Method and system for auditing forgery using a plurality of audit committees having different proof algorithm

Abstract

A method and system for auditing forgery using multiple audit consensus bodies having different proof methods are provided. A method for auditing forgery using multiple audit consensus bodies according to one embodiment of the present invention is performed by a computing device and comprises the steps of: collecting multiple ledger information from multiple node devices within a blockchain network for electronic notarization; identifying inconsistencies among the multiple ledger information and verifying forgery of the multiple ledger information by an audit network in response to the inconsistencies; and generating a block for updating the ledger information of the multiple node devices based on the verified result. The blockchain network generates a block to be distributed within the blockchain network through a block generation process based on neural consensus proof, and the audit network includes multiple audit consensus bodies having different proof methods, and can verify forgery of the multiple ledger information by voting based on the proof results of the multiple audit consensus bodies.

Description

Technology Field

[0001] The present invention relates to a method and system for auditing forgery in a blockchain network. More specifically, it relates to a method and system for auditing forgery in ledger information with high reliability by utilizing a plurality of audit consensus bodies having different proof methods. Background Technology

[0002] Blockchain is a type of distributed database that utilizes a P2P (Peer-to-Peer) network. A distributed database is a technology that physically distributes data, enabling multiple users to share a large-scale database. As a list of structures that store data, a blockchain allows network participating node devices to store data and, through verification, jointly record and manage ledger data that records transaction information.

[0003] When a new block is created in a blockchain network, the block is verified through a consensus algorithm of multiple participants (node ​​devices) and linked to existing blocks. It is then confirmed as the final ledger containing transaction records and can be distributed and stored. Furthermore, when a transaction occurs on a participating node device, the transaction information is verified through validation and propagated to each node device. Through this process, transaction records—specifically verified transactions—are propagated and distributed for storage. Consequently, in the event of data forgery by some nodes, the authenticity of the tampering can be identified based on the distributed transactions. The security stability of a blockchain increases as the number of users sharing data grows. Blockchain is utilized in various online services, such as cloud computing, in addition to cryptocurrencies like Bitcoin.

[0004] Meanwhile, recent attempts are underway to apply blockchain technology to electronic notarization systems to more reliably prove the integrity of notarized documents. For instance, storing the original document or its hash value on a blockchain makes it safer from hacking compared to existing computer systems, thereby enhancing the reliability of the document creation, management, and distribution processes. Prior art literature

[0005] Korean Patent Publication No. 10-2268700 (Published June 24, 2021) The problem to be solved

[0006] The technical problem to be solved through the embodiments of the present invention is to provide a method and system for auditing forgery using multiple audit consensus bodies, which further enhances reliability and security by auditing whether ledger information stored in a blockchain network has been tampered with, and by performing the audit of forgery and restoration of the originality of the ledger information using multiple audit consensus bodies having different proof methods.

[0007] Another technical problem to be solved through the embodiments of the present invention is to provide a method and system for auditing forgery using multiple audit consensus bodies of a blockchain network, which more reliably guarantees the integrity of data stored in a blockchain by verifying whether ledger information has been tampered with using audit nodes, and enables the use of blockchain technology even in public ledgers requiring high data stability and reliability.

[0008] Another technical problem to be solved through the embodiments of the present invention is to provide a method and system for auditing forgery using multiple audit consensuses that can guarantee the integrity of blockchain network data by enabling a non-random consensus proof-based blockchain network to be used as a random consensus proof-based blockchain network, and by auditing the ledger information of the random consensus proof-based blockchain network through an audit node operating with a multiple consensus algorithm.

[0009] The technical problems of the present invention are not limited to those mentioned above, and other unmentioned technical problems will be clearly understood by a person skilled in the art from the description below. means of solving the problem

[0010] A method for auditing forgery using a plurality of audit consensus bodies according to embodiments of the present invention, for solving the above technical problem, is performed by a computing device and comprises the steps of: collecting a plurality of ledger information from a plurality of node devices within a blockchain network for electronic notarization; identifying a discrepancy between the plurality of ledger information and verifying forgery of the plurality of ledger information by an audit network in response to the discrepancy; and generating a block for updating the ledger information of the plurality of node devices based on the verified result. The blockchain network generates a block to be distributed within the blockchain network through a block generation process based on neural consensus proof, and the audit network includes a plurality of audit consensus bodies having different proof methods, and can verify forgery of the plurality of ledger information by voting based on the proof result of the plurality of audit consensus bodies.

[0011] A forgery audit system using a plurality of audit consensus bodies according to embodiments of the present invention for solving the above technical problem comprises: a blockchain network for electronic notarization including a plurality of node devices that perform a block generation process based on neural consensus proof according to preset conditions; and an audit network that identifies discrepancies between a plurality of ledger information collected from the plurality of node devices, verifies forgery of the plurality of ledger information based on the result of identifying the discrepancies, and replies a first ledger information whose integrity has been verified to the blockchain network; wherein the blockchain network generates a block for updating the ledger information of the plurality of node devices based on the first ledger information, and the audit network includes a plurality of audit consensus bodies having different proof methods, and can verify forgery of the plurality of ledger information by voting based on the proof results of the plurality of audit consensus bodies. Effects of the invention

[0012] According to the embodiments of the present invention described above, the reliability and safety of the audit of tampering can be further enhanced by auditing whether ledger information stored in a blockchain network has been tampered with, using a plurality of audit consensus bodies having different proof methods.

[0013] In addition, by using audit nodes to verify whether ledger information has been tampered with, the integrity of data stored on the blockchain can be more reliably guaranteed, and blockchain technology can be utilized in public ledgers that require high data stability and reliability.

[0014] In addition, by converting the existing non-random consensus proof-based blockchain network into a random consensus proof-based blockchain network while maintaining its infrastructure and utility as much as possible, it is possible to provide an efficient and equitable distributed consensus process based on neural consensus proof while preventing the waste of resources and social costs.

[0015] The technical problems of the present invention are not limited to those mentioned above, and other unmentioned technical problems will be clearly understood by a person skilled in the art from the description below. Brief explanation of the drawing

[0016] FIG. 1 is a schematic diagram showing the entire system according to an embodiment of the present invention. FIG. 2 is a diagram showing the neural consensus proof-based blockchain network (1000) illustrated in FIG. 1 in more detail. FIG. 3 is a block diagram showing the detailed configuration of a node device (100) according to one embodiment of the present invention. FIG. 4 is a conceptual diagram illustrating the neural consensus proof module cluster configuration and block generation process according to one embodiment of the present invention. FIG. 5 is a flowchart for explaining the operation method of a node device (100) according to one embodiment of the present invention. FIGS. 6 to 9 are drawings illustrating step-by-step data processed by a consensus proof module node device (100) according to an embodiment of the present invention. FIG. 10 is a flowchart for explaining the operation method of a node device (100) according to another embodiment of the present invention. FIG. 11 is a flowchart for explaining the operation method of a node device (100) according to another embodiment of the present invention. FIG. 12 is a diagram illustrating a ledger information forgery audit system using a plurality of audit consensus bodies according to one embodiment of the present invention. FIG. 13 is a diagram showing the configuration and operation method of the audit network (2000) of FIG. 12 in more detail. FIG. 14 is a block diagram showing the detailed configuration of an audit node (300) according to one embodiment of the present invention. FIG. 15 is a flowchart illustrating a method for auditing ledger information forgery using a plurality of audit bodies according to an embodiment of the present invention. FIG. 16 is a flowchart illustrating an embodiment that further specifies step S403 of FIG. 15. FIG. 17 is a block diagram illustrating the hardware configuration of a computing device used to implement various embodiments of the present invention. Specific details for implementing the invention

