A meta-universe anti-attack consensus method and system based on spatiotemporal information feature enhancement

Abstract

The application discloses a meta-universe attack-resistant consensus method and system based on space-time information feature enhancement, a space-time certificate is embedded in a node consensus message, the certificate is generated by binding a node physical coordinate and a high-precision global clock with a clock source trusted proof, a consensus process completes node access verification and event time sequence arbitration based on the space-time certificate, and an authentication information consensus algorithm with strong attack resistance is formed. Meanwhile, a layered blockchain scheme based on DAG is proposed, a new P2P network is constructed in combination with a sharding technology and a directed acyclic graph structure: a global shard is composed of global nodes verified by STC, is responsible for maintaining a cross-shard distributed digital identity index and a space-time anchoring, local shards are divided according to meta-universe regions or application domains, and maintain intra-shard distributed digital identity documents and verifiable certificate storage; BLS threshold drawing, Bullshark and space-time certificate time sequence arbitration mechanisms are used in each shard.

Description

Technical Field

[0001] This invention relates to the fields of blockchain consensus and metaverse digital identity technology, specifically to a metaverse anti-attack consensus method and system based on spatiotemporal information feature enhancement. Background Technology

[0002] The security of blockchain consensus mechanisms is typically built on the strong assumption of "node honesty." However, in large-scale open heterogeneous networks like the metaverse, the forgery of node identities and system times constitutes two long-standing and difficult-to-eradicate attack vectors.

[0003] First, there's the attack of spoofing node identity and geolocation. In sharded consensus architectures, attackers often use cloud virtualization technology, combined with fake IP geolocation information, to forge a large number of candidate nodes with "geographically dispersed" characteristics during the sharding election phase. This "Syllabic attack" can allow a single physical entity to gain excessive weight in the sharding committee, thereby manipulating the consensus outcome.

[0004] Secondly, timestamp and clock manipulation attacks. Existing consensus mechanisms often rely on nodes declaring their own times or on vulnerable network time protocols such as NTP. Attackers can maliciously tamper with timestamps through NTP spoofing, system clock rollback, or fast-forwarding, thereby interfering with the causal order of transactions, bypassing transaction expiration checks, extending the validity period of proposals, or misleading the tip selection algorithm of directed acyclic graphs (DAGs), thus implementing "timestamp transaction spoofing."

[0005] Furthermore, the metaverse application scenario places extreme performance demands on infrastructure. The metaverse involves the high-frequency registration, authentication, and authorization of distributed digital identities (DIDs) for massive numbers of users, posing severe challenges to system storage scalability and transaction confirmation latency. Traditional linear chain structures struggle to balance "high storage scalability" and "low confirmation latency"; while simple sharding solutions, although improving parallelism, often suffer from "shard silos" due to the lack of a globally unified cross-shard verifiable anchoring and mutual verification mechanism, and the overall system security is non-linearly diluted with the increase in the number of shards.

[0006] Therefore, to address the aforementioned shortcomings, this invention proposes a metaverse anti-attack consensus method and system based on enhanced spatiotemporal information features. By introducing Spatiotemporal Certificates (STCs), this invention extends the root of trust in consensus from the fragile "logical identity" to the immutable "physical spatiotemporal verifiability," fundamentally combating node information forgery and timestamp spoofing. Simultaneously, it constructs a DAG-based layered blockchain architecture (DASH), employing block header compression technology, a sharding committee mechanism, and a cross-shard reference mutual protection strategy to effectively meet the dual requirements of the metaverse DID system for high-concurrency storage and low-latency confirmation without sacrificing security. Summary of the Invention

[0007] The purpose of this invention is to propose a metaverse anti-attack consensus method and system based on spatiotemporal information feature enhancement, aiming to solve the following core problems existing in the prior art: (1) The problem of lack of trusted anchoring of node identity: Existing sharding consensus mechanisms usually rely only on logical identifiers for node election, lacking a trusted binding and verification mechanism for physical spatiotemporal attributes. This allows attackers to use cloud hosts in conjunction with fake Geo-IP addresses to carry out Sybil attacks, forging a large number of “geographically dispersed” candidate nodes in the same physical location, thereby monopolizing the sharding committee and diluting system security. (2) Insufficient anti-tampering of time base: Existing consensus relies on local node clocks or network time protocols that are susceptible to interference. Attackers can tamper with timestamps by means of clock rollback, fast forward or NTP spoofing, which can interfere with the DAG’s tip selection, transaction order and expiration determination, and trigger timestamp transaction spoofing attacks. (3) Performance and scalability bottlenecks in the metaverse DID scenario: Traditional chain structure is difficult to balance high storage scalability and low confirmation latency; while conventional sharding schemes lack a globally unified cross-shard verifiable anchoring and mutual verification mechanism, which can easily lead to sharding islands, and the overall security of the system decreases non-linearly with the increase of the number of shards, which cannot meet the high concurrency and low latency business needs of massive user DID.

[0008] In summary, this invention aims to anchor the root of trust to physical spatiotemporal verifiability by introducing a spacetime credential (STC), construct a DAG-based layered architecture (DASH), and fundamentally solve the technical challenges of node identity forgery, timestamp spoofing, and the difficulty in simultaneously achieving metaverse DID storage expansion and low-latency confirmation by utilizing cross-shard mutual verification and block header compression mechanisms.

