Carbon digital asset cross-border transaction method and system, electronic equipment and storage medium

Abstract

The invention discloses a carbon digital asset cross-border transaction method and system, an electronic device and a storage medium, the carbon digital asset cross-border transaction method uses an Internet of Things sensing device to collect carbon emission data in real time, can obtain comprehensive and dynamic carbon emission data, facilitates real-time and accurate monitoring of the carbon emission permit, and improves the transaction efficiency. Therefore, accurate right confirmation of the carbon assets is realized, a unified and credible right confirmation mechanism of the carbon digital assets is established, the authenticity and validity of the carbon digital assets can be accurately traced, and the problems of repeated right confirmation and false right confirmation are avoided. In addition, circulation, transaction and liquidation of cross-border carbon assets are effectively realized, and privacy protection can be well realized.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon finance, and in particular, to a method and system for cross-border trading of carbon digital assets, an electronic device, and a computer-readable storage medium. Background Art

[0002] Carbon digital assets refer to the digital forms of carbon emission allowances or carbon credits represented and managed through blockchain technology. These assets usually originate from the carbon market, and through the carbon emission trading mechanism, the quantified results of carbon emission reduction are transformed into tradable digital assets, thereby promoting the reduction of carbon emissions. Carbon digital assets have the characteristics of decentralization, traceability, transparency, etc., and can effectively realize the confirmation of rights, circulation, and trading of carbon emission rights. On the blockchain platform, carbon digital assets can provide a safe, credible, and verifiable trading environment, support cross-border trading and the global flow of carbon credits, help promote the realization of global carbon emission reduction goals, and provide new carbon trading methods and incentive mechanisms for enterprises or individuals. However, in the actual application process, there is currently no unified and credible carbon digital asset right confirmation mechanism, and it is impossible to accurately trace the authenticity and effectiveness of carbon digital assets, and it is easy to have the situation where the same carbon asset is right-confirmed multiple times by different institutions, resulting in frequent problems of duplicate right confirmation and false right confirmation. In addition, there are also problems such as high cost, low efficiency, and high energy consumption of the consensus mechanism during cross-border trading, making it difficult to achieve the efficient circulation of carbon assets in cross-border trading. Summary of the Invention

[0003] The present invention provides a method and system for cross-border trading of carbon digital assets, an electronic device, and a computer-readable storage medium, which can achieve accurate carbon asset right confirmation, establish a unified and credible carbon digital asset right confirmation mechanism, can accurately trace the authenticity and effectiveness of carbon digital assets, and avoid the problems of duplicate right confirmation and false right confirmation.

[0004] According to one aspect of the present invention, a method for cross-border trading of carbon digital assets is provided, including the following:

[0005] Based on the Internet of Things sensing data, confirm the rights of the carbon assets of the first carbon digital asset holding node, and generate the carbon digital assets of the first carbon digital asset holding node;

[0006] The first carbon digital asset holding node conducts cross-border trading with the second carbon digital asset holding node in the second blockchain based on the carbon digital assets through the first blockchain;

[0007] The second carbon digital asset holding node conducts transaction settlement on the second blockchain based on the traded carbon digital assets.

[0008] Furthermore, the process of confirming the ownership of the carbon asset of the first carbon digital asset holding node based on the IoT sensor data and generating the carbon digital asset of the first carbon digital asset holding node includes the following:

[0009] Deploy sensor equipment at the carbon emission sources of the First Carbon digital asset holding nodes to collect carbon emission data in real time and pre-process the collected carbon emission data;

[0010] Perform zero-knowledge verification on pre-processed carbon emission data;

[0011] The LSTM-Attention neural network model is used to extract features from the preprocessed carbon emission data to obtain feature vectors. The extracted feature vectors are then input into the trained emission reduction efficiency factor prediction model to predict the current emission reduction efficiency factor.

[0012] The number of carbon assets that have been confirmed is calculated based on the current emission reduction efficiency factor and the collected carbon emission data;

[0013] The corresponding carbon digital assets are determined based on the number of confirmed carbon assets, and the carbon digital assets are issued to the account of the first carbon digital asset holding node.

[0014] Furthermore, after the number of carbon assets is determined, the carbon assets are fragmented, and the complete carbon assets are divided into multiple carbon asset fragments.

[0015] Furthermore, the process of the first carbon digital asset holding node conducting a cross-border transaction based on the carbon digital asset through the first blockchain with the second carbon digital asset holding node in the second blockchain includes the following:

[0016] The first carbon digital asset holding node initiates a cross-border transaction request on the first blockchain to the second carbon digital asset holding node in the second blockchain, and dynamically compiles a smart contract based on compliance rules to perform a preliminary compliance check on the cross-border transaction request;

[0017] The market price of carbon digital asset transactions is calculated based on the supply and demand of carbon digital assets, carbon prices, exchange rates, and taxes;

[0018] The Second Carbon digital asset holding node receives a cross-border transaction request, dynamically compiles a smart contract based on compliance rules, performs a preliminary compliance check on the cross-border transaction request, and then confirms the transaction request;

[0019] The carbon digital assets traded on the first blockchain are locked based on a hash time lock contract, and carbon digital assets of equal value are minted on the second blockchain based on a mirrored hash time lock contract and distributed to the account of the second carbon digital asset holding node, and the locked carbon digital assets on the first blockchain are destroyed or frozen.

[0020] Furthermore, the market price of carbon digital asset transactions is calculated based on the following formula:

[0021]

[0022] where P market represents the market price of carbon digital asset transactions, D carbon represents the demand for carbon digital assets, S carbon represents the supply of carbon digital assets, P carbon represents the carbon price, E rate represents the exchange rate, T fee represents the tax, and δ represents the adjustment coefficient.

