users can access and recover private key fragments during the private key recovery process; even if an attacker obtains certain fragments or devices, they still need to pass multiple authentications to access the private key, further enhancing the security of the system.

[0045] 5. The private key management scheme of the present invention is applicable to a variety of devices and storage scenarios, including mobile phones, tablets, personal computers and cloud storage services; this flexibility allows users to choose different storage methods according to their own needs, while supporting future device or technology updates and expansions, and has strong compatibility and adaptability. Attached Figure Description

[0046] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0047] Figure 1 A graphical system architecture diagram for generating private key shards for blockchain wallets. Detailed Implementation

[0048] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the scope of protection of the present invention.

[0049] Example 1

[0050] The present invention provides a method and system for graphically generating private key fragments for blockchain wallets, comprising: processing the private key of the blockchain wallet into fragments, and generating corresponding graphical content through artificial intelligence technology. Users can recover and manage the private key graphically, thereby improving the security of the private key and the convenience of user operation.

[0051] The method for graphically generating private key shards for blockchain wallets includes:

[0052] Step 1: Divide the private key of the blockchain wallet into multiple private key fragments;

[0053] In this embodiment, the private key of the blockchain wallet is first segmented by a private key sharding module. The private key is the most critical and sensitive part of the blockchain wallet. To improve its security, the private key is not directly stored or transmitted, but rather first divided into multiple fragments. Each fragment is independent and unrelated, so even if an attacker obtains partial fragments, they cannot recover the complete private key.

[0054] The private key sharding module includes:

[0055] The private key fragmentation process is based on encryption algorithms such as Shamir's Secret Sharing. This algorithm ensures that:

[0056] The private key is divided into n fragments, and at least k fragments are needed to recover the complete private key, where k ≤ n.

[0057] Each fragment is generated and stored according to the principle of independent encryption, making it impossible to deduce the content of other fragments from any fragment.

[0058] Specific procedures:

[0059] First, generate a polynomial P(x) = a0 + a1x + a2x 2 +...+a n-1 x n-1 Where a0 is the numerical representation of the private key, and the other coefficients are randomly generated.

[0060] By inputting different values ​​of x, the value of P(x) is calculated, resulting in n points (x... i ,P(x i These points constitute n fragments of the private key.

[0061] Any k segments can be used to recover the original polynomial P(x) through Lagrange interpolation, and thus obtain the private key.

[0062] To ensure system security, the present invention also includes functions for managing and updating private key fragments;

[0063] Private key fragments are periodically regenerated to address potential security risks.

[0064] For invalid or lost private key fragments, the system provides a mechanism for replacement and updating to ensure that the security of the private key is not affected.

[0065] Step 2: Use AIGC technology to generate a unique graphical representation for each private key fragment to obtain a graphical private key fragment;

[0066] To facilitate the storage and management of private key fragments, this embodiment utilizes AIGC (Artificial Intelligence Generated Content) technology to generate a unique graphical representation for each private key fragment. Each graphic is a complex visual encoding of the private key fragment, possessing aesthetic appeal and being uncopyable.

[0067] Specifically, step 2 includes:

[0068] The graphics generation process specifically includes:

[0069] A generative adversarial network (GAN) is constructed and trained so that the generator can learn to generate highly complex and unique graphics. A preliminary image is obtained by inputting a fragment of private key data into the trained GAN. Then, a style transfer technique is used to integrate the preliminary image into a specific style of graphics. Random noise is introduced during graphics generation to ensure that the same input can generate different graphics. The final output image contains not only the numerical features of the private key fragment but also the features of the artistic style and the unique characteristics of the graphics.

[0070] Training the generative adversarial network includes:

[0071] Generative Adversarial Networks (GANs) train generator and discriminator networks to generate graphics that are complex and difficult to imitate.

[0072] In the image generation process, the generator attempts to produce images that match the distribution of real data, while the discriminator continuously tries to identify which images are forged by the generator and which are real. Through adversarial training, both gradually improve the quality of image generation, making the generator's output images increasingly closer to real data in terms of complexity and uniqueness. First, GAN training is required so that the generator can learn to generate highly complex and unique images.

[0073] The training process is as follows:

[0074] Data preparation: Input a large amount of existing image data (such as a stylized image library) into the discriminator so that it can learn the distribution characteristics of the images.