[0009] This application constructs a three-layer architecture that decouples physical nodes, sharding nodes, and logical nodes, as specifically defined below: (1) Logical Node (LN) Mapping and Hosting: Every Metaverse User In specific application domains Internally represented as a logical node This node is based on application domain. Mapped to the corresponding local shard The local shard maintains its DID document and verifiable credential VC; the logical node is defined as a triple structure. Its lifecycle is strongly bound to the DID document and decoupled from the STC lifecycle of the physical node that hosts it. (2) Physical Node (PN) Admission: A physical node refers to a physical device that runs the STC acquisition module and blockchain client, including but not limited to edge servers, VR headsets, and various user terminals; such devices must pass the STC verification process to join the network; their trustworthiness is determined by the physical coordinate digest in STC. With clock source credibility proof Joint guarantee; (3) Shard Node (SN) Election: A shard node refers to a physical node that has been selected through STC legitimacy filtering and an EC-VRF lottery mechanism to participate in the consensus process; within one epoch, it is assigned to a global shard or a local shard. The consensus participation identity of a physical node is that it belongs to at most one shard within the same epoch, that is, the global shard or a local shard. (4) Separation of Duties and Hosting Mechanism: A single physical node can host multiple users belonging to different users within the same epoch. The logical nodes are defined, but the DID operations of each logical node, such as update, revocation, and VC issuance, must be performed using its corresponding user private key. Signature; Physical nodes only act as hosts, providing STC anchoring, network forwarding, and storage I / O capabilities, and are strictly prohibited from performing any DID-level signature operations; (5) Layered defense and performance support: Thus, STC's anti-attack capability mainly works on the L1 layer, ensuring that physical nodes cannot forge geographical locations or clock information to mix into multiple shards; while the high-concurrency storage requirements and low-latency authentication requirements of Metaverse DID are supported by the L3 layer, which is achieved through the decoupling design of logical nodes and shards and the DAG concurrency mechanism within the local shard; the above two-layer architecture achieves a unity of security and scalability through strict separation of responsibilities.

[0010] To achieve the above objectives, this invention provides a metaverse anti-attack consensus method and system based on spatiotemporal information feature enhancement, comprising the following steps: Step 1: Physical nodes connected to the network generate Spatiotemporal Certificates (STCs). Step 2: The consensus system performs global node election and sharding construction; Step 3: The consensus system constructs a three-layer mapping architecture of physical nodes, shard ownership, and logical nodes; Step 4: The consensus system performs DAG timing arbitration based on STC-UTC.

[0011] Optionally, the execution process of step 1 includes the following steps: Step 1.1: Physical Nodes Obtain current physical coordinates from the location source. ,in For latitude, For longitude, Altitude; Step 1.2: To prevent user location from being leaked due to plaintext coordinates, physical nodes... Generate local random numbers and call the collision-resistant hash function. Calculated coordinate summary ; Step 1.3: Physical Nodes Obtain Coordinated Universal Time (UTC) timestamps from a high-precision clock source. And read the identifier of the clock source. Subsequently, physical nodes Will Send to a local trusted time source, which will then process the data. Issuance of clock source trust certificate ;in cryptographic types and Security level binding: When For high-precision time sources, chip-level atomic clocks or dual-frequency timekeeping, For short signatures within a trusted execution environment; when When used as a medium-precision time source or a single frequency, For timestamp authority tokens; when When it is a low-precision time source (NTP), It is a symmetric key message authentication code; Step 1.4: Physical Nodes Assemble the time-space certificate and using their own private key right Perform digital signature, obtain ,in It is the identity identifier of the physical node; subsequently, the physical node Will It is broadcast to the entire network as its own spatiotemporal anchoring certificate; Step 1.5: When any subsequent node or shard receives a physical node... When sending a message, first use the public key. Verify signature Then verify with the public key of the trusted time source. If both verifications pass, then it is considered valid. Valid, marked as .

[0012] Optionally, the execution process of step 2 includes the following steps: Step 2.1: Collect and filter spatiotemporal credentials to generate a candidate physical node set. Specifically, it includes: (1) After all nodes in the network publish the STC, the pre-set coordinating node for this epoch obtains the broadcast STCs for the entire network within the current epoch. ; (2) The coordination node verifies each node one by one. signature Proof with a clock And perform two-level rejection: if If the verification is invalid, the node is removed directly; if If the security level is lower than the preset threshold, the node will be removed. (3) For the remaining nodes that have passed the above two-level filtering, the coordination node summarizes their coordinates. Mapped to a preset geographic grid Perform cluster detection: if the same grid Internal appearance Homogeneous and number of nodes In such cases, it is determined to be a "pseudo-geographical dispersion" cluster, used to prevent attackers from using multiple instances in the same data center to forge multiple geographical locations. This is a preset cluster density threshold; downsampling is performed on this cluster, retaining at most one node, with the retention rule being to take... The earliest one, or take The node with the smallest lexicographical order is moved to the local sharding candidate pool; (4) The set of candidate physical nodes obtained after filtering is denoted as ,in This represents the total number of candidate physical nodes. Step 2.2: Based on the candidate set Generate the lottery seed and threshold key, and perform BLS lottery, specifically including: (1) with All according to Merkle roots are calculated by concatenating lexicographical orders and denoted as . This serves as the global seed for this epoch; each within Refresh at each epoch to ensure unpredictability; (2) Candidate set All internal nodes operate together Distributed Key Generation Protocol (DKG), in which The BLS threshold value satisfies , Generate their respective threshold key fragments And export the corresponding group public key. It is stored by all nodes; (3) Each node by Calculate the BLS lottery factor using the input: , in For collision-resistant hash functions; Mapped to Interval obtained ; (4) Based on binomial distribution Will The interval is divided into consecutive small intervals : , in , The target size of the global partitioning for this epoch, and satisfying the following conditions: ,and This ensures that the elected candidate is capable of reconstructing the BLS threshold signature; (5) When a certain node of and At that time, the judgment Once selected as a candidate global node, it will proceed to the next round of confirmation. Step 2.3: Broadcast and confirm candidate global nodes to form a global shard, specifically including: (1) Candidate global nodes Broadcast to the entire network ,in for Verification evidence for the correctness of the computation includes the group's public key. and corresponding Aggregate signature fragments; (2) Use at any node in the entire network Verify the aggregation path; those that pass the verification are officially designated as global nodes, denoted as [node name missing]. All global nodes constitute a set ,Depend on Forming a global partition; (3) Global sharding maintains the following states: one is the cross-shard DID index. The first is for DID cross-application domain routing; the second is for inter-shard consensus, used to handle cross-shard DID migration, cross-shard VC verification, cross-shard transactions and other transactions that require coordination among multiple shards. Step 2.4: Divide the local space into fragments, specifically including: (1) Not selected for global fragmentation The remaining nodes are assigned to local partitions according to the metaverse two-dimensional partitioning strategy. One type is the geographical region, as described in step 2.3. Mapped geographic grid One approach is to define the geographical domain, making nodes physically adjacent within the same geographical domain and reducing intra-slice DAG Gossip latency; the other approach is to define the application domain, which is defined by the metaverse business logic, making DID transactions semantically similar within the same application domain and improving intra-slice DAG concurrency. (2) Each combination of (regional domain, application domain) constitutes a local shard. ,in For fragmentation ; (3) Each local shard Internally, a directed acyclic graph (DAG) structure is used to implement intra-chip consensus and maintain user relationships within the domain. DID document records With verifiable credentials (VC).