[0023] Furthermore, during the cross-border transaction process, the first blockchain and the second blockchain adopt a PoS+PBFT hybrid consensus mechanism to reach a consensus. When the number of transactions between the two blockchains is less than the preset threshold, the PoS consensus mechanism is adopted, and when the number of transactions between the two blockchains is not less than the preset threshold, the PBFT consensus mechanism is adopted.

[0024] Furthermore, it also includes the following:

[0025] Supervise and conduct compliance audits on the cross-border transaction process.

[0026] In addition, the present invention also provides a carbon digital asset cross-border trading system, including:

[0027] A carbon asset right confirmation module, used to confirm the carbon assets of the first carbon digital asset holding node based on Internet of Things sensing data, and generate the carbon digital assets of the first carbon digital asset holding node;

[0028] A cross-border trading module, used to enable the first carbon digital asset holding node to conduct cross-border transactions with the second carbon digital asset holding node in the second blockchain based on the carbon digital assets;

[0029] A transaction settlement module, used to enable the second carbon digital asset holding node to conduct transaction settlements on the second blockchain based on the traded carbon digital assets.

[0030] In addition, the present invention also provides an electronic device, including a processor and a memory. A computer program is stored in the memory, and the processor is used to execute the steps of the method described above by calling the computer program stored in the memory.

[0031] In addition, the present invention also provides a computer-readable storage medium, used to store a computer program for carbon digital asset cross-border transactions. When the computer program runs on a computer, it executes the steps of the method described above.

[0032] The present invention has the following beneficial effects:

[0033] The carbon digital asset cross-border trading method of the present invention uses Internet of Things sensing devices to collect carbon emission data in real time, enabling the acquisition of comprehensive and dynamic carbon emission data. This is conducive to the real-time and accurate monitoring of carbon emission rights, thereby achieving accurate carbon asset rights confirmation. A unified and credible carbon digital asset rights confirmation mechanism is established, which can accurately trace the authenticity and effectiveness of carbon digital assets, avoiding problems such as duplicate rights confirmation and false rights confirmation.

[0034] In addition, the carbon digital asset cross-border trading system of the present invention also has the above advantages.

[0035] In addition to the purposes, features, and advantages described above, the present invention has other purposes, features, and advantages. The following will refer to the drawings for a more detailed description of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The drawings forming a part of this application are used to provide a further understanding of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0037] Figure 1 is a schematic flow chart of the carbon digital asset cross-border trading method of the preferred embodiment of this application;

[0038] Figure 2 is Figure 1 a sub-flow schematic diagram of step S1 in

[0039] Figure 3 is Figure 1 a sub-flow schematic diagram of step S2 in

[0040] Figure 4 is another schematic flow chart of the carbon digital asset cross-border trading method of the preferred embodiment of this application;

[0041] Figure 5 is a schematic module structure diagram of the carbon digital asset cross-border trading system of another embodiment of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] It should be noted that, without conflict, the embodiments in this application and the features in the embodiments can be combined with each other. The following will refer to the drawings and combine with the embodiments to detail this application.

[0043] Refer to Figure 1 , the preferred embodiment of this application provides a carbon digital asset cross-border trading method, including the following:

[0044] Step S1: Confirm the carbon assets of the first carbon digital asset holding node based on the Internet of Things sensing data, and generate the carbon digital assets of the first carbon digital asset holding node;

[0045] Step S2: The first carbon digital asset holding node conducts cross-border transactions with the second carbon digital asset holding node in the second blockchain based on the carbon digital assets through the first blockchain;

[0046] Step S3: The second carbon digital asset holding node conducts transaction settlement on the second blockchain based on the traded carbon digital assets.

[0047] It can be understood that the process of cross-border transaction of carbon digital assets in this embodiment is as follows: First, confirm the carbon assets of the first carbon digital asset holding node through the Internet of Things sensing data, generate the carbon digital assets of the first carbon digital asset holding node on the first blockchain where the first carbon digital asset holding node is located. Then, the first carbon digital asset holding node can conduct cross-border transactions with the second carbon digital asset holding node in the second blockchain based on the carbon digital assets. After the cross-border transaction is completed, the second carbon digital asset holding node can conduct transaction settlement on the second blockchain according to the obtained carbon digital assets, and convert the carbon digital assets into the legal currency of the country where the second blockchain is located. Among them, the first blockchain and the second blockchain belong to different countries.

[0048] It can be understood that the method for cross-border transaction of carbon digital assets in this embodiment uses Internet of Things sensing devices to collect carbon emission data in real time, can obtain comprehensive and dynamic carbon emission data, is conducive to real-time and accurate monitoring of carbon emission rights, thereby realizing accurate carbon asset confirmation, establishing a unified and credible carbon digital asset confirmation mechanism, can accurately trace the authenticity and validity of carbon digital assets, and avoids the problems of repeated confirmation and false confirmation.

[0049] Among them, as Figure 2 shown, in the step S1, the process of confirming the carbon assets of the first carbon digital asset holding node based on the Internet of Things sensing data and generating the carbon digital assets of the first carbon digital asset holding node includes the following contents:

[0050] Step S11: Deploy sensor devices at the carbon emission sources of the first carbon digital asset holding node, collect carbon emission data in real time, and preprocess the collected carbon emission data;

[0051] Step S12: Conduct zero-knowledge verification on the preprocessed carbon emission data;

[0052] Step S13: Use the LSTM-Attention neural network model to extract features from the preprocessed carbon emission data to obtain feature vectors, and input the extracted feature vectors into the trained emission reduction efficiency factor prediction model to predict the current emission reduction efficiency factor;

[0053] Step S14: Calculate the quantity of carbon assets with confirmed rights based on the current emission reduction efficiency factor and the collected carbon emission data;

[0054] Step S15: Determine the corresponding carbon digital assets based on the quantity of carbon assets with confirmed rights, and distribute the carbon digital assets to the account of the first carbon digital asset holding node.