[0075] Generator Training: Responsible for generating the graph. It creates new images from random noise (or, in this invention, from data features from private key fragments). During each training round, the generator is fed noise (typically a random high-dimensional vector) and generates a graph through the network. In this implementation, the input noise is replaced by numerical data of private key fragments. Each fragment is converted into a unique vector, which serves as the generator's input.

[0076] Discriminator training: Responsible for determining whether the generated images are real or fake. It learns features from the data to try to distinguish between images generated by the generator and real data. The discriminator receives images generated by the generator and a dataset of real images, and updates its parameters through a binary classification task (i.e., determining whether an image is real or fake).

[0077] Iterative training: The generator and discriminator are trained alternately. The generator continuously attempts to produce more realistic images, while the discriminator improves its judgment by identifying forgeries in the generated images. As training progresses, the images generated by the generator gradually approach the real data.

[0078] After generation, the graphic has the following characteristics:

[0079] Uniqueness: By inputting different data from the private key fragment, the generated graph will be different each time, ensuring that each private key fragment corresponds to a unique graph.

[0080] Complexity: The generated graphics are highly complex due to the adversarial training of GANs, making them difficult to crack through simple image processing or reverse engineering.

[0081] Irreversibility: The original private key fragment data cannot be deduced from the generated graph, ensuring the security of the private key.

[0082] Style transfer technique: Incorporating initial images into a specific style to ensure that each graphic has a unique artistic style and complexity.

[0083] In this invention, style transfer technology is used to transform a preliminary image into a visual style, generating artistic and complex graphics.

[0084] It can combine the content of one image with the style of another. Specifically:

[0085] The initial image serves as the content input: After encoding, the initial image becomes the "content" input for style transfer. Style transfer techniques are then used to generate a basic structural image.

[0086] Selecting a Style Image: The system will select one or more style images from a predefined art style library as style input. This image can be an artwork, design graphic, etc., with a specific style, the purpose of which is to give the generated graphic a specific stylized effect.

[0087] Style transfer model: A pre-trained style transfer model applies the selected style to the underlying structure image generated from the private key fragment.

[0088] Output results: The final output image not only contains the numerical features of the private key fragment, but also the features of artistic style, making the generated image both complex and artistic.

[0089] Random perturbation: Introducing random noise when generating graphics ensures that the same input may generate different graphics, thereby improving the uniqueness of the graphics.

[0090] Graphical verification and visualization

[0091] Each generated graphic needs to pass through an automated verification system to ensure it meets the following standards:

[0092] Uniqueness: Each graphic has sufficient visual difference from other graphics.

[0093] Difficult to replicate: The generated graph is complex and the private key fragment cannot be recovered through simple reverse engineering.

[0094] Step 3: Encrypt the graphical private key fragments and then perform redundant backups and storage.

[0095] In this embodiment, the generated graphical private key fragment needs to be stored in a distributed manner to further improve security. The storage strategy includes:

[0096] Distributed storage: Private key fragments are stored on different devices (such as users' mobile phones, tablets, cloud storage, etc.) to avoid the security risks caused by single-point storage.

[0097] Redundant backup: Each segment can have multiple redundant backups to ensure that the private key can still be recovered from other devices if some devices are lost or damaged.

[0098] Step 4: Recover the graphical private key fragments through a multi-factor authentication mechanism and combine them to restore the complete private key.

[0099] In this embodiment, when a user needs to recover the private key, the fragment storage and recovery module will initiate the recovery process:

[0100] The user initiates a recovery request on an authorized device.

[0101] The system verifies user identity through multiple verification methods.

[0102] The private key recovery and management process incorporates a multi-factor authentication mechanism to ensure that only authorized users can access or recover private key fragments. The specific scheme is as follows:

[0103] Biometric authentication: When a user performs a private key recovery operation on the device, the system first requires the user to perform biometric authentication. The device calls the system's biometric module (such as Android's FingerprintManager or iOS's Face ID / Touch ID interface) for authentication. Upon successful authentication, the system returns a success flag, allowing the user to continue; if authentication fails, subsequent operations are rejected, and further protection measures can be implemented according to the system's security policies, such as suspending attempts or locking the user's account. Biometric data is typically stored in a secure area on the device (such as Apple's Secure Enclave or Android's TrustZone) to ensure that even if the device is compromised, the biometric data cannot be easily stolen.