[0013] Optionally, the execution process of step 3 includes the following steps: Step 3.1: Determine the sharding affiliation of physical nodes, specifically including: (1) Physical Nodes After the election process in step 2, if a node is elected as a global node, it will belong to the global shard. If not selected, it will be assigned to the unique local fragment according to the two-dimensional fragmentation strategy determined in step 2.4, i.e., (regional domain, application domain). and obtain Level 2 (L2) identity identifier. "as" Shard nodes participate in the intra-shard directed acyclic graph (DAG) consensus; (2) Within a single epoch, a single physical node is limited. It can only belong to one shard, either a global shard or a local shard, in order to prevent the same physical entity from forming a Sybil attack lever across multiple shards; Step 3.2: Manage logical nodes and establish a global routing index, specifically including: (1) Physical Nodes In its local shard Internally, it hosts at least one logical node. The logical node is defined as a triplet structure: ,in, For user identification, For users The W3C standard distributed digital identity document anchor, containing the public key. , server endpoint and undo list pointer; For users In the application domain Metadata of the incarnation; For users A set of verifiable credentials held; (2) Allow the same user In multiple different application domains Register logical nodes separately Each logical node independently maintains a corresponding DID document shard copy; (3) Global fragmentation Maintain cross-slice DID index Used to respond to user-related issues across the entire network. Cross-application domain routing query requests; Step 3.3: Implement permission isolation between the physical host and the logical identity, specifically including: (1) Define the boundaries of storage and execution responsibilities: logical nodes The maintenance of DID documents and verifiable credentials is handled by the local shard to which they belong. Responsible for; physical nodes As only The execution host provides network forwarding, storage I / O, and STC spatiotemporal anchoring capabilities, but does not possess... DID private key signing permissions; (2) Enforce client-side signature policy: Any operation involving DID, including but not limited to registration, update, revocation, VC issuance / verification, and cross-domain migration, must be performed by the user. I used the private key Signature; even physical nodes The system was maliciously compromised, and the attackers were unable to obtain [access / resources]. It can only cause a denial of service or tamper with a local storage copy, but cannot forge a user. Any DID semantic operations; (3) Forming a two-layer defense closed loop: The STC anchoring in step 1 constitutes the first layer of defense (L1), which is used to prevent malicious nodes from spoofing geographical locations or clocks and mixing into multiple fragments during the filtering stage in step 2.1; the separation of duties in this step constitutes the second layer of defense (L3), which prevents the spread of the virus due to physical hosts. The compromised system resulted in the hijacking of a batch of logical nodes (LNs) hosted by the system, thus converging the attack surface to the storage layer and preventing identity spoofing.

[0014] Optionally, the execution process of step 4 includes the following steps: Step 4.1: Construct a DAG structure embedding spatiotemporal credentials, specifically including: (1) In each local shard Internally, it adopts Bullshark consensus and uses Narwhal as its underlying DAG memory pool; the vertices in the DAG are defined as transaction batches, and the directed edges between vertices are defined as causal reference relationships and STC anchoring relationships; (2) Force the embedding of its physical node into each vertex structure. The STC core fields include at least the coordinate summary. UTC timestamp and clock source identifier ; (3) Global fragmentation Periodically partition the local partition. Randomly sample vertices within the range to verify the information they carry. Effectiveness to curb long-term cheating behavior; Step 4.2: Perform Leader election and deterministic commit based on STC entropy source, specifically including: (1) The Bullshark protocol proceeds in rounds; each round elects a leader using a deterministic algorithm: based on the network's STC. The median, as the primary entropy source, is used through a collision-resistant hash function. Derivative primary seed ; Total number of candidate nodes for this sub-seed Take the modulus to obtain the Leader offset. In the list of candidate nodes arranged lexicographically by pk, the first... Each node is elected as the Leader in this round; since the main entropy source depends on the real time median of the network's STC, malicious nodes cannot predict or manipulate the sub-seeds, thus making it impossible to predict the Leader sequence and effectively resisting targeted network attacks. (2) The vertex submitted by the current leader receives at least When a vertex receives a strong visible vote from several other nodes, it has reached a deterministic commit. This represents the number of fault-tolerant nodes. (3) If the Leader times out in the current round, or if the vertex submitted by it fails to achieve strong visibility within the specified time, the "scythe rule" of the next round is triggered, skipping the submission attempt of the current round and directly entering the next round of consensus; Step 4.3: Calculate the consensus timestamp of the free vertices, specifically including: (1) Discard the node local clock and force the use of the STC. As a timing reference; (2) For the same round The leader failed to reach the free vertex submitted by the leader. First, extract the vertices. direct ancestor set and its descendants ; (3) Merge sets Filter out All Node declaration Calculate the median of this time series. and will Officially designated as the vertex The final consensus timestamp; Step 4.4: Establish the total order arrangement rule for the vertices of the DAG, and set the global linearization sort priority of the vertices in the DAG as follows: ① Round (ascending order): Prioritize processing vertices with smaller round numbers; ② Consensus timestamp ( Ascending order: Within the same round, assign... Vertices with smaller numerical values ​​have higher priority. ③ Vertex hash lexicographical order: If the timestamps are the same, they are arranged according to the lexicographical order of the vertex hash values; ④ Random number XOR result ascending order: If the hash values ​​are still the same, they are arranged in ascending order according to the preset random number XOR result to resolve extreme conflicts; Step 4.5: Perform block timestamp deviation verification, specifically including: (1) Physical nodes When a new block is generated, its block header timestamp must include a valid one. ; (2) Local Fragmentation Maintain a preset maximum permissible deviation window for STC-UTC. ; (3) When a node receives a new block, it verifies the deviation between the block header timestamp and the locally maintained valid STC-UTC reference; if the absolute value of the deviation exceeds the threshold... If the block is not found, it will be immediately discarded and refused to be added to the blockchain.