[0055] Specifically, deploy IoT sensor devices at the carbon emission sources (such as factories and power plants) of the first carbon digital asset holding node U A to collect carbon emission data P raw in real time. Since there are noises, outliers, missing values, etc. in the collected original data, in order to improve the data quality, it is necessary to preprocess the collected carbon emission data. For example, use the moving average filtering method to denoise the data. Assuming that the filtering window size is w, the denoised data at the i-th moment can be expressed as: where, P filtered (i) represents the denoised data at the i-th moment, P raw (i) represents the original data at the i-th moment. Then, use the Min-Max normalization method to normalize the denoised data and map the data to the interval [0,1].

[0056] Then, the IoT device sends the collected carbon emission data to the verification node of the first blockchain (such as a carbon emission verification agency), and the verification node verifies the authenticity of the data based on zero-knowledge proof (ZKP) without disclosing the original data. For example, assume that the verification node wants to prove that a certain carbon emission data P raw is within a given interval, but does not want to disclose the specific value. The generated proof π satisfies the following relationship: π = ZKP(P raw , commitment), commitment = H(P raw , r), H() represents the hash function, r represents the random number, and the commitment is obtained by the hash function H for the original carbon emission data P raw and a random number r. The hash function H has characteristics such as one-wayness and collision resistance, making it difficult to reverse-derive the original data P raw and the random number r from the commitment, and the introduction of the random number r increases the security and unpredictability. Even for different original data P rawIn some cases, the same hash value may be calculated (with an extremely low probability). After adding the random number r, the probability of different original data generating the same commitment will also be greatly reduced, thus better protecting the privacy of the data and the validity of the proof. The verifier can confirm certain characteristics of the data by verifying the commitment and the relevant proof π without obtaining the original data P raw under the condition.

[0057] Next, a hybrid neural network of LSTM-Attention is used to extract features from the preprocessed carbon emission data to obtain feature vectors. Among them, LSTM is suitable for processing sequential data and can capture long-term dependencies in the data, while the Attention mechanism can help the network focus on the important parts of the data and improve the performance of the model. Assume the input sequence is X = [x1, x2,..., x T , and the output H = [h1, h2,..., h T of the LSTM layer is calculated by the following formula:

[0058]

[0059] where, i t , f t , g t , o t represent the input gate, forget gate, candidate memory unit, and output gate respectively, c t represents the cell state, σ represents the sigmoid function, W and b represent the learned weight matrix and bias vector, and ⊙ represents element-wise multiplication. The Attention layer calculates the attention weight α t for each time step in the output of the LSTM layer and obtains the weighted sum output h att , and the calculation formula is: e t = v T tanh(W1h t + b1), where, v, W1, and b1 are learnable parameters, and h att is a feature vector that combines sequence information and attention weights obtained after being processed by the LSTM and Attention layers.

[0060] Then, the extracted feature vector h att is input into the trained emission reduction efficiency factor prediction model, and the current emission reduction efficiency factor can be predicted based on the real-time collected carbon emission data. It can be understood that the emission reduction efficiency factor is an indicator used to measure the efficiency of carbon emission sources in emission reduction, and it reflects the efficiency of carbon emission reduction under certain carbon emission data P rawOn this basis, the proportional relationship that can be converted into the quantity of carbon assets that can be confirmed in rights reflects the comprehensive situation such as the emission reduction motivation and effect of this carbon emission source. As time goes by, the equipment of carbon emission sources such as factories and power plants may be updated, the production process may be improved, the energy structure may be adjusted, etc. These will all lead to changes in their emission reduction capabilities. Historical data can only reflect the past situation, so it is necessary to continuously adjust the emission reduction efficiency factor according to newly collected real-time data to accurately reflect the current emission reduction efficiency; moreover, external factors such as environmental policies and carbon emission targets in different periods are different, which will also prompt carbon emission sources to adopt different emission reduction measures and invest different emission reduction costs, thereby affecting the emission reduction efficiency factor.

[0061] Among them, the training process of the emission reduction efficiency factor prediction model is as follows: First, it is necessary to continuously collect various relevant data of carbon emission sources, including but not limited to historical carbon emission data, equipment operation data, energy consumption data, production output data, etc., as well as external data such as policy documents related to emission reduction and market environment changes; then, use feature engineering methods in machine learning to extract features related to emission reduction efficiency from the collected data, such as energy utilization rate, carbon emission per unit output, and the proportion of operation time of emission reduction equipment, etc.; next, use the extracted features as input, and use the known emission reduction efficiency or the quantity of carbon assets that can be confirmed in rights in history as labels, and select a suitable machine learning model for training to obtain a model that can reflect the relationship between data features and emission reduction efficiency; finally, as new data is continuously added, retrain the model regularly or irregularly to update the parameters in the model, so as to achieve dynamic adjustment of the emission reduction efficiency factor.

[0062] Then, based on the current emission reduction efficiency factor and the collected carbon emission data, calculate the quantity of carbon assets that can be confirmed in rights, and the calculation formula can be expressed as: A asset =P raw ×E eff , where A asset represents the quantity of carbon assets that can be confirmed in rights, P raw represents the carbon emission data, and E eff represents the emission reduction efficiency factor.