[0017] ** This patent application includes research conducted with support from the Korea Internet & Security Agency (KISA) under the 2023 Blockchain Public Sector (Dissemination Project) "Advancement of Blockchain-based Electronic Notarization System" project. **

[0018] Hereinafter, embodiments of the present invention will be described in detail with reference to the attached drawings. The advantages and features of the present invention, and the methods for achieving them, will become clear by referring to the embodiments described below in detail together with the attached drawings. However, the technical concept of the present invention is not limited to the following embodiments but can be implemented in various different forms. The following embodiments are provided merely to complete the technical concept of the present invention and to fully inform those skilled in the art of the scope of the present invention, and the technical concept of the present invention is defined only by the scope of the claims.

[0019] It should be noted that when assigning reference numerals to the components of each drawing, the same components are assigned the same reference numeral whenever possible, even if they are shown in different drawings. Furthermore, in describing the present invention, if it is determined that a detailed description of related known components or functions could obscure the essence of the invention, such detailed description is omitted.

[0020] Unless otherwise defined, all terms used herein (including technical and scientific terms) may be used in a meaning commonly understood by those skilled in the art to which the present invention pertains. Furthermore, terms defined in commonly used dictionaries are not to be interpreted ideally or excessively unless explicitly and specifically defined otherwise. The terms used herein are for describing embodiments and are not intended to limit the present invention. In this specification, the singular form includes the plural form unless specifically stated otherwise in the text.

[0021] Additionally, terms such as first, second, A, B, (a), (b), etc., may be used when describing the components of the present invention. These terms are intended merely to distinguish the components from other components, and the nature, order, or sequence of the components is not limited by such terms. Where it is stated that a component is "connected," "combined," or "joined" to another component, it should be understood that the component may be directly connected or joined to the other component, but that another component may also be "connected," "combined," or "joined" between each component.

[0022] Meanwhile, in this invention, "originality" has the same meaning as "integrity," and "originality" and "integrity" will be used interchangeably depending on the context.

[0023] FIG. 1 is a schematic diagram illustrating an entire system according to an embodiment of the present invention. Referring to FIG. 1, external data (2) for electronic notarization output through an electronic notarization system (1) can be carried in a transaction (3, or transaction data) and stored in a neural consensus proof-based blockchain network (1000) included in a ledger information forgery audit system (4). The neural consensus proof-based blockchain network (1000) is composed of a plurality of node devices, and the plurality of node devices form a neural consensus proof module cluster to verify the integrity of the ledger information of each node device through a consensus algorithm.

[0024] Accordingly, even if the ledger information of some node devices is damaged due to hacking or other reasons, it is immediately restored to the same content as the original by the consensus algorithm of the neural consensus proof module cluster, so the integrity of the data stored in the blockchain network (1000) can be guaranteed.

[0025] However, even if the blockchain network (1000) has a consensus algorithm that can restore originality (or integrity), in some extreme situations, it may not be able to restore the damaged original on its own. For example, if a 51% attack on the blockchain network (1000) succeeds and the incorrect ledger information is considered the original, it may be difficult for the blockchain network (1000) itself to restore the damaged original.

[0026] To remedy this problem, the ledger information falsification audit system (4) audits the falsification of ledger information of node devices within the blockchain network (1000) through the audit network when it is determined that the originality of the blockchain network (1000) has been compromised, and provides the correct ledger information stored in the audit network (2000) to the blockchain network (1000) so that the originality of the ledger information of each node device within the blockchain network (1000) can be restored.

[0027] Hereinafter, the detailed configuration and operation method of the neural consensus proof-based blockchain network (1000) and audit network (2000) for auditing the falsification of such ledger information will be described with specific embodiments.

[0028] FIG. 2 is a diagram showing the neural consensus proof-based blockchain network (1000) illustrated in FIG. 1 in more detail.

[0029] A blockchain network (1000) according to an embodiment of the present invention may be configured as a blockchain network of a mesh network topology by one or more node devices connected via a wired or wireless network. The node devices may be connected to the blockchain network through input / output devices and may exchange data. The blockchain network (1000) may include various electronic systems as node devices, such as mobile devices like mobile phones, smartphones, PDAs, tablet computers, and laptop computers; computing devices like personal computers, tablet computers, and netbooks; or electronic products such as televisions, smart televisions, and security devices for gate control.

[0030] Additionally, multiple node devices (100) may be equipped with communication modules for accessing a blockchain network. The blockchain network may be implemented as a wired network, such as a Local Area Network (LAN), a Wide Area Network (WAN), or a Value Added Network (VAN). Furthermore, the blockchain network may be implemented as any type of wireless network, such as a mobile radio communication network, a satellite communication network, Bluetooth, Wibro (Wireless Broadband Internet), HSDPA (High Speed ​​Downlink Packet Access), Wi-Fi, LTE (Long Term Evolution), etc. If necessary, the blockchain network may be a network that combines wired and wireless networks.

[0031] And, each node device (100) can register account information corresponding to its node connection in transaction ledger data shared via the network in a cloud manner. And, if a transaction of encryption information to create a blockchain is required, each trader terminal can propagate transaction information to be recorded in the transaction ledger data to each trader terminal.

[0032] And, in accordance with the corresponding mutual verification process, the transaction ledger data is updated and the information is shared, thereby allowing the transaction of cryptographic information for creating a blockchain to be processed.

[0033] Here, the transaction ledger data can be linked with blockchain data having a structure in which multiple blocks are sequentially connected according to their creation order, such that for each block corresponding to a certain time or unit, the current block includes the hash value of a previously created block. Accordingly, the verification of whether the transaction ledger data has been tampered with can be easily handled by verifying the hash value of the blockchain.

[0034] The security stability of such a blockchain can be established through the system participation of data sharers. Accordingly, transaction information blocks containing details of sharing between each sharer terminal connected to the blockchain network and details of cryptographic information issuance / transactions for creating the blockchain can be stored sequentially, and transaction verification processing to sequentially blockchain hash values ​​to prevent tampering can be performed in a distributed manner at each transaction terminal.

[0035] A non-random consensus blockchain network (200) is a non-random consensus proof-based blockchain network (200) such as PoW (Proof-of-Work) and PoS (Proof-of-Stake), and blockchain networks such as Bitcoin and Ethereum may be applicable.