[0104] Two-factor authentication (2FA):

[0105] 1) TOTP Validation:

[0106] When a user sets up 2FA for the first time, the system generates a key and displays a QR code. The user scans the QR code using an application such as Google Authenticator, and then the user's device generates a dynamic 6-digit verification code based on the time and the key.

[0107] Each time a user makes a move, they enter the current dynamic verification code. The system verifies the user's identity by checking whether the entered TOTP value matches the locally calculated TOTP.

[0108] If the user enters the correct verification code, the verification will pass; if the code is entered incorrectly, the user will need to re-enter it or take security measures such as system locking.

[0109] 2) SMS verification code:

[0110] When a user performs a sensitive operation (such as private key recovery), the system sends a one-time verification code to the user's preset mobile phone number through the SMS gateway.

[0111] Users need to enter the received verification code within a limited time. The system verifies whether the entered verification code matches the sent verification code. If they match, the verification is successful; otherwise, the user is refused further operation.

[0112] After collecting a sufficient number of graphical fragments, decrypt and combine these fragments to recover the complete private key.

[0113] During the recovery process, the system will also detect and prevent various security risks, such as malicious attacks or unauthorized access attempts.

[0114] The present invention also provides a graphical generation system for blockchain wallet private key shards. The graphical generation system for blockchain wallet private key shards can be implemented by executing the process steps of the graphical generation method for blockchain wallet private key shards. That is, those skilled in the art can understand the graphical generation method for blockchain wallet private key shards as a preferred embodiment of the graphical generation system for blockchain wallet private key shards.

[0115] Example 2

[0116] like Figure 1 As shown, this invention provides a graphical method for generating blockchain wallet private key shards based on Artificial Intelligence Generated Content (AIGC) technology, including:

[0117] Private key sharding process: When a user creates a blockchain wallet, they first generate a 256-bit private key. This generated private key is then sharded using Shamir's Secret Sharing algorithm. Assuming the private key is divided into 5 fragments (n=5), at least 3 fragments (k=3) are required to recover the complete private key.

[0118] By generating a second-order polynomial P(x) = a0 + a1x + a2x 2 In this equation, a0 is the private key value, and a1 and a2 are randomly generated coefficients. Five points (x1, P(x1)) are calculated for each point, which are the five fragments of the private key. Each private key fragment will be stored as an independent data unit for subsequent processing.

[0119] Graphical Generation Module: The system utilizes AIGC technology to transform each private key fragment into a unique graphical representation. Specifically, it employs a Generative Adversarial Network (GAN) to generate the graphs, training the network to produce complex and unique graphics.

[0120] To enhance the artistry and complexity of the graphics, the system also employs style transfer technology, combining the numerical characteristics of the private key fragment with a specific style to generate unique graphics. The generated graphics are random; even with the same input data, different graphical representations will be produced.

[0121] After the graphic is generated, the graphical private key fragment is bound to the user's device, and a QR code or other graphic encoding that can be recognized by the device is generated.

[0122] Fragment Storage: The generated graphical private key fragments are stored on different devices of the user. For example, fragment 1 is stored on the user's mobile phone, fragment 2 on the tablet, and fragment 3 in the user's cloud storage account. Each fragment is encrypted with AES-256 before storage, ensuring that even if the device is lost, the fragments cannot be accessed by unauthorized personnel. To further enhance security, the system sets up multiple redundant backups. For example, fragment 1 is also backed up on the user's personal computer, and a backup of fragment 3 is also stored in another cloud account.

[0123] Fragment recovery:

[0124] When a user needs to recover their private key, they should first start the recovery process on any authorized device. The system will prompt the user to provide at least three graphical private key fragments.

[0125] Users scan images stored on different devices or enter the corresponding fragment key, and the system first performs multiple verifications. Once verification is successful, the system decrypts and recovers the fragment data.

[0126] The collected fragments are used to recover the original private key using Shamir's Secret Sharing algorithm. The recovered private key is temporarily stored in the device's secure storage area for user use.

[0127] Those skilled in the art will understand that, besides implementing the system and its various devices, modules, and units provided by this invention in the form of purely computer-readable program code, the same functions can be achieved entirely through logical programming of the method steps, making the system and its various devices, modules, and units of this invention function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, the system and its various devices, modules, and units provided by this invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered as structures within the hardware component; alternatively, the devices, modules, and units for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0128] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A method for graphically generating blockchain wallet private key shards, characterized in that: include: Step S1: Split the private key of the blockchain wallet into multiple private key fragments; Step S2: Generate a unique graphical representation for each private key fragment using AIGC technology to obtain a graphical private key fragment; Step S3: Encrypt the graphical private key fragments and store them as redundant backups; Step S4: Recover the graphical private key fragments through a multiple verification mechanism and combine them to restore the complete private key.