[0063] Finally, based on the calculated quantity of carbon assets A asset determine the corresponding carbon digital assets and distribute the carbon digital assets to the account of the first carbon digital asset holding node. For example, assuming that each unit of carbon emission reduction can be exchanged for a token (such as token), then the quantity of carbon digital assets (i.e., the number of tokens) that can be generated based on the quantity of carbon assets A asset is: T cabon =A asset×β, β represents the exchange ratio between carbon assets and carbon digital assets. After the carbon digital assets are calculated, a carbon emission certificate will be generated. The carbon emission certificate will be signed by multiple nodes such as the issuer, holder, regulator, and verifier to confirm the authenticity and validity of the carbon emission certificate, ensuring that the asset cannot be changed after confirmation. After the signature is completed, the final carbon digital asset certificate C is formed. final , and the carbon digital asset issuance node will cabon It is issued to the account of the First Carbon digital asset holding node, and is transparent, traceable and tamper-proof based on blockchain technology.

[0064] It can be understood that the present invention introduces the LSTM-Attention hybrid neural network and the emission reduction efficiency factor prediction model, which can efficiently process complex carbon emission data and accurately predict the current emission reduction efficiency factor based on the real-time collected carbon emission data, thereby improving the accuracy and efficiency of carbon asset title confirmation, and establishing a unified and reliable carbon digital asset title confirmation mechanism, which can accurately trace the authenticity and validity of carbon digital assets, and avoid the problems of duplicate title confirmation and false title confirmation.

[0065] Optionally, in step S14, after the carbon asset quantity is determined, the carbon asset is further fragmented, and the complete carbon asset is divided into multiple carbon asset fragments. Specifically, a dynamic NFT architecture is adopted to fragment the carbon asset. Assuming that a complete carbon asset A asset , split it into n fragments, then the value of each fragment is calculated as: Each fragment corresponds to an ERC-1155 standard NFT, whose properties can be updated dynamically.

[0066] It can be understood that the present invention also fragments carbon assets, allowing flexible fragmentation and title confirmation of carbon digital assets, meeting the diverse use and trading needs of carbon assets in different scenarios, and making the management and circulation of carbon assets more efficient and convenient.

[0067] In addition, if Figure 3 As shown, in step S2, the process of the first carbon digital asset holding node conducting a cross-border transaction based on the carbon digital asset through the first blockchain with the second carbon digital asset holding node in the second blockchain includes the following:

[0068] Step S21: The first carbon digital asset holding node initiates a cross-border transaction request on the first blockchain to the second carbon digital asset holding node in the second blockchain, and dynamically compiles a smart contract based on compliance rules to perform a preliminary compliance check on the cross-border transaction request;

[0069] Step S22: Calculate the market price of carbon digital asset transactions based on the supply and demand of carbon digital assets, carbon price, exchange rate, and taxes and fees;

[0070] Step S23: The second carbon digital asset holding node receives a cross-border transaction request, and after a preliminary compliance check on the cross-border transaction request based on the dynamically compiled smart contract according to the compliance rules, it confirms the transaction request;

[0071] Step S24: Lock the carbon digital assets of the transaction on the first blockchain based on the hash time lock contract, mint equivalent carbon digital assets on the second blockchain based on the mirror hash time lock contract and distribute them to the account of the second carbon digital asset holding node, and destroy or freeze the locked carbon digital assets on the first blockchain.

[0072] Specifically, the first carbon digital asset holding node U A initiates a cross-border transaction request on the first blockchain A to the second carbon digital asset holding node U in the second blockchain B B and can specify the receiving chain and target address on the first blockchain A. Moreover, before initiating the cross-border transaction request, the first carbon digital asset holding node U A performs a preliminary compliance check on the cross-border transaction request through the dynamically compiled smart contract according to the compliance rules. The dynamically compiled smart contract according to the compliance rules converts the collected legal terms L = {l1, l2,..., l n} related to carbon digital asset cross-border transactions into executable smart contract code SC. The specific compilation process is SC = Compile(L), where Compile represents the compilation function. The smart contract SC will check information such as the transaction quantity Q and the identities of both parties in the transaction request. If all compliance rules are met, the cross-border transaction request is allowed to be initiated. It can be understood that the present invention converts the legal terms of various countries into executable smart contracts to ensure that cross-border transactions comply with the regulatory requirements of different countries, making the mutual recognition of carbon assets between different countries simpler and facilitating the formation of an efficient cross-border transaction environment.

[0073] Then, during the cross-border transaction matching process, the transaction platform node will comprehensively consider data in multiple dimensions such as the supply and demand of carbon digital assets, carbon price, exchange rate, and taxes and fees to adjust the market price of carbon digital asset transactions. Specifically, the market price of carbon digital asset transactions is calculated based on the following formula:

[0074]

[0075] where P market represents the market price of carbon digital asset transactions, D carbon represents the demand for carbon digital assets, S carbon represents the supply of carbon digital assets, P carbonDenote the carbon price as E rate Denote the exchange rate as T fee Denote the tax as δ, and the adjustment coefficient can be adjusted according to actual needs.

[0076] Next, the first blockchain platform A sends the cross-chain transaction request of the holding node U A to the holding node U on the second blockchain platform B B . Among them, in this process, the transaction path dynamic optimization algorithm is used to select the optimal cross-chain communication path. This algorithm considers the latency D path of different paths, the bandwidth B path , as well as factors such as carbon price, exchange rate, and tax. Assume that there are k possible cross-chain communication paths Path = {path1, path2, path3..., path k}, and the comprehensive cost calculation formula for each path is: where g() represents the function for calculating the comprehensive cost of the path, and then select the path with the minimum value for cross-chain communication. It can be understood that the present invention designs a transaction path dynamic optimization algorithm, fully considering multi-dimensional parameters such as carbon price, exchange rate, and tax. By calculating the comprehensive cost of the path, the optimal cross-chain transaction path is selected, improving the transaction efficiency and cost-effectiveness.