[0015] This invention provides a metaverse-based anti-attack consensus method and system based on spatiotemporal information feature enhancement, constructing a layered trust architecture consisting of a physical anchoring layer, a network sharding layer, and a logical abstraction layer. The method is based on spatiotemporal credentials generated by binding node physical coordinates and high-precision clocks through trusted proof. It uses an STC filtering mechanism to eliminate nodes from the same source cluster, blocking Sybil attacks based on false geographical locations at the source. Furthermore, the system utilizes an improved Bullshark consensus protocol, using the median STC timestamp of the entire network as the entropy source for Leader election, and implements deterministic timing arbitration of DAG vertices based on STC-UTC, effectively resisting clock rollback and NTP spoofing. Simultaneously, this invention designs a DAG-based layered blockchain solution, using block header compression technology to reduce storage overhead. Through BLS threshold signatures and cross-shard reference mutual protection mechanisms, it achieves high-concurrency storage and millisecond-level low-latency authentication of massive distributed digital identities in the metaverse while ensuring global security, solving the industry problems of sharding silos and security dilution with scale. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart illustrating the steps of a metaverse anti-attack consensus method and system based on spatiotemporal information feature enhancement according to the present invention.

[0018] Figure 2 This is a system architecture diagram of a metaverse anti-attack consensus method and system based on spatiotemporal information feature enhancement according to the present invention. Detailed Implementation

[0019] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0020] Please see Figure 1 This invention provides a metaverse anti-attack consensus method and system based on spatiotemporal information feature enhancement, comprising the following steps: Step 1: Physical nodes connected to the network generate Spatiotemporal Certificates (STCs). Step 2: The consensus system performs global node election and sharding construction; Step 3: The consensus system constructs a three-layer mapping architecture of physical nodes, shard ownership, and logical nodes; Step 4: The consensus system performs DAG timing arbitration based on STC-UTC.

[0021] The following provides further explanation with reference to specific embodiments and execution processes: This invention provides a metaverse anti-attack consensus method and system based on spatiotemporal information feature enhancement, such as... Figure 2 As shown, the system mainly adopts a layered hybrid architecture, consisting of four core modules: a spatiotemporal anchoring module, a layered sharding management module, an enhanced DAG consensus module, and a logical identity decoupling module. These modules work together to build a full-stack defense system from the physical root of trust to the upper-layer business logic. (1) Spatiotemporal Anchoring Module (L1 Physical Layer): This module is the root of trust of the system and is responsible for generating and verifying the Spatiotemporal Certificate (STC). It integrates a high-precision positioning source and a trusted clock source, processes physical coordinates through an anti-collision hash function to generate a digest, and issues clock certificates by a trusted time source. This module ensures that nodes cannot forge geographical locations or tamper with system time, providing an immutable "physical spatiotemporal fingerprint" for upper-layer consensus. (2) Layered Slicing Management Module (L2 Network Layer): This module is responsible for the dynamic construction and secure election of network topology. It first filters nodes with the same source cluster according to STC to prevent Sybil attacks. Then it generates BLS threshold keys based on DKG protocol and uses a binomial distribution lottery mechanism combined with STC entropy source to elect global nodes. This module divides the network into global slices responsible for cross-slice coordination and local slices divided by region / application domain to realize the optimization of physical proximity and parallel processing of network resources. (3) Enhanced DAG consensus module (L2 consensus engine): This module runs within the local shard, using Narwhal as the data propagation layer and Bullshark as the sorting layer; its core innovation lies in embedding the STC timestamp (UTC) into the DAG vertices, abandoning the node's local clock, deriving the entropy source based on the STC median for Leader election, and determining the consensus timestamp of the free vertices through the "median arbitration" algorithm; this module achieves deterministic sorting and low-latency confirmation based on physical time while ensuring Byzantine fault tolerance; (4) Logical Identity Decoupling Module (L3 Application Layer): This module is responsible for the lifecycle management of digital identities in the metaverse. It defines a logical node (LN) triple structure (DID, Avatar, VC) and maintains cross-shard DID indexes through global sharding, achieving complete decoupling between user identity and physical host. This module enforces a separation of duties strategy of "physical nodes do not sign DIDs on behalf of users," ensuring that even if the physical host is compromised, attackers cannot steal user identities or forge digital asset operations, fundamentally guaranteeing the security of the metaverse economic system.