[0036] In contrast, a plurality of node devices (100) can form a neural consensus proof module cluster, and the neural consensus proof module cluster can form a new block by combining neural consensus validity verification data based on a random consensus proof method, and can process the formed new block to be propagated through a non-random consensus blockchain network (200).

[0037] Accordingly, in a non-random consensus blockchain network (200), the re-propagated block data is shared within the network, and the next block can be generated again by a node device (100) that constitutes a neural consensus proof module cluster. Since no separate proof such as PoW or PoS is required in this process, the blockchain network system (1000) can build a new random consensus that can implement decentralization in a non-competitive manner.

[0038] That is, according to an embodiment of the present invention, a plurality of node devices (100) can be provided to form a network that enables a random consensus proof-based blockchain network based on a blockchain network by constructing a neural consensus proof module cluster (100) that allows an existing blockchain network (200) based on a non-random consensus proof to be used as a random consensus proof-based blockchain network (1000), thereby controlling the existing blockchain network based on PoW or PoS methods so that it is not operated in a PoW or PoS manner anymore, or controlling it to be operated restrictively according to the minimum number of nodes of a Byzantine fault-tolerant consensus.

[0039] Accordingly, by converting the existing non-random consensus proof-based blockchain network into a random consensus proof-based blockchain network while maintaining its infrastructure and utility to the maximum extent, it is possible to provide an efficient and equitable distributed consensus process based on neural consensus proof while preventing the waste of resources and social costs. Here, the participation credentials for the random consensus may utilize a nonce chain and hash verification process based on one-time random numbers, but this is merely an example, and the designation or participation credentials for the random consensus may be possible in various other ways.

[0040] Referring to FIGS. 3 and FIGS. 4 for a more detailed description of the plurality of node devices (100), FIG. 3 is a block diagram showing the detailed configuration of a node device (100) according to an embodiment of the present invention, and FIG. 4 is a conceptual diagram for explaining the neural consensus proof module cluster configuration and block generation process according to an embodiment of the present invention.

[0041] Node devices (100) of a blockchain network (1000) according to an embodiment of the present invention may be included in a neural consensus proof module cluster for configuring the next block by a random node selection process, and each may include a neural consensus proof module (110) for performing a random consensus proof process according to an embodiment of the present invention, which is included in such a neural consensus proof module cluster.

[0042] Additionally, the node device (100) is connected to a non-random consensus blockchain network (200) and may include a blockchain service unit (120) that performs the processing of the shared propagation process of the next block configured by the random consensus proof process through the non-random consensus blockchain network (200).

[0043] Accordingly, in an embodiment of the present invention, the node devices (100) may be node devices (100) that participate in a non-random consensus blockchain network (200) and are selected by a random consensus selection process and are selectively granted the authority to generate each block according to the consensus agreement, thereby allowing a random consensus blockchain network system (1000) to be independently constructed.

[0044] Additionally, as illustrated in FIG. 4, the node devices (100) can selectively perform the functions of a fourth node device which is a general node, a third node device which is a participation node, a second node device which is a council node, and a first node device which is a committee node.

[0045] A neural consensus proof mode cluster can be constructed based on a third node device, which is a terminal registered as a participating node. The participating node, which is the third node device, can verify eligibility for participation based on the next consensus selection information identified in the consensus validity verification data of a newly propagated block, and the second node device may be a terminal that processes the operation of the council node function by checking whether it has been selected as a council node based on the verification result. The first node device may be a terminal that processes the operation of the committee node function by checking whether it has been selected as a committee node based on the verification result.

[0046] In the case of a node device (100) selected as a council node, it can perform a candidate block presentation and consensus process as in the second node device shown in FIG. 4, and in the case of a node device (100) selected as a committee node, it can determine a consensus block and collect signature information to perform a process of configuring and distributing consensus validation data for the next block. Here, the consensus validation data may include consensus process verification data, multi-signature information, and next consensus selection information, and this can be propagated through a pre-established non-random consensus blockchain network (200).

[0047] According to this new block configuration and propagation process, the proof process of the existing non-random consensus blockchain network (200) may be restricted, and the creation of the next block based on Pow or Pos proof between node devices (100) may be processed only in exceptional cases where the number of some nodes falls short of the number set based on the Byzantine Tolerance Allowance (PBFT) threshold.

[0048] Meanwhile, the participation qualification and verification information of such a node device (100) can be calculated based on random values ​​computed for each individual node according to the registration of participating nodes, and can be mutually disclosed and verified, and a nonce chain can be used as described above. For example, depending on what value the node device (100) has its qualification verification value obtained through hash processing using the nonce value included in the next consensus selection information and the height value of the current block, the node device (100) can be determined as at least one of a participating node, a council node, a committee node, or a chair node.

[0049] Also, as illustrated in FIG. 3, a node device (100) according to an embodiment of the present invention includes a device information setting unit (111), a node information setting unit (112), a validity verification processing unit (113), a qualification verification processing unit (114), a consensus node function unit (115), and a data interface unit (116).

[0050] The device information setting unit (111) acquires and stores / manages device information of a terminal (100) in which a neural consensus proof module (110) is installed. Here, the device information may include at least one of the terminal (100)'s node name information, device address information, device performance information, device reliability information, and network usage information. Such device information may be used for identifying or constructing a neural consensus proof module cluster, performing a voting consensus process, etc.

[0051] The node information setting unit (112) sets node information for the non-random consensus blockchain network (200) and the registration of participating nodes. The set node information may include blockchain network client address information, and the terminal (100) can access the blockchain network through the blockchain network client address information to obtain or share block information.

[0052] The validity verification processing unit (113) obtains new block data propagated through the non-random consensus blockchain network (200), extracts validity verification data from the new block data, and obtains neural consensus designation information of the next block generated based on a random consensus proof process according to the verification processing of the validity verification data.

[0053] Additionally, the consensus node function (115) is selectively driven based on the neural consensus designation information of the next block to generate validity verification data for the next block, and can selectively drive at least one of the chair node function (1151), the council node function (1152), and the committee node function (1153). The chair node function (1151) can be selectively driven by comparing at least a portion of the neural consensus designation information and the nonce value of the designated node device (100), but the present invention is not limited to this selection method.

[0054] First, the chair node function unit (1151) can perform a chair process corresponding to the council and committee nodes, and can collect delegation information and participation qualification verification information of valid transaction blocks obtained from the transaction pool of the blockchain network from the council nodes, as well as next block consensus candidate information. Accordingly, at least 3f + 1 (f is a natural number) council nodes can be selected for the next block, and at least 2f + 1 committee nodes can be selected.

[0055] And, the council node function unit (1152) can transmit delegation information and participation qualification verification information of a valid transaction block obtained from the transaction pool of the non-random consensus blockchain network (200) to the node device (100) where the chairman node function unit (1151) is operated.