[0077] In addition, in the message signature process of cross-chain communication, the present invention adopts a cross-chain verification scheme based on threshold signature. Specifically, assume that the signature threshold is t, and the set of nodes participating in the signature is S = {s1, s2,..., s n}(n ≥ t), and each node generates its own signature share sig i , then the final threshold signature Sig threshold is calculated as: where mod n represents the modulus related to the signature algorithm. It can be understood that the present invention adopts a cross-chain verification scheme based on threshold signature. By dispersing the signature power, only a certain number of nodes need to participate in the signature together to generate a valid signature, effectively improving the signature efficiency, and it is expected that the signature efficiency will be improved by 35%.

[0078] Next, the second carbon digital asset holding node U BAfter receiving a cross-border transaction request, a smart contract is dynamically compiled based on compliance rules to conduct a preliminary compliance check on the cross-border transaction request. If the check passes, a "confirmed transaction" message is created on the second blockchain platform B. The second blockchain platform B transfers the "confirmed transaction" information to the first blockchain platform A through an interchain communication protocol (IBC). Similarly, the transaction path dynamic optimization algorithm is used again to select the optimal return path to ensure fast and accurate information transfer. Moreover, during the return process, a PoS+PBFT hybrid consensus mechanism is adopted for consensus, and the consensus algorithm is dynamically switched according to the transaction volume. After receiving the "confirmed transaction" information, the first blockchain platform A sends it to the first carbon digital asset holding node U A .

[0079] Then, a cross-chain bridge is built between the first blockchain A and the second blockchain B, and a hash time lock contract (HTLC) is generated on the first blockchain platform A to lock the carbon digital asset TokenC of the transaction A , and at the same time, the contract embeds the transaction price to ensure that the exchange is carried out at this price on the second blockchain platform B. Specifically, a hash value H(x) is generated on the first blockchain A, where x represents a secret credential that is only disclosed when unlocking on the target chain. The first blockchain A starts a hash time lock contract (HTLC) and requires the recipient to provide the same x on the second blockchain B to unlock the asset. The hash time lock contract can be expressed as: If the transaction is not completed within the preset time T expire , the carbon digital asset will be automatically unlocked and returned to the first carbon digital asset holding node U A . At the same time, a mirrored hash time lock contract is created on the second blockchain B, and based on the market price P of the carbon digital asset transaction market and the cross-chain liquidity pool dynamic balance model, the corresponding carbon digital asset quantity TokenC on the second blockchain B is calculated B , where the cross-chain liquidity pool dynamic balance model is an improved algorithm based on the AMM mechanism. It assumes that there are two assets X and Y in the liquidity pool, and their reserve amounts are R X and R Y , and the transaction fee is γ. Then, the calculation formula for the quantity ΔY of asset X exchanged for asset Y is: where ΔX represents the exchange quantity of asset X, that is, the quantity of asset X taken out or deposited from the liquidity pool. Then, the second blockchain platform B verifies the locked transaction on the first blockchain platform A through an SPV client to ensure that the locked asset quantity and price on the first blockchain platform A are the same as before, and verifies whether the transaction hash and time lock conditions meet the following conditions: where T A represents the locked transaction on the first blockchain A, MerkleProof(TA ) represents the Merkle proof of the locked transaction on the first blockchain A, Block A represents the block storing the locked transaction on the first blockchain A. The second blockchain platform B then requests the secret credential x from the second carbon digital asset holding node U B to unlock the hash time lock. The second carbon digital asset holding node U B submits x to the second blockchain B. The second blockchain platform B transmits x to the first blockchain platform A through a cross-chain communication protocol. The first blockchain platform A automatically verifies x. After the hash time lock is successfully unlocked, an equivalent carbon digital asset TokenC is minted on the second blockchain platform B B and sent to the holding node U B 's account. Among them, TokenC B is equivalent to TokenC A and forms a two-way mapping. Finally, the locked carbon digital asset TokenC on the first blockchain A A is destroyed or frozen. The first blockchain platform A and the second blockchain platform B synchronously update the total amount of carbon digital assets to ensure consistency. And during the synchronization process, a transaction path dynamic optimization algorithm is used to select the optimal data synchronization path to ensure the accurate and timely synchronization of data.

[0080] In addition, the trading platform node adopts atomic swap technology to ensure the security of transactions, that is, either all succeed or all fail, to avoid the loss of carbon digital assets.

[0081] In addition, in order to avoid the repeated registration or transfer of carbon digital assets on multiple chains to ensure the uniqueness and traceability of carbon digital assets, users need to register a distributed identity DID in the cross-chain bridge A , and this identity binds the user's carbon digital assets. When conducting cross-border transactions of carbon digital assets, it is necessary to verify whether the DID of the target chain user A exists and ensure the uniqueness of the asset. Among them, the verification process needs to meet the following conditions: DID A =H(Identity||C A ), where Identity represents the user identity information, C A represents the carbon digital asset on the first blockchain platform A, and C B represents the carbon digital asset on the second blockchain platform B. If the same user DID A already exists on the target chain, the cross-chain transaction is rejected to prevent the repeated transfer of assets. It can be understood that the present invention ensures the uniqueness and traceability of cross-chain assets through DID identity and prevents the repeated registration of carbon digital assets on different chains.