[0022] The specific execution steps of the metaverse anti-attack consensus method and system based on spatiotemporal information feature enhancement are as follows.

[0023] The execution process of step 1 includes the following steps: Step 1.1: Physical Nodes Obtain current physical coordinates from the location source. ,in For latitude, For longitude, Altitude; Step 1.2: To prevent user location from being leaked due to plaintext coordinates, physical nodes... Generate local random numbers and call the collision-resistant hash function. Calculated coordinate summary ; Step 1.3: Physical Nodes Obtain Coordinated Universal Time (UTC) timestamps from a high-precision clock source. And read the identifier of the clock source. Subsequently, physical nodes Will Send to a local trusted time source, which will then process the data. Issuance of clock source trust certificate ;in cryptographic types and Security level binding: When For high-precision time sources, chip-level atomic clocks or dual-frequency timekeeping, For short signatures within a trusted execution environment; when When used as a medium-precision time source or a single frequency, For timestamp authority tokens; when When it is a low-precision time source (NTP), It is a symmetric key message authentication code; Step 1.4: Physical Nodes Assemble the spacetime certificate and using their own private key right Perform digital signature to obtain ,in It is the identity identifier of the physical node; subsequently, the physical node Will It is broadcast to the entire network as its own spatiotemporal anchoring certificate; Step 1.5: When any subsequent node or shard receives a physical node... When sending a message, first use the public key. Verify signature Then verify with the public key of the trusted time source. If both verifications pass, then it is considered valid. Valid, marked as .

[0024] The execution process of step 2 includes the following steps: Step 2.1: Collect and filter spatiotemporal credentials to generate a candidate physical node set. Specifically, it includes: (1) After all nodes in the network publish the STC, the pre-set coordinating node for this epoch obtains the broadcast STCs for the entire network within the current epoch. ; (2) The coordination node verifies each node one by one. signature Proof with a clock And perform two-level rejection: if If the verification is invalid, the node is removed directly; if If the security level is lower than the preset threshold, the node will be removed. (3) For the remaining nodes that have passed the above two-level filtering, the coordination node summarizes their coordinates. Mapped to a preset geographic grid Perform cluster detection: if the same grid Internal appearance Homogeneous and number of nodes In such cases, it is determined to be a "pseudo-geographical dispersion" cluster, used to prevent attackers from using multiple instances in the same data center to forge multiple geographical locations. This is a preset cluster density threshold; downsampling is performed on this cluster, retaining at most one node, with the retention rule being to take... The earliest one, or take The node with the smallest lexicographical order is moved to the local sharding candidate pool; (4) The set of candidate physical nodes obtained after filtering is denoted as ,in This represents the total number of candidate physical nodes. Step 2.2: Based on the candidate set Generate the lottery seed and threshold key, and perform BLS lottery, specifically including: (1) with All according to Merkle roots are calculated by concatenating lexicographical orders and denoted as . This serves as the global seed for this epoch; each within Refresh at each epoch to ensure unpredictability; (2) Candidate set All internal nodes operate together Distributed Key Generation Protocol (DKG), in which The BLS threshold value satisfies , Generate their respective threshold key fragments And export the corresponding group public key. It is stored by all nodes; (3) Each node by Calculate the BLS lottery factor using the input: , in For collision-resistant hash functions; Mapped to Interval obtained ; (4) Based on binomial distribution Will The interval is divided into consecutive small intervals : , in , The target size of the global partitioning for this epoch, and satisfying the following conditions: ,and This ensures that the elected candidate is capable of reconstructing the BLS threshold signature; (5) When a certain node of and At that time, the judgment Once selected as a candidate global node, it will proceed to the next round of confirmation. Step 2.3: Broadcast and confirm candidate global nodes to form a global shard, specifically including: (1) Candidate global nodes Broadcast to the entire network ,in for Verification evidence for the correctness of the computation includes the group's public key. and corresponding Aggregate signature fragments; (2) Use at any node in the entire network Verify the aggregation path; those that pass the verification are officially designated as global nodes, denoted as [node name missing]. All global nodes constitute a set ,Depend on Forming a global partition; (3) Global sharding maintains the following states: one is the cross-shard DID index. The first is for DID cross-application domain routing; the second is for inter-shard consensus, used to handle cross-shard DID migration, cross-shard VC verification, cross-shard transactions and other transactions that require coordination among multiple shards. Step 2.4: Divide the local space into fragments, specifically including: (1) Not selected for global fragmentation The remaining nodes are assigned to local partitions according to the metaverse two-dimensional partitioning strategy. One type is the geographical region, as described in step 2.3. Mapped geographic grid One approach is to define the geographical domain, making nodes physically adjacent within the same geographical domain and reducing intra-slice DAG Gossip latency; the other approach is to define the application domain, which is defined by the metaverse business logic, making DID transactions semantically similar within the same application domain and improving intra-slice DAG concurrency. (2) Each combination of (regional domain, application domain) constitutes a local shard. ,in For fragmentation ; (3) Each local shard Internally, a directed acyclic graph (DAG) structure is used to implement intra-chip consensus and maintain user relationships within the domain. DID document records With verifiable credentials (VC).