[0056] And, the chair node function unit (1151) can select a block that matches more than the consensus quorum of the council node among the transaction blocks proposed by the council node as a candidate block, and transmit a message requesting partial signature processing of a multi-signature area representing consensus on the candidate block to the node devices (100) in which the committee node function unit (1153) is driven. For example, the chair node function unit (1151) can determine a transaction data candidate block that matches f+1 of 2f+1 transaction data candidate blocks and transmit a message requesting partial signature processing of a multi-signature area to the committee node function unit (1153), and the node device (100) in which the committee node function unit (1153) is driven can process a partial signature representing consensus corresponding to the candidate block and transmit it to the node device (100) in which the chair node function unit (1151) is driven.

[0057] Accordingly, the chair node function unit (1151) verifies a candidate block for which multi-signature processing has been completed in accordance with the committee's consensus and determines it as a distribution block, and generates validation data corresponding to the consensus process and combines it with the distribution block to create a new block.

[0058] The data interface unit (116) can convert the newly generated block into the format of a non-random consensus blockchain network (200) and transmit it to the blockchain service unit (120).

[0059] And, the blockchain service unit (120) can process the new block through a non-random consensus blockchain network (200), and the new block can be not only propagated through the non-random consensus blockchain network (200) but also added to a transaction data memory pool according to the operation of the transaction data management unit (121).

[0060] Meanwhile, although not described, the node device (100) may include memory that can be utilized by the aforementioned blockchain service unit (120) and neural consensus proof module (110). The memory may contain instructions that can be read from a computer, and the blockchain service unit (120) and neural block module (110) may perform the aforementioned operations as the instructions stored in the memory are executed on a processor. The memory may be volatile memory or non-volatile memory.

[0061] The memory may include a storage device to store user data. The storage device may be an eMMC (embedded multimedia card), an SSD (solid state drive), a UFS (universal flash storage), etc. The storage device may include at least one non-volatile memory device. The non-volatile memory device may be a NAND flash memory, a vertical NAND flash memory (VNAND), a NOR flash memory, a resistive random access memory (RRAM), a phase-change memory (PRAM), a magnetoresistive random access memory (MRAM), a ferroelectric random access memory (FRAM), a spin transfer torque random access memory (STT-RAM), etc.

[0062] FIG. 5 is a flowchart for explaining the operation method of a node device (100) according to an embodiment of the present invention.

[0063] Referring to FIG. 5, when a new block data propagated through a pre-established non-random consensus blockchain network (200) is obtained by a node device (100) according to an embodiment of the present invention (S101), a validity verification processing unit (113) extracts validity verification data from the new block data and obtains consensus designation information based on the verification processing of the validity verification data (S103).

[0064] The validity verification processing unit (113) can designate neural consensus information of the next block generated based on a random consensus proof process according to the verification processing of the validity verification data, and as described above, the validity verification data may include consensus process verification data corresponding to the random consensus proof process.

[0065] For example, the consensus process verification data may include multi-signature data formed by combining nonce chain-based credential hash data and partial signatures of said council nodes, as membership verification information for council nodes processing consensus on transaction data. Additionally, the neural consensus designation information for the next block may include nonce information for verifying the eligibility to participate in the neural consensus corresponding to the next block.

[0066] Afterwards, the node device (100) determines whether it is selected as a node constituting a neural consensus proof cluster node for the next block (S107), and if selected, checks whether it is a chair node based on consensus designation information (S109).

[0067] If not designated as a chair node, delegation information and participation qualification verification information of a valid transaction block obtained from the transaction pool of the blockchain network according to each qualification may be transmitted to the council chair node (S113).

[0068] Accordingly, the node device (100) in which the chairman node function unit (1151) is activated can collect delegation information and next block consensus candidate information from other nodes (S115).

[0069] Additionally, the node device (100) in which the chair node function unit (1151) is activated determines the agreed-upon candidate block from the node device (100) in which the council node function unit (1152) is activated, and transmits a message to the committee member node requesting partial signature processing of a multi-signature area representing the consensus on the candidate block (S117).

[0070] Then, the node device (100) in which the chair node function unit (1151) is activated verifies a candidate block that has completed multi-signature processing according to the committee consensus and determines it as a distribution block (S119), generates validation data and combines it with the distribution block to create a new block (S121), registers the combined new block in the transaction pool of the non-random consensus blockchain network (200), and propagates the new block through the established non-random consensus blockchain network (200) (S123).

[0071] FIGS. 6 to 9 are drawings illustrating step-by-step data processed by a consensus proof module node device according to an embodiment of the present invention.

[0072] Figure 6 illustrates delegation information transmitted to the chair node during the delegation request stage for the configuration of the current block, and the delegation information may include a nonce value corresponding to the current block height, Qi value information that each council node intends to use for multi-signature, transaction data, information on the next consensus council candidate, and a nonce value of the next block height.

[0073] Also, FIG. 7 illustrates candidate block information transmitted from the chair node to the committee node during the preparation phase. The candidate block information may include header information including a Merkle root, candidate block transaction data, information designating the next consensus body, multi-signature request data (Q data incorporating Qi, public key Pk), and verification data. The verification data may include bitmap information capable of identifying the server information that proposed the transaction data, which enables the chair node to prevent cases proposed by itself in advance.

[0074] Additionally, FIG. 8 illustrates partial signature data propagated from the committee node to the chair node in the process where committee verification is handled, and the chair node can integrate the partial signature data Si to produce signature completion data S.

[0075] Meanwhile, FIG. 9 illustrates the configuration of a new block generated and propagated according to an embodiment of the present invention, wherein the new block may include header information, transaction block information, and validity verification data. As previously described, the validity verification data may include information on designating the next consensus body, information on completed multi-signatures, and various information capable of proving the consensus process and eligibility for participation. Additionally, the header information may also include a Merkle Root value for validating the block data itself.

[0076] Accordingly, the validity verification processing unit (113) first verifies the consensus process by verifying the multi-signature information, then verifies the Merkle root value of the header to verify it a second time, and verifies it a third time by comparing it with the Merkle root value calculated again using the transaction block information, thereby enabling the processing of a secure transaction block.

[0077] FIG. 10 is a flowchart illustrating a method of operation of a node device according to another embodiment of the present invention.

[0078] Referring to FIG. 10, a node device (100) according to another embodiment of the present invention first identifies the number of council and committee nodes of the next neural consensus body (S201).

[0079] And, the node device (100) determines whether the pre-set consensus quorum is not met according to the minimum allowable number of nodes tolerant to Byzantine.

[0080] For example, the consensus quorum can be determined by the maximum Byzantine number (maximum allowed number of malicious nodes) that can be selected by the node selection probability P corresponding to the number of participating nodes N, and the number of council nodes must be at least 3f+1 (f is a natural number) and the number of committee nodes must be at least 2f+1 to satisfy the consensus quorum.