[0082] Optionally, during the cross-border transaction process, the first blockchain and the second blockchain reach a consensus using a PoS+PBFT hybrid consensus mechanism. When the number of transactions between the two blockchains is less than a preset threshold, the PoS consensus mechanism is adopted, and when the number of transactions between the two blockchains is not less than the preset threshold, the PBFT consensus mechanism is adopted. Among them, in the PoS consensus mechanism, the probability calculation formula for node i to become a block-producing node is: Among them, represents the probability that node i becomes a block-producing node, and Stake i represents the stake held by node i, and n represents the total number of nodes participating in the consensus.

[0083] It can be understood that, different from the traditional Proof of Work (PoW) consensus mechanism, the Proof of Stake (PoS) mechanism does not require nodes to compete for the block production right through a large amount of calculations, reducing energy consumption. Because under the PoS mechanism, the probability of a node becoming a block-producing node depends on the stake it holds, rather than computing power. This avoids the high-energy-consuming computing competition for the accounting right like PoW. For a blockchain network with limited resources, especially when the number of transactions is relatively small, it can effectively reduce the operating cost. Moreover, the transaction confirmation speed of the PoS consensus mechanism is relatively fast. In the case of a small number of transactions, the PoS mechanism can quickly determine the block-producing node. Since complex hash calculations are not required, nodes can quickly respond and complete the block production process, significantly shortening the transaction confirmation time compared with the PoW mechanism, improving the transaction processing efficiency, enabling small-value and low-frequency transactions to be confirmed in a timely manner, and enhancing the user experience. Additionally, the PoS mechanism encourages nodes to hold stakes for a long time. The more stakes a node holds, the higher the probability of becoming a block-producing node, which prompts more nodes to participate in the network. Even nodes with relatively small stakes have the opportunity to participate in the consensus. Compared with the trend of computing power centralization in the PoW mechanism, the PoS mechanism can better ensure the decentralized characteristics of the network, enabling more participants to influence network decisions. The Practical Byzantine Fault Tolerance (PBFT) mechanism is suitable for processing a large number of transactions. Under this mechanism, the three stages of pre-prepare, prepare, and commit can quickly reach a consensus, having good adaptability to high-concurrency transaction scenarios. Compared with PoS, it does not rely on the stake ratio of nodes to determine the block-producing node, but quickly confirms transactions through information interaction and voting among nodes, and can process a large number of transaction requests in a short time, meeting the transaction processing requirements in high-traffic scenarios and ensuring the stable operation of the network when the transaction volume is large. Moreover, the PBFT mechanism confirms transactions through the interaction and voting of multiple nodes, and to a certain extent, can tolerate the failures or malicious behaviors of some nodes, ensuring the consistency and reliability of transactions. When the transaction volume is large, ensuring transaction consistency is crucial. PBFT can provide relatively high fault tolerance, preventing transaction inconsistency problems caused by abnormal conditions of some nodes and ensuring the integrity and correctness of blockchain data. Additionally, the block production process and transaction confirmation time of the PBFT mechanism are relatively fixed. In the case of a large transaction volume, its certainty and predictability help the network better plan and manage resources. Nodes can make advance resource allocation and processing preparations according to the process and time characteristics of the PBFT mechanism, avoiding network congestion and uncertainty caused by a sudden increase in the number of transactions and ensuring the stable operation of the network. The present invention adopts a PoS + PBFT hybrid consensus mechanism, which can dynamically switch the consensus algorithm according to the network transaction situation. When the network transaction volume is small, the PoS mechanism is adopted to reduce energy consumption. When the network transaction volume increases, it switches to the PBFT mechanism to ensure fast transaction confirmation and consistency. It is expected that the energy consumption can be reduced by more than 40%, achieving a balance between energy conservation and performance.

[0084] In addition, during the cross-border transaction process, the Merkle tree structure is adopted to ensure data consistency, and the Hash value H of the data A and H B satisfy the following formula: wherein, H A and H B represent the Merkle tree hash values of two blockchains to prove the validity and consistency of the transaction.

[0085] In addition, in the step S3, the second carbon digital asset holding node U B holds the carbon digital asset TokenC after the transaction on the second blockchain B B , and it can apply to the second blockchain B to exchange the held carbon digital asset TokenC B for the legal currency Currency of Country B B . After receiving the request, the second blockchain B calls the exchange rate oracle (Oracle) to obtain the exchange rate E between the second blockchain platform B and the legal currency of Country B in real time real-time , embeds the exchange rate into the transaction contract to ensure that price fluctuations will not affect the transaction. Assuming the quantity of the carbon digital asset TokenC B is N Token , then the quantity N Currency of the legal currency obtained by exchange is calculated by the formula: N Currency = N Token × E real-time . The transaction contract automatically exchanges the carbon digital asset TokenC B for the legal currency according to the real-time exchange rate and sends it to the account of the holding node U B . After the transaction is completed, the status of the carbon digital asset TokenC B on the second blockchain platform B is updated to "exchanged" or "destroyed". At the same time, based on the blockchain, the transaction hash and the transfer path are detailedly recorded, and the on-chain status is synchronously updated to ensure the total amount and transaction transparency of the carbon digital assets. In addition, during the liquidation process, the PoS+PBFT hybrid consensus mechanism is still adopted to ensure the consistency and reliability of the transaction.

[0086] It can be understood that the present invention embeds the exchange rate oracle Oracle in the cross-border transaction, can obtain the exchange rates of multiple countries in real time, realizes the automatic exchange and settlement of the carbon digital asset Token and the currencies of various countries, and adopts the smart contract to automatically execute the exchange process, which is beneficial to improving the efficiency of the cross-border transaction of carbon assets.