[0025] The execution process of step 3 includes the following steps: Step 3.1: Determine the sharding affiliation of physical nodes, specifically including: (1) Physical Nodes After the election process in step 2, if a node is elected as a global node, it will belong to the global shard. If not selected, it will be assigned to the unique local fragment according to the two-dimensional fragmentation strategy determined in step 2.4, i.e., (regional domain, application domain). and obtain Level 2 (L2) identity identifier. "as" Shard nodes participate in the intra-shard directed acyclic graph (DAG) consensus; (2) Within a single epoch, a single physical node is limited. It can only belong to one shard, either a global shard or a local shard, in order to prevent the same physical entity from forming a Sybil attack lever across multiple shards; Step 3.2: Manage logical nodes and establish a global routing index, specifically including: (1) Physical Nodes In its local shard Internally, it hosts at least one logical node. The logical node is defined as a triplet structure: ,in, For user identification, For users The W3C standard distributed digital identity document anchor, containing the public key. , server endpoint and undo list pointer; For users In the application domain Metadata of the incarnation; For users A set of verifiable credentials held; (2) Allow the same user In multiple different application domains Register logical nodes separately Each logical node independently maintains a corresponding DID document shard copy; (3) Global fragmentation Maintain cross-slice DID index Used to respond to user-related issues across the entire network. Cross-application domain routing query requests; Step 3.3: Implement permission isolation between the physical host and the logical identity, specifically including: (1) Define the boundaries of storage and execution responsibilities: logical nodes The maintenance of DID documents and verifiable credentials is handled by the local shard to which they belong. Responsible for; physical nodes As only The execution host provides network forwarding, storage I / O, and STC spatiotemporal anchoring capabilities, but does not possess... DID private key signing permissions; (2) Enforce client-side signature policy: Any operation involving DID, including but not limited to registration, update, revocation, VC issuance / verification, and cross-domain migration, must be performed by the user. I used the private key Signature; even physical nodes The system was maliciously compromised, and the attackers were unable to obtain [access / resources]. It can only cause a denial of service or tamper with a local storage copy, but cannot forge a user. Any DID semantic operations; (3) Forming a two-layer defense closed loop: The STC anchoring in step 1 constitutes the first layer of defense (L1), which is used to prevent malicious nodes from spoofing geographical locations or clocks and mixing into multiple fragments during the filtering stage in step 2.1; the separation of duties in this step constitutes the second layer of defense (L3), which prevents the spread of the virus due to physical hosts. The compromised system resulted in the hijacking of a batch of logical nodes (LNs) hosted by the system, thus converging the attack surface to the storage layer and preventing identity spoofing.

[0026] The execution process of step 4 includes the following steps: Step 4.1: Construct a DAG structure embedding spatiotemporal credentials, specifically including: (1) In each local shard Internally, it adopts Bullshark consensus and uses Narwhal as its underlying DAG memory pool; the vertices in the DAG are defined as transaction batches, and the directed edges between vertices are defined as causal reference relationships and STC anchoring relationships; (2) Force the embedding of its physical node into each vertex structure. The STC core fields include at least the coordinate summary. UTC timestamp and clock source identifier ; (3) Global fragmentation Periodically partition the local partition. Randomly sample vertices within the range to verify the information they carry. Effectiveness to curb long-term cheating behavior; Step 4.2: Perform Leader election and deterministic commit based on STC entropy source, specifically including: (1) The Bullshark protocol proceeds in rounds; each round elects a leader using a deterministic algorithm: based on the network's STC. The median, as the primary entropy source, is used through a collision-resistant hash function. Derivative primary seed ; Total number of candidate nodes for this sub-seed Take the modulus to obtain the Leader offset. In the list of candidate nodes arranged lexicographically by pk, the first... Each node is elected as the Leader in this round; since the main entropy source depends on the real time median of the network's STC, malicious nodes cannot predict or manipulate the sub-seeds, thus making it impossible to predict the Leader sequence and effectively resisting targeted network attacks. (2) The vertex submitted by the current leader receives at least When a vertex receives a strong visible vote from several other nodes, it has reached a deterministic commit. This represents the number of fault-tolerant nodes. (3) If the Leader times out in the current round, or if the vertex submitted by it fails to achieve strong visibility within the specified time, the "scythe rule" of the next round is triggered, skipping the submission attempt of the current round and directly entering the next round of consensus; Step 4.3: Calculate the consensus timestamp of the free vertices, specifically including: (1) Discard the node local clock and force the use of the STC. As a timing reference; (2) For the same round The leader failed to reach the free vertex submitted by the leader. First, extract the vertices. direct ancestor set and its descendants ; (3) Merge sets Filter out All Node declaration Calculate the median of this time series. and will Officially designated as the vertex The final consensus timestamp; Step 4.4: Establish the total order arrangement rule for the vertices of the DAG, and set the global linearization sort priority of the vertices in the DAG as follows: ① Round (ascending order): Prioritize processing vertices with smaller round numbers; ② Consensus timestamp ( Ascending order: Within the same round, assign... Vertices with smaller numerical values ​​have higher priority. ③ Vertex hash lexicographical order: If the timestamps are the same, they are arranged according to the lexicographical order of the vertex hash values; ④ Random number XOR result ascending order: If the hash values ​​are still the same, they are arranged in ascending order according to the preset random number XOR result to resolve extreme conflicts; Step 4.5: Perform block timestamp deviation verification, specifically including: (1) Physical nodes When a new block is generated, its block header timestamp must include a valid one. ; (2) Local Fragmentation Maintain a preset maximum permissible deviation window for STC-UTC. ; (3) When a node receives a new block, it verifies the deviation between the block header timestamp and the locally maintained valid STC-UTC reference; if the absolute value of the deviation exceeds the threshold... If the block is not found, it will be immediately discarded and refused to be added to the blockchain.