[0081] If the number of the above consensus nodes falls short of the quorum of the neural consensus council and committee pre-set according to the minimum allowable number of nodes for Byzantine tolerance, the node device (100) performs an optional exception processing in which the validation data of the next block is formed in the PoW (Proof of Work) or PoS (Proof of Stake) method (S205).

[0082] On the other hand, if the number of the above consensus nodes is greater than or equal to the quorum of the neural consensus council and committee pre-set according to the minimum allowable number of nodes tolerant to Byzantine, the PoW (Proof of Work) or PoS (Proof of Stake) process of the above non-random consensus proof-based blockchain network can be restricted, and a neural consensus can be formed using the process of FIG. 5 described above, and validity verification data can be formed to create and propagate a new block (S203).

[0083] FIG. 11 is a flowchart illustrating a method of operation of a node device according to another embodiment of the present invention.

[0084] Referring to FIG. 11, the identification or construction of a neural consensus proof module cluster and the execution of a voting consensus process according to another embodiment of the present invention can be used to quickly generate the next block to ensure continuity in the event of a failure of a non-random consensus blockchain network (200).

[0085] Typically, in the case of non-random consensus methods such as proof of work or proof of stake like Ethereum, problems such as timeouts in the block generation cycle or unstable consensus due to duplicate transactions occur due to abnormal service operation or overload. As a result, the current non-random consensus blockchain network (200) does not sufficiently guarantee the continuity of block generation and is vulnerable to failures, such as service suspension or hard fork.

[0086] Accordingly, the identification or construction of a neural consensus proof module cluster and the execution of a voting consensus process according to an embodiment of the present invention can also be applied in a manner that ensures continuity by being performed complementarily in the event of a failure in the operation of an existing non-random consensus blockchain network (200).

[0087] This can be implemented without building a separate infrastructure by configuring one or more of the node devices constituting the existing non-random consensus blockchain network (200) to operate as a node device (100) constituting the aforementioned neural consensus proof module cluster when a pre-configured failure condition occurs.

[0088] More specifically, referring to FIG. 11, a node device (100) according to an embodiment of the present invention may be a node device that constitutes a non-random consensus blockchain network (200), and may be configured as a terminal that operates as a node device (100) that constitutes a neural consensus proof module cluster when a preset next block consensus failure condition is met, and constructs neural consensus-based validity verification data and propagates it as the next block.

[0089] For such terminal configuration, the node device (100) can be driven as a node device (100) that constitutes a pre-configured neural consensus proof module cluster, and unlike the switching operation of the aforementioned existing blockchain, it can be driven in a continuity guarantee mode for continuity guarantee.

[0090] For example, the node device (100) can be operated in either a network switching mode, which converts the existing non-random consensus blockchain network (200) into a random consensus blockchain network as described above, or a continuity guarantee mode, which is operated auxiliaryly in the event of a failure of the existing non-random consensus blockchain network (200), and FIG. 11 explains the operation when operating in the continuity guarantee mode.

[0091] First, the node device (100) performs the next block consensus process on a normal non-random consensus blockchain network (200) (S301).

[0092] Then, the node device (100) determines whether the next block consensus failure condition applies (S303).

[0093] Here, the following block consensus failure conditions may be pre-set with various conditions, and preferably, a timeout condition in which a block is not generated during a first period may be used. For example, the first period may be the same as the second period, which is a timeout period defined in the proof-of-work or proof-of-stake process of a non-random consensus blockchain network (200).

[0094] In addition, considering the speed of the operation, the first time may be set to a shorter time than the second time so that the neural consensus proof module cluster configuration is processed first, faster than the timeout of the non-random consensus blockchain network (200).

[0095] Additionally, the following block consensus failure conditions may include service suspension. For example, in the event of a service suspension of a non-random consensus blockchain network (200) due to a hard fork or a temporary service operation problem, auxiliary block generation processing may be configured to be performed continuously according to the neural consensus proof module cluster configuration.

[0096] If the failure condition for the next block consensus is not met, non-random consensus-based validation data is generated on the non-random consensus blockchain network (200) in a manner such as a normal proof of work or proof of stake (S304).

[0097] And, in the event of a failure condition for the next block consensus, the aforementioned node device (100) can be operated as a node device (100) constituting a neural consensus proof module cluster and performs a random method neural consensus proof module cluster constituting process and a consensus process based thereon as described in FIGS. 4 and 5 (S305).

[0098] If consensus based on the neural consensus proof module cluster is completed (S307), the node device (100) constructs validation data based on the neural consensus proof, and based on the constructed validation data, verifies the validity of the data between the previous block and the next block constructed in the non-random consensus blockchain network (200) (S309).

[0099] Here, for data validation between the previous block and the next block, specific block height information, previous block information, and next block information may be used, and through validation based thereon, block generation of a non-random consensus format that can be used in a non-random consensus blockchain network (200) may be carried out.

[0100] Afterwards, the node device (100) generates the next consensus block based on the non-random consensus-based validation data from step S304 or the neural consensus proof-based validation data verified in step S309 (S311).

[0101] For example, the node device (100) may generate the next block containing neural consensus proof-based validation data, but may generate the next block of a non-random consensus format verified according to step S309. More specifically, the node device (100) may generate the next block such that consensus on the non-random consensus blockchain network (200) is restarted starting from a block of height 110 when the current latest block height is 100.

[0102] And, the node device (100) propagates the generated block as the next block of the non-random consensus blockchain network (200) (S313).

[0103] According to the process processing of such a node device (100), a neural consensus proof-based block generation process is performed to be operated as an auxiliary process in the event of a failure in a non-random consensus blockchain network (200) of a proof-of-work or proof-of-stake method such as Ethereum or Bitcoin, thereby ensuring sufficient continuity of service.

[0104] FIG. 12 is a diagram illustrating a ledger information tampering audit system using a plurality of audit consensus bodies according to an embodiment of the present invention. In this embodiment, when the originality is compromised in the neural consensus proof-based blockchain network (1000) described above, an embodiment is described in which the tampering is audited through an audit network (2000), and the originality of the blockchain network (1000) is restored using the audit ledger information of the audit network (2000).

[0105] In this embodiment, the audit network includes a plurality of audit nodes (300), and the plurality of audit nodes (300) may form a plurality of audit councils operating in different certification methods.

[0106] In this case, multiple audit nodes (300) are divided among multiple audit councils, and each audit council generates its own audit block by each proof method.

[0107] In the forgery audit system (or ledger information forgery audit system) using multiple audit consensus bodies illustrated in FIG. 12, when electronic notarization is performed and external data is generated, the external data is provided to the blockchain network (1000) and the audit network (2000), respectively. The blockchain network (1000) updates the ledger information of each of the multiple node devices (100) with the ledger information containing the external data through a neural consensus body proof-based block generation process, and the audit network (2000) updates the multiple audit ledger information corresponding to each of the multiple audit consensus bodies with the audit ledger information containing the external data through a block generation process for each of the multiple audit consensus bodies. Through this method, the multiple audit consensus bodies of the audit network (2000) update the latest blocks to have the same ledger information as the blockchain network (1000).