[0087] Optionally, as Figure 4 shown, the cross-border transaction method of the carbon digital asset further includes the following content:

[0088] Step S4: Supervise and conduct compliance audits on the cross-border transaction process.

[0089] Specifically, to ensure data security, homomorphic encryption (HE) is used to encrypt transaction data throughout the transaction process, including transaction quantity, transaction price, trading parties, transaction hash, etc. Before encryption, to ensure data integrity, the data is first hashed, and then the hash value is encrypted together with the data. Assume the encryption key is K enc , then the encrypted data C data is calculated as: C data = HE-Encrypt(data||SHA256(data), K enc ), where Encryp() represents the encryption function. Homomorphic encryption allows calculations to be performed on ciphertexts. For example, the regulatory node can calculate the ciphertext value of the total transaction volume without decrypting. Assume C quantity1 and C quantity2 are the encrypted data of two transaction quantities, then the homomorphic addition can be expressed as:

[0090] C total-quantity = HE-Add(C quantity1 , C quantity2 ).

[0091] The decryption key K reg used by the regulatory node is generated by a trusted third party (such as a regulatory agency) using the elliptic curve encryption algorithm, distributed through a secure SSL / TLS channel, stored in a hardware security module (HSM), and updated regularly. The decrypted data D decrypted satisfies: D decrypted = Decrypt(C data , K reg ), where Decrypt() represents the decryption function, enabling the regulatory agency to verify the transaction content of carbon digital assets without disclosing the user's privacy information.

[0092] Meanwhile, in cross-border carbon trading, to comply with the regulations of different countries, the regulatory node needs to audit the compliance of carbon digital assets. Assume the legitimacy of a certain carbon asset transaction is represented by a compliance factor C compliance , and this factor is calculated according to the carbon emission regulations of each country. C compliance = check-regulations(T carbon , jurisdiction), where check-regulations() represents the compliance factor verification function, which performs a legality check based on, T carbon represents the quantity of carbon digital assets, and jurisdiction represents the laws and regulations of the source region and trading region of the carbon digital assets. If the second blockchain platform B feeds back the result C complianceIf it is equal to 1, it is determined that the transaction is compliant; otherwise, it is non-compliant. After the audit result is generated, to ensure its verifiability when stored on the blockchain, a Merkle tree of the audit result is generated, with the root hash being RootHash, and RootHash and the corresponding Merkle proof (MerkleProof) are uploaded to the chain. The audit result deposit hash H audit is uploaded to the chain to form an immutable transaction compliance review record. Future traceability queries can be made through the audit record hash H audit to verify whether the transaction has passed the compliance audit. The verification process can be expressed as: AuditResult represents the audit result, and Record on-chain represents the record on the chain.

[0093] It can be understood that the present invention can also achieve fast and efficient carbon asset transaction auditing and supervision, effectively improving transaction efficiency, reducing on-chain transaction costs, and creating a fair, transparent, and efficient carbon market environment.

[0094] In addition, as Figure 5 shown, another embodiment of the present invention further provides a carbon digital asset cross-border trading system, preferably adopting the carbon digital asset cross-border trading method as described above, including:

[0095] A carbon asset rights confirmation module, used to confirm the carbon assets of the first carbon digital asset holding node based on Internet of Things sensing data, and generate the carbon digital assets of the first carbon digital asset holding node;

[0096] A cross-border trading module, used to enable the first carbon digital asset holding node to conduct cross-border transactions with the second carbon digital asset holding node in the second blockchain based on the carbon digital assets;

[0097] A transaction settlement module, used to enable the second carbon digital asset holding node to conduct transaction settlement on the second blockchain based on the traded carbon digital assets.

[0098] It can be understood that the carbon digital asset cross-border trading system of this embodiment uses Internet of Things sensing devices to collect carbon emission data in real time, can obtain comprehensive and dynamic carbon emission data, is conducive to real-time and accurate monitoring of carbon emission rights, thereby realizing accurate carbon asset rights confirmation, establishing a unified and credible carbon digital asset rights confirmation mechanism, can accurately trace the authenticity and validity of carbon digital assets, and avoids the problems of repeated rights confirmation and false rights confirmation.

[0099] In addition, the carbon digital asset cross-border trading system further includes:

[0100] A supervision and compliance audit module, used to supervise and conduct compliance audits on the cross-border trading process.

[0101] In addition, another embodiment of the present invention further provides an electronic device, including a processor and a memory. A computer program is stored in the memory, and the processor is configured to execute the steps of the method described above by invoking the computer program stored in the memory.

[0102] In addition, another embodiment of the present invention further provides a computer-readable storage medium for storing a computer program for cross-border transactions of carbon digital assets. The computer program, when running on a computer, executes the steps of the method described above.

[0103] The forms of common computer-readable storage media generally include: floppy disks, flexible disks, hard disks, magnetic tapes, any other magnetic media, CD-ROMs, any other optical media, punch cards, paper tapes, any other physical media with a pattern of holes, random access memories (RAMs), programmable read-only memories (PROMs), erasable programmable read-only memories (EPROMs), flash erasable programmable read-only memories (FLASH-EPROMs), any other memory chips or cartridges, or any other media readable by a computer. Instructions can further be transmitted or received by a transmission medium. The term transmission medium can include any tangible or intangible medium that can be used to store, encode, or carry instructions for execution by a machine, and includes digital or analog communication signals or the intangible medium facilitating the communication of the above instructions. The transmission medium includes coaxial cables, copper wires, and optical fibers, which include the wires of a bus for transmitting a computer data signal.