2. The method for generating a graphical sharding of a blockchain wallet private key according to claim 1, characterized in that: The step S1 comprises: using Shamir's Secret Sharing algorithm to split the private key of the blockchain wallet to obtain n private key fragments; wherein at least k private key fragments are required to restore the complete private key, k≤n; The segmentation using Shamir's Secret Sharing algorithm includes: using the second-order polynomial P(x)=a0+a1x+a2x 2 +...+a n-1 x n-1 Calculate n points (x i ,P(x i )), n points correspond to n private key fragments; among them, a0 represents the private key value, and a1 and a2 are randomly generated coefficients.

3. The method for generating a graphical sharding of a blockchain wallet private key according to claim 1, characterized in that: The step S2 comprises: generating a unique graphical representation of each private key fragment using a generative adversarial network and style transfer technology; The method of using a generative adversarial network and style transfer technology to generate a unique graphical representation of each private key fragment includes: Step S2.1: construct a generative adversarial network, and train the constructed generative adversarial network to obtain a trained generative adversarial network; Step S2.2: Generate a preliminary image based on each private key fragment using the trained generative adversarial network; Step S2.3: Processing the generated image using style transfer technology to obtain an image that meets preset requirements; Step S2.4: Introduce random noise into the currently acquired image to ensure that the same input generates different images.

4. The method for generating a graphical sharding of a blockchain wallet private key according to claim 1, characterized in that: The step S3 includes: encrypting the graphical private key fragments by AES-256 and storing them in different devices or locations as redundant backups.

5. The method for generating a graphical sharding of a blockchain wallet private key according to claim 2, characterized in that: The step S4 includes: obtaining at least k graphical private key fragments, performing multiple verifications on the obtained at least k graphical private key fragments, and then restoring the complete private key using Shamir's Secret Sharing algorithm. The multiple authentications include biometric authentication and two-factor authentication.

6. A blockchain wallet private key sharding graphical generation system, characterized in that: include: Module M1: Split the private key of the blockchain wallet into multiple private key fragments; Module M2: Generate a unique graphical representation for each private key fragment using AIGC technology to obtain a graphical private key fragment; Module M3: Encrypt the graphical private key fragments and store them as redundant backups; Module M4: Recover graphical private key fragments and combine them through a multiple verification mechanism to restore the complete private key.

7. The blockchain wallet private key sharding graphical generation system according to claim 6 is characterized in that: The module M1 includes: using Shamir's Secret Sharing algorithm to split the private key of the blockchain wallet to obtain n private key fragments; wherein at least k private key fragments are required to restore the complete private key, k≤n; The segmentation using Shamir's Secret Sharing algorithm includes: using the second-order polynomial P(x)=a0+a1x+a2x 2 +...+a n-1 x n-1 Calculate n points (x i ,P(x i )), n points correspond to n private key fragments; among them, a0 represents the private key value, and a1 and a2 are randomly generated coefficients.

8. The blockchain wallet private key sharding graphical generation system according to claim 6, characterized in that: The module M2 includes: generating a unique graphical representation of each private key fragment using a generative adversarial network and style transfer technology; The method of using a generative adversarial network and style transfer technology to generate a unique graphical representation of each private key fragment includes: Module M2.1: Construct a generative adversarial network and train the constructed generative adversarial network to obtain the trained generative adversarial network; Module M2.2: Generate preliminary images based on each private key fragment using the trained GAN. Module M2.3: Use style transfer technology to process the generated image to obtain an image that meets the preset requirements; Module M2.4: Introduce random noise into the currently acquired image to ensure that the same input generates different images.

9. The blockchain wallet private key sharding graphical generation system according to claim 6, characterized in that: The module M3 includes: encrypting the graphical private key fragments through AES-256 and then storing them in different devices or locations as redundant backups.

10. The blockchain wallet private key sharding graphical generation system according to claim 7, characterized in that: The module M4 includes: obtaining at least k graphical private key fragments, performing multiple verifications on the obtained at least k graphical private key fragments, and then restoring the complete private key using Shamir's Secret Sharing algorithm. The multiple authentications include biometric authentication and two-factor authentication.

Images