[0108] In one embodiment, the plurality of ledger information may include an electronic notarized document or a hash value extracted from the electronic notarized document.

[0109] Under these conditions, if tampering occurs with the ledger information of the blockchain network (1000), the tampering with the ledger information of the blockchain network (1000) can be verified and the originality restored using the audit ledger information stored in the audit network (2000).

[0110] First, in order to determine whether the authenticity of the neural consensus proof-based blockchain network (1000) has been compromised, ledger information (10) of each of the multiple node devices (100) constituting the neural consensus proof module cluster of the neural consensus proof-based blockchain network (1000) is extracted. Then, the extracted multiple ledger information (10) is compared with one another. At this time, if a discrepancy is found between the multiple ledger information (10), the ledger information of the multiple node devices (100) is considered to have been compromised, and a request for verification of ledger information tampering is made to the audit network (2000) within the audit network (2000).

[0111] Meanwhile, when verifying integrity through a conventional consensus algorithm, if 51% consensus is not achieved for multiple ledger information (10), the ledger information is considered to be corrupted. However, in this embodiment, if there is even one ledger information among the multiple ledger information (10) that is inconsistent with other ledger information (i.e., if one ledger information among the multiple ledger information is different from other ledger information), the ledger information is determined to be corrupted and a request for verification of tampering with the ledger information is transmitted. This is because, if a 51% attack on multiple ledger information (10) is successful, there is a possibility that the ledger information is corrupted even if 51% or more of consensus is achieved. In this case, the consensus process for the multiple ledger information (10) alone cannot correctly determine whether the ledger information is corrupted. Therefore, in this embodiment, if there is even one ledger information among the multiple ledger information (10) that is inconsistent with other ledger information, the ledger information is determined to be corrupted.

[0112] If it is determined that the ledger information of the blockchain network (1000) has been damaged, a request for verification of falsification of the ledger information is sent to the audit network (2000), and the audit network (2000) verifies the falsification of multiple ledger information (10) through multiple audit nodes (300) and then sends back the result of the verification of the falsification of the ledger information.

[0113] To explain this in more detail, multiple audit nodes (300) form multiple audit consensus bodies, and multiple audit nodes (300) may be divided among multiple audit consensus bodies.

[0114] Each of the multiple audit consensus bodies is an audit consensus body with a different proof method, and proves the audit ledger information corresponding to each of the multiple audit consensus bodies (i.e., the audit ledger information held by the audit nodes belonging to each audit consensus body) using its own proof method.

[0115] And, among the multiple audit ledger information verified by each audit council, the audit ledger information with the largest number of verifications is determined as the first audit ledger information with proven authenticity. That is, each audit council verifies the authenticity of the audit ledger information it possesses, and based on the results of such verification, the audit ledger information whose authenticity is verified by the largest number of audit councils is determined as the aforementioned first audit ledger information (determination of the first audit ledger information by voting).

[0116] If all audit councils have verified the same Audit Ledger Information A, then Audit Ledger Information A is determined as the first Audit Ledger Information. Or, if 70% of the audit councils verify Audit Ledger Information A and 30% of the audit councils verify Audit Ledger Information B, then Audit Ledger Information A, whose authenticity is verified by a larger number of audit councils, is determined as the first Audit Ledger Information.

[0117] In one embodiment, each of the different proof methods of the plurality of audit consensus may be a proof method performed by any one of the following algorithms: PoW (Proof of Work), PoS (Proof of Stake), dPoS (delegate Proof of Stake), zero-knowledge proof, PBFT (Practical Byzantine Fault Tolerance), and a neural consensus proof-based random consensus algorithm.

[0118] Thus, configuring the proof methods of multiple audit consensus bodies differently is intended to enhance the security of the audit network (2000). In blockchain technology, each proof method has unique advantages and disadvantages, and the resulting vulnerabilities may also differ. Accordingly, if the proof methods of multiple audit consensus bodies are all identical, they expose the same vulnerabilities to external attacks, thereby increasing the likelihood that multiple audit consensus bodies will be attacked simultaneously. However, as in the present invention, if the proof methods of multiple audit consensus bodies are configured differently, the vulnerabilities of each audit consensus body also differ, thereby minimizing the case where all audit consensus bodies are attacked simultaneously by external attacks. Furthermore, even if an attack on some audit consensus bodies is successful, the remaining audit consensus bodies can remain safe, allowing the originality of the entire audit network (2000) to be restored and maintained.

[0119] Meanwhile, when the first audit ledger information whose authenticity has been proven is determined, the audit network (2000) can compare the first audit ledger information with the multiple ledger information (10) to verify the falsification of the multiple ledger information (10) and provide a response regarding the verification result. To this end, one or more audit nodes (300) receive transaction data identical to the transaction data provided to the blockchain network (1000), and record the transaction data in the audit ledger information of each of the one or more audit nodes (300) through the block generation process of the audit network (2000). Then, the falsification of the ledger information is verified by comparing whether the multiple ledger information (10) matches the audit ledger information. For example, the audit network (2000) may determine that the ledger information among the multiple ledger information (10) that is identical to the first audit ledger information is not falsified, and determine that the ledger information among the multiple ledger information (10) that is not identical to the first audit ledger information is falsified.

[0120] According to the embodiment described in FIG. 12, external data for electronic notarization can be stored in both the blockchain network (1000) and the audit network (2000), and even if the ledger information of the blockchain network (1000) is damaged by an attack, the integrity of the ledger information of the blockchain network (1000) can be restored using the audit ledger information stored in the audit network (2000). In addition, the audit network (2000) is composed of multiple audit councils having different proof methods, and since it maintains audit ledger information whose authenticity is proven by voting among the audit councils, its authenticity can be maintained, preserved, and restored in a state that is safer from external attacks.

[0121] In one embodiment, the audit network (2000) may be a network isolated from the blockchain network (1000). This is to minimize the situation where the blockchain network (1000) and the audit network (2000) are attacked together by keeping the audit network (2000) isolated from the blockchain network (1000).

[0122] FIG. 13 is a diagram showing the configuration and operation method of the audit network (2000) of FIG. 12 in more detail. Referring to FIG. 13, the audit network (20000) includes a first audit council (2100), a second audit council (2200), and an nth audit council (2300).

[0123] Each audit consensus body (2100, 2200, 2300) includes a plurality of audit nodes (300), and proves the authenticity of the audit ledger information held by the audit nodes (300) belonging to it using its own proof method, and generates independent audit blocks using a consensus algorithm according to the said proof method.

[0124] In one embodiment, each audit council (2100, 2200, 2300) may be an audit council with a different proof method. For example, the first audit council (2100) may be an audit council with a PoW proof method, the second audit council (2200) may be an audit council with a PoS proof method, and the nth audit council (2300) may be an audit council with a dPoS proof method.