[0104] Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program code. The solutions in the embodiments of the present application can be implemented in various computer languages. For example, object-oriented programming languages such as Java and interpreted scripting languages such as JavaScript.

[0105] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processors of general-purpose computers, special-purpose computers, embedded processors, or other programmable data processing devices to generate a machine, such that the instructions executed by the processors of the computer or other programmable data processing devices generate means for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in one block or multiple blocks.

[0106] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in one block or multiple blocks.

[0107] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in one block or multiple blocks.

[0108] Although the preferred embodiments of the present application have been described, those skilled in the art can make additional changes and modifications to these embodiments once they learn the basic creative concepts. Therefore, the appended claims are intended to be construed to include the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0109] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application is also intended to include these modifications and variations.

[0110] The above description is only for the preferred embodiments of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention can have various changes and alterations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A cross-border trading method for carbon digital assets, characterized in that, Includes the following: Based on IoT sensor data, the carbon assets of the First Carbon Digital Asset holding node are confirmed to generate the carbon digital assets of the First Carbon Digital Asset holding node; The first carbon digital asset holding node conducts cross-border transactions based on carbon digital assets through the first blockchain with the second carbon digital asset holding node in the second blockchain; The second carbon digital asset holding node performs transaction settlement on the second blockchain based on the traded carbon digital assets.

2. The cross-border carbon digital asset trading method according to claim 1, characterized in that The process of confirming the ownership of the carbon assets of the first carbon digital asset holding node based on the IoT sensor data and generating the carbon digital assets of the first carbon digital asset holding node includes the following: Deploy sensor equipment at the carbon emission sources of the First Carbon digital asset holding nodes to collect carbon emission data in real time and pre-process the collected carbon emission data; Perform zero-knowledge verification on pre-processed carbon emission data; The LSTM-Attention neural network model is used to extract features from the preprocessed carbon emission data to obtain feature vectors. The extracted feature vectors are then input into the trained emission reduction efficiency factor prediction model to predict the current emission reduction efficiency factor. The number of carbon assets that have been confirmed is calculated based on the current emission reduction efficiency factor and the collected carbon emission data; The corresponding carbon digital assets are determined based on the number of confirmed carbon assets, and the carbon digital assets are issued to the account of the first carbon digital asset holding node.

3. The cross-border trading method of carbon digital assets according to claim 2, wherein After obtaining the confirmed quantity of carbon assets, the carbon assets are also fragmented, dividing the complete carbon assets into multiple carbon asset fragments.

4. The cross-border trading method of carbon digital assets according to claim 1, characterized in that The process of the first carbon digital asset holding node conducting a cross-border transaction based on the carbon digital asset through the first blockchain with the second carbon digital asset holding node in the second blockchain includes the following: The first carbon digital asset holding node initiates a cross-border transaction request on the first blockchain to the second carbon digital asset holding node in the second blockchain, and dynamically compiles a smart contract based on compliance rules to perform a preliminary compliance check on the cross-border transaction request; The market price of carbon digital asset transactions is calculated based on the supply and demand of carbon digital assets, carbon prices, exchange rates, and taxes; The Second Carbon digital asset holding node receives a cross-border transaction request, dynamically compiles a smart contract based on compliance rules, performs a preliminary compliance check on the cross-border transaction request, and then confirms the transaction request; The carbon digital assets traded on the first blockchain are locked based on a hash time lock contract, and carbon digital assets of equal value are minted on the second blockchain based on a mirrored hash time lock contract and distributed to the account of the second carbon digital asset holding node, and the locked carbon digital assets on the first blockchain are destroyed or frozen.

5. The cross-border trading method of carbon digital assets according to claim 4, characterized in that, The market price of carbon digital asset transactions is calculated based on the following formula: Among them, P market represents the market price of carbon digital asset transactions, D carbon represents the demand for carbon digital assets, S carbon represents the supply of carbon digital assets, P carbon represents the carbon price, E rate represents the exchange rate, T fee represents the tax and fee, and δ represents the adjustment coefficient.

6. The cross-border carbon digital asset trading method according to claim 4, wherein, During cross-border transactions, the first blockchain and the second blockchain use the PoS+PBFT hybrid consensus mechanism to reach consensus. When the number of transactions between the two blockchains is less than the preset threshold, the PoS consensus mechanism is adopted, and when the number of transactions between the two blockchains is not less than the preset threshold, the PBFT consensus mechanism is adopted.

7. The carbon digital asset cross-border trading method according to claim 1, wherein Also included: Conduct supervision and compliance audits on cross-border transaction processes.

8. A cross-border trading system for carbon digital assets, characterized in that, include: The carbon asset rights confirmation module is used to confirm the carbon assets of the first carbon digital asset holding node based on the Internet of Things sensing data, and generate the carbon digital assets of the first carbon digital asset holding node; The cross-border transaction module is used for the first carbon digital asset holding node to conduct cross-border transactions with the second carbon digital asset holding node in the second blockchain based on the carbon digital assets through the first blockchain; The transaction settlement module is used for the second carbon digital asset holding node to conduct transaction settlement on the second blockchain based on the traded carbon digital assets.

9. An electronic device, characterized in that, It includes a processor and a memory. A computer program is stored in the memory. The processor is used to execute the steps of the method according to any one of claims 1 to 7 by calling the computer program stored in the memory.

10. A computer-readable storage medium for storing a computer program for cross-border transactions of carbon digital assets, characterized in that, When the computer program runs on a computer, it executes the steps of the method according to any one of claims 1 to 7.

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