[0027] In summary, the metaverse anti-attack consensus method and system based on spatiotemporal information feature enhancement provided by this invention, by extending the consensus trust root from the fragile "logical identifier" to the immutable "physical spatiotemporal attributes," constructs an L1-L3 layered defense system. Compared with traditional consensus schemes and existing sharding technologies, it has the following significant advantages: (1) Eradicate node identity forgery and build a physical-level anti-Syllabus barrier: This invention breaks through the limitations of traditional consensus relying on IP address or logical ID for node authentication. It uses the Spatiotemporal Certificate (STC) to strongly bind the network identity of a node to its physical coordinates and high-precision clock. The STC filtering mechanism effectively identifies and eliminates "same-origin cluster" nodes, fundamentally eliminating the possibility of attackers using virtualization technology to forge the illusion of "geographical dispersion", and improving the defense capability against Sybil attacks to the physical hardware level. (2) Resisting timestamp manipulation and establishing objective causal order: In response to time fraud methods such as NTP spoofing and clock rollback, this invention abandons the easily contaminated local clock of the node and instead uses the UTC timestamp in STC as the sole time reference for consensus; by introducing a Leader election mechanism based on the median of STC-UTC and a free vertex timestamp arbitration algorithm in DAG consensus, the objectivity and determinism of the transaction ordering of the entire network are ensured, and the double-spending attack, transaction replay and DAG topology destruction caused by malicious time tampering are effectively prevented. (3) Achieve decoupling of performance and security to meet the high concurrency requirements of the metaverse: The DASH layered architecture proposed in this invention maintains a lightweight cross-shard index through global sharding and processes high-throughput transactions through local sharding. Combined with block header compression technology, it significantly improves storage scalability while controlling consensus latency to the millisecond level. In particular, the sharding strategy based on physical proximity significantly reduces the Gossip propagation latency of DAG within the shard, solving the performance bottlenecks of "security being diluted with the increase of shards" and "poor scalability of chain structure" in traditional sharding technology. (4) Strengthen privacy protection and separation of duties to safeguard user sovereignty: Through the complete decoupling of logical nodes (LN) and physical nodes, this invention achieves strict separation of duties of "physical host does not sign on behalf of others"; even if the physical device is compromised, the attacker can only cause denial of service because he cannot obtain the user's DID private key, and cannot forge the user's identity or steal digital assets; at the same time, the application of coordinate digest technology can verify the authenticity of the node's geographical location while avoiding the plaintext exposure of the original coordinates, thus taking into account both compliance supervision and user location privacy. (5) Enhance system robustness and adapt to complex network environment: The global node election mechanism based on BLS threshold signature and DKG protocol, combined with Bullshark's asynchronous consensus characteristics, enables the system to maintain high availability while tolerating no more than 1 / 3 of Byzantine nodes; even in network partition or high jitter environment, the unpredictability based on STC entropy source can ensure the fairness of Leader election and avoid consensus stagnation.

[0028] The above description discloses only one preferred embodiment of the present invention, and should not be construed as limiting the scope of the present invention. Those skilled in the art will understand that all or part of the processes of the above embodiments can be implemented, and equivalent changes made in accordance with the claims of the present invention are still within the scope of the invention.

Claims

1. A metaverse anti-attack consensus method and system based on spatiotemporal information feature enhancement, characterized in that, Includes the following steps: Step 1: Physical nodes connected to the network generate Spatiotemporal Certificates (STCs). Step 2: The consensus system performs global node election and sharding construction; Step 3: The consensus system constructs a three-layer mapping architecture of physical nodes, shard ownership, and logical nodes; Step 4: The consensus system performs DAG timing arbitration based on STC-UTC.

2. The metaverse anti-attack consensus method and system based on spatiotemporal information feature enhancement as described in claim 1, characterized in that, Step 1: Physical nodes connected to the network generate Spatiotemporal Certificates (STCs). Step 1.1: Physical Nodes Obtain current physical coordinates from the location source. ,in For latitude, For longitude, Altitude; Step 1.2: To prevent user location from being leaked due to plaintext coordinates, physical nodes... Generate local random numbers and call the collision-resistant hash function. Calculated coordinate summary ; Step 1.3: Physical Nodes Obtain Coordinated Universal Time (UTC) timestamps from a high-precision clock source. And read the identifier of the clock source. Subsequently, physical nodes Will Send to a local trusted time source, which will then process the data. Issuance of clock source trust certificate ;in cryptographic types and Security level binding: When For high-precision time sources, chip-level atomic clocks or dual-frequency timekeeping, For short signatures within a trusted execution environment; when When used as a medium-precision time source or a single frequency, For timestamp authority tokens; when When it is a low-precision time source (NTP), It is a symmetric key message authentication code; Step 1.4: Physical Nodes Assemble the spacetime certificate and using their own private key right Perform digital signature to obtain ,in It is the identity identifier of the physical node; subsequently, the physical node Will It is broadcast to the entire network as its own spatiotemporal anchoring certificate; Step 1.5: When any subsequent node or shard receives a physical node... When sending a message, first use the public key. Verify signature Then verify with the public key of the trusted time source. If both verifications pass, then it is considered valid. Valid, marked as .