[0125] To verify the tampering with the ledger information of the blockchain network (1000), each audit consensus body (2100, 2200, 2300) first proves its audit ledger information. For example, the first audit consensus body (2100) can prove the authenticity of its audit ledger information using the PoW proof method, the second audit consensus body (2200) can prove the authenticity of its audit ledger information using the PoS proof method, and the nth audit consensus body (2300) can prove the authenticity of its audit ledger information using the dPoS proof method.

[0126] And, based on the proof results of each audit council (2100, 2200, 2300), the audit ledger information supported by the largest number of audit councils is determined to be the first audit ledger information with proven authenticity (voting).

[0127] For example, if the first audit consensus body (2100) proves audit ledger information B through a PoW consensus algorithm, the second audit consensus body (2200) proves audit ledger information A through a PoS consensus algorithm, and the nth audit consensus body (2300) proves audit ledger information A through a dPoS consensus algorithm, then the audit ledger information A, whose authenticity has been proven by a larger number of audit consensus bodies (2200, 2300), is determined as the first audit ledger information, which is the true audit ledger information. Then, based on the determined first audit ledger information, the falsification of the ledger information of the blockchain network (1000) can be verified, and the verification result can be returned so that the blockchain network (1000) can restore the authenticity of the ledger information.

[0128] At this time, the first audit consensus body (2100) that has proven audit ledger information B that is different from the first audit ledger information can perform the consensus algorithm once again to update its audit ledger information with the first audit ledger information.

[0129] FIG. 14 is a block diagram showing the detailed configuration of an audit node (300) according to an embodiment of the present invention. Referring to FIG. 14, the audit node (300) includes a forgery verification unit (310), a verification result providing unit (320), an audit node information setting unit (330), and an audit consensus node function unit (340).

[0130] The forgery verification unit (310) verifies whether the multiple ledger information (10) extracted from the multiple node devices (100) has been forged or tampered with. At this time, if there is a discrepancy between the multiple ledger information (10), the ledger information (10) is determined to be forged or tampered with. However, the forgery verification unit (310) can go further and determine which of the multiple ledger information (10) is the forged or tampered ledger information by comparing each of the multiple ledger information (10) with the first audit ledger information. For example, let us assume that the first ledger information and the second ledger information among the multiple ledger information (10) are different from each other. At this time, if the first ledger information is identical to the first audit ledger information, the forgery verification unit (310) can determine based on this that the first ledger information is the correct ledger information and the second ledger information is the damaged ledger information.

[0131] The verification result providing unit (320) generates a verification result based on the verification result of the forgery verification unit (310) and provides it to the blockchain network (1000). At this time, the verification result providing unit (320) may provide the first audit ledger information, whose integrity has been proven, to the blockchain network (1000) in order to restore the originality of the blockchain network (1000).

[0132] In one embodiment, the verification result providing unit (320) may reply to the blockchain network (1000) as ledger information identical to the first audit ledger information among the plurality of ledger information (10) as ledger information whose authenticity has been proven. Alternatively, the verification result providing unit (320) may reply directly to the blockchain network (1000) with the first audit ledger information whose authenticity has been proven without referring to the plurality of ledger information (10). The blockchain network (1000) can restore the integrity of the ledger information of the plurality of node devices (100) by creating and distributing the next block based on the provided first audit ledger information.

[0133] The audit node information setting unit (330) sets audit node information for registering an audit node (300). The set audit node information may include audit network client address information, and the audit node (300) can access the audit network (2000) through the audit network client address information to obtain or share block information.

[0134] The audit consensus node function (340) executes a consensus algorithm for block generation within the audit consensus to which the audit node (300) belongs. At this time, the consensus algorithm may include a Proof of Work (PoW), Proof of Stake (PoS), Delegate Proof of Stake (dPoS), Zero-Knowledge Proof, Practical Byzantine Fault Tolerance (PBFT), or a random consensus algorithm based on neural consensus proof, as previously described, and the audit ledger information within the audit consensus is updated by the consensus algorithm.

[0135] FIG. 15 is a flowchart illustrating a ledger information forgery audit method using a plurality of audit consensus bodies according to an embodiment of the present invention. The ledger information forgery audit method of FIG. 15 can be performed by the ledger information forgery audit system (4) illustrated in FIG. 1.

[0136] First, multiple ledger information is collected from multiple node devices within a blockchain network for electronic notarization (S401).

[0137] Then, discrepancies between the collected multiple ledger information are identified, and in response to the discrepancies, the falsification of the multiple ledger information is verified by an audit network (S403).

[0138] At this time, if any one of the aforementioned ledger information differs from the other ledger information, it can be determined that damage has occurred to the ledger information agreed upon by the multiple node devices.

[0139] In addition, the above multiple ledger information can be compared with the first audit ledger information whose integrity has been verified by the audit node, and the ledger information among the multiple ledger information that matches the first audit ledger information can be determined as the first ledger information whose integrity has been verified.

[0140] Next, based on the verified result, a block for updating the ledger information of a plurality of node devices is generated (S405). For example, the previously determined first audit ledger information is provided to a neural consensus proof-based blockchain network as a verification result, and a plurality of node devices within the neural consensus proof-based blockchain network can generate a block for updating the ledger information based on the provided first audit ledger information.

[0141] Then, the generated block is distributed to a neural consensus proof-based blockchain network, and through this, the damaged ledger information within the blockchain network is restored (S407).

[0142] FIG. 16 is a flowchart illustrating an embodiment that further specifies step S403 of FIG. 15.

[0143] First, multiple audit consensus bodies within the audit network verify multiple audit ledger information corresponding to each of the multiple audit consensus bodies by their own verification method (S403a).

[0144] And, among the multiple audit ledger information, the ledger information verified by the largest number of audit consensus bodies is determined as the first audit ledger information verified for the originality of the audit network (S403b).

[0145] And, among multiple audit councils, the first audit council that proves that its audit council information is different from the first audit council information updates its audit council information with the first audit council information (S403c). Through this, the originality of the audit council whose originality has been compromised can be restored.

[0146] Then, the information from the first audit ledger is compared with the information from multiple ledgers of the blockchain network, and based on this, the falsification or alteration of the multiple ledgers is verified.

[0147] Hereinafter, with reference to FIG. 17, an exemplary computing device (500) in which the methods described in various embodiments of the present invention are implemented will be described. For example, the computing device (500) of FIG. 17 may be the node device (100) or the audit node (300) of FIG. 12.

[0148] FIG. 17 is an exemplary hardware configuration diagram showing a computing device (500).

[0149] As illustrated in FIG. 17, a computing device (500) may include one or more processors (510), a bus (550), a communication interface (570), a memory (530) for loading a computer program (591) executed by the processor (510), and a storage (590) for storing the computer program (591). However, FIG. 17 illustrates only the components related to the embodiments of the present invention. Therefore, a person skilled in the art to which the present invention pertains will understand that other general-purpose components may be included in addition to the components illustrated in FIG. 17.

[0150] The processor (510) controls the overall operation of each component of the computing device (500). The processor (510) may be configured to include at least one of a CPU (Central Processing Unit), MPU (Micro Processor Unit), MCU (Micro Controller Unit), GPU (Graphic Processing Unit), or any form of processor well known in the art of the present invention. Additionally, the processor (510) may perform operations for at least one application or program for executing a method / operation according to various embodiments of the present invention. The computing device (500) may have one or more processors.

[0151] The memory (530) stores various data, commands and / or information. The memory (530) may load one or more programs (591) from storage (590) to execute methods / operations according to various embodiments of the present invention. Examples of the memory (530) may be RAM, but are not limited thereto.

[0152] The bus (550) provides communication functions between components of the computing device (500). The bus (550) can be implemented as various types of buses, such as an address bus, a data bus, and a control bus.

[0153] The communication interface (570) supports wired and wireless internet communication of the computing device (500). The communication interface (570) may also support various communication methods other than internet communication. To this end, the communication interface (570) may be configured to include a communication module well known in the technical field of the present invention.

[0154] Storage (590) may store one or more computer programs (591) non-temporarily. Storage (590) may be configured to include volatile memory such as ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), flash memory, a hard disk, a removable disk, or any form of computer-readable recording medium well known in the art to which the present invention belongs.

[0155] A computer program (591) may include one or more instructions in which methods / operations according to various embodiments of the present invention are implemented. When the computer program (591) is loaded into memory (530), a processor (510) may perform methods / operations according to various embodiments of the present invention by executing the one or more instructions.

[0156] The technical concept of the present invention described so far may be implemented as computer-readable code on a computer-readable medium. The computer-readable recording medium may be, for example, a removable recording medium (CD, DVD, Blu-ray disc, USB storage device, removable hard disk) or a fixed recording medium (ROM, RAM, computer-equipped hard disk). The computer program recorded on the computer-readable recording medium may be transmitted to another computing device via a network such as the Internet and installed on the other computing device, thereby allowing it to be used on the other computing device.

[0157] Although embodiments of the present invention have been described above with reference to the attached drawings, those skilled in the art will understand that the present invention may be implemented in other specific forms without altering the technical concept or essential features thereof. Therefore, the embodiments described above should be understood as illustrative in all respects and not restrictive. The scope of protection of the present invention shall be interpreted by the claims below, and all technical concepts within the equivalent scope shall be interpreted as being included within the scope of rights of the technical concept defined by the present invention.

Claims

Claim 1 A method for auditing forgery using a plurality of audit consensus bodies performed by a computing device, comprising: a step of collecting a plurality of ledger information from a plurality of node devices within a blockchain network for electronic notarization; a step of identifying a discrepancy indicating the possibility of damage to the plurality of ledger information when any one of the plurality of ledger information differs from another ledger information, and a step of verifying forgery of the plurality of ledger information by an audit network in response to the discrepancy. A method for auditing forgery using multiple audit consensus bodies, comprising the step of generating a block for updating ledger information of the plurality of node devices based on the verified result, wherein the blockchain network generates a block to be distributed within the blockchain network through a block generation process based on neural consensus proof, and the audit network includes a plurality of audit consensus bodies having different proof methods, wherein each of the plurality of audit consensus bodies independently proves audit ledger information corresponding to itself by its own proof method, and verifies forgery of the plurality of ledger information by voting, wherein the audit ledger information proven by the largest number of audit consensus bodies among the plurality of audit consensus bodies is determined as the first audit ledger information whose authenticity is proven, and wherein an audit consensus body among the plurality of audit consensus bodies that proves audit ledger information different from the first audit ledger information re-executes its own consensus algorithm to update its audit ledger information with the first audit ledger information. Claim 2 A forgery audit method using multiple audit consensus bodies, wherein each of the different proof methods is a proof method performed by any one of the following algorithms: PoW (Proof of Work), PoS (Proof of Stake), dPoS (delegate Proof of Stake), Zero-Knowledge Proof, PBFT (Practical Byzantine Fault Tolerance), and a Neural Consensus Proof-based Random Consensus Algorithm. Claim 3 A forgery audit method using a plurality of audit consensus bodies, wherein each of the plurality of audit consensus bodies includes a plurality of audit nodes, in accordance with claim 1. Claim 4 delete Claim 5 delete Claim 6 delete Claim 7 delete Claim 8 In claim 1, the plurality of ledger information comprises an electronic notarized document or a hash value extracted from the electronic notarized document, a forgery auditing method using a plurality of audit consensus bodies. Claim 9 A method for auditing forgery using multiple audit consensus bodies, wherein, in claim 1, when external data for electronic notarization is generated, the external data is provided to the blockchain network and the audit network, respectively, the blockchain network updates the ledger information of each of the plurality of node devices with the external data by the neural consensus proof-based block generation process, and the audit network updates the multiple audit ledger information corresponding to each of the plurality of audit consensus bodies with the external data by the block generation process of each of the plurality of audit consensus bodies. Claim 10 In claim 1, the audit network is a network separated from the blockchain network, and the forgery audit method using multiple audit consensus bodies. Claim 11 A method for auditing forgery using multiple audit consensus bodies according to claim 1, wherein the plurality of node devices perform a neural consensus proof-based block generation process according to preset conditions, and the neural consensus proof-based block generation process extracts validity verification data from new block data, obtains neural consensus designation information of the next block generated based on a random consensus proof process according to the verification processing of the validity verification data, selectively drives a consensus node function unit based on the neural consensus designation information of the next block, and generates validity verification data of the next block. Claim 12 A method for auditing forgery using multiple audit consensus bodies, wherein, in claim 11, the validity verification data includes consensus process verification data corresponding to the random consensus body proof process, and the neural consensus body designation information of the next block includes nonce information for verifying the eligibility of participation of the neural consensus body corresponding to the next block. Claim 13 A blockchain network for electronic notarization comprising multiple node devices that perform a block generation process based on neural consensus proof according to preset conditions; The system includes an audit network that identifies a discrepancy indicating the possibility of damage to the multiple ledgers when any one of the multiple ledgers collected from the multiple node devices differs from other ledgers, verifies the falsification of the multiple ledgers based on the result of identifying the discrepancy, and returns the first ledgers whose integrity has been verified to the blockchain network; the blockchain network generates a block for updating the ledgers of the multiple node devices based on the first ledgers; the audit network includes multiple audit consensus bodies having different proof methods, each of the multiple audit consensus bodies independently proves the audit ledgers corresponding to itself by its own proof method, and verifies the falsification of the multiple ledgers by voting to determine the audit ledgers proven by the largest number of audit consensus bodies among the multiple audit ledgers proven by the multiple audit consensus bodies as the first audit ledgers whose authenticity has been verified, and among the multiple audit consensus bodies, the audit consensus body that proved audit ledgers different from the first audit ledgers re-executes its own consensus algorithm to determine its audit of the first audit ledgers A forgery audit system using multiple audit consensus bodies to update ledger information.

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