3. The metaverse anti-attack consensus method and system based on spatiotemporal information feature enhancement as described in claim 2, characterized in that, Step 2: The consensus system performs global node election and sharding construction; Step 2.1: Collect and filter spatiotemporal credentials to generate a candidate physical node set. Specifically, it includes: (1) After all nodes in the network publish the STC, the pre-set coordinating node for this epoch obtains the broadcast STCs for the entire network within the current epoch. ; (2) The coordination node verifies each node one by one. signature Proof with a clock And perform two-level rejection: if If the verification is invalid, the node is removed directly; if If the security level is lower than the preset threshold, the node will be removed. (3) For the remaining nodes that have passed the above two-level filtering, the coordination node summarizes their coordinates. Mapped to a preset geographic grid Perform cluster detection: if the same grid Internal appearance Homogeneous and number of nodes In such cases, it is identified as a "pseudo-geographical dispersion" cluster, used to prevent attackers from using multiple instances in the same data center to forge multiple geographical locations. This is a preset cluster density threshold; downsampling is performed on this cluster, retaining at most one node, with the retention rule being to take... The earliest one, or take The node with the smallest lexicographical order is moved to the local sharding candidate pool; (4) The set of candidate physical nodes obtained after filtering is denoted as ,in This represents the total number of candidate physical nodes. Step 2.2: Based on the candidate set Generate the lottery seed and threshold key, and perform BLS lottery, specifically including: (1) with All according to Merkle roots are calculated by concatenating lexicographical orders and denoted as . This serves as the global seed for this epoch; each within Refresh at each epoch to ensure unpredictability; (2) Candidate set All internal nodes operate together Distributed Key Generation Protocol (DKG), in which The BLS threshold value satisfies , Generate their respective threshold key fragments And export the corresponding group public key. It is stored by all nodes; (3) Each node by Calculate the BLS lottery factor using the input: ， in For collision-resistant hash functions; Mapped to Interval obtained ; (4) Based on binomial distribution Will The interval is divided into consecutive small intervals : ， in , The target size of the global partitioning for this epoch, and satisfying the following conditions: ,and This ensures that the elected candidate is capable of reconstructing the BLS threshold signature; (5) When a certain node of and At that time, the judgment Once selected as a candidate global node, it will proceed to the next round of confirmation. Step 2.3: Broadcast and confirm candidate global nodes to form a global shard, specifically including: (1) Candidate global nodes Broadcast to the entire network ,in for Verification evidence for the correctness of the computation includes the group's public key. and corresponding Aggregate signature fragments; (2) Use at any node in the entire network Verify the aggregation path; those that pass the verification are officially designated as global nodes, denoted as [node name missing]. All global nodes constitute a set ,Depend on Forming a global partition; (3) Global sharding maintains the following states: one is the cross-shard DID index. The first is for DID cross-application domain routing; the second is for inter-shard consensus, used to handle cross-shard DID migration, cross-shard VC verification, cross-shard transactions and other transactions that require coordination among multiple shards. Step 2.4: Divide the local space into fragments, specifically including: (1) Not selected for global fragmentation The remaining nodes are assigned to local partitions according to the metaverse two-dimensional partitioning strategy. One type is the geographical region, as described in step 2.

3. Mapped geographic grid One approach is to define the geographical domain, making nodes physically adjacent within the same geographical domain and reducing intra-slice DAG Gossip latency; the other approach is to define the application domain, which is defined by the metaverse business logic, making DID transactions semantically similar within the same application domain and improving intra-slice DAG concurrency. (2) Each combination of (regional domain, application domain) constitutes a local shard. ,in For fragmentation ; (3) Each local shard Internally, a directed acyclic graph (DAG) structure is used to implement intra-chip consensus and maintain user relationships within the domain. DID document records With verifiable credentials (VC).

4. The metaverse anti-attack consensus method and system based on spatiotemporal information feature enhancement as described in claim 3, characterized in that, Step 3: The consensus system constructs a three-layer mapping architecture of physical nodes, shard ownership, and logical nodes; Step 3.1: Determine the sharding affiliation of physical nodes, specifically including: (1) Physical Nodes After the election process in step 2, if a node is elected as a global node, it will belong to the global shard. If not selected, it will be assigned to the unique local fragment according to the two-dimensional fragmentation strategy determined in step 2.4, i.e., (regional domain, application domain). and obtain Level 2 (L2) identity identification. "as" Shard nodes participate in the intra-shard directed acyclic graph (DAG) consensus; (2) Within a single epoch, a single physical node is limited. It can only belong to one shard, either a global shard or a local shard, in order to prevent the same physical entity from forming a Sybil attack lever across multiple shards; Step 3.2: Manage logical nodes and establish a global routing index, specifically including: (1) Physical Nodes In its local shard Internally, it hosts at least one logical node. The logical node is defined as a triplet structure: ,in, For user identification, For users The W3C standard distributed digital identity document anchor, containing the public key. , server endpoint and undo list pointer; For users In the application domain Metadata of the incarnation; For users A set of verifiable credentials held; (2) Allow the same user In multiple different application domains Register logical nodes separately Each logical node independently maintains a corresponding DID document shard copy; (3) Global fragmentation Maintain cross-slice DID index Used to respond to user-related issues across the entire network. Cross-application domain routing query requests; Step 3.3: Implement permission isolation between the physical host and the logical identity, specifically including: (1) Define the boundaries of storage and execution responsibilities: logical nodes The maintenance of DID documents and verifiable credentials is handled by the local shard to which they belong. Responsible for; physical nodes As only The execution host provides network forwarding, storage I / O, and STC spatiotemporal anchoring capabilities, but does not possess... DID private key signing permissions; (2) Enforce client-side signature policy: Any operation involving DID, including but not limited to registration, update, revocation, VC issuance / verification, and cross-domain migration, must be performed by the user. I used the private key Signature; even physical nodes The system was maliciously compromised, and the attackers were unable to obtain [access / resources]. It can only cause a denial of service or tamper with a local storage copy, but cannot forge a user. Any DID semantic operations; (3) Forming a two-layer defense closed loop: The STC anchoring in step 1 constitutes the first layer of defense (L1), which is used to prevent malicious nodes from spoofing geographical locations or clocks and mixing into multiple fragments during the filtering stage in step 2.1; the separation of duties in this step constitutes the second layer of defense (L3), which prevents the spread of the virus due to physical hosts. The compromised system resulted in the hijacking of a batch of logical nodes (LNs) hosted by the system, thus converging the attack surface to the storage layer and preventing identity spoofing.

5. The metaverse anti-attack consensus method and system based on spatiotemporal information feature enhancement as described in claim 4, characterized in that, Step 4: The consensus system performs DAG timing arbitration based on STC-UTC; Step 4.1: Construct a DAG structure embedding spatiotemporal credentials, specifically including: (1) In each local shard Internally, it adopts Bullshark consensus and uses Narwhal as its underlying DAG memory pool; the vertices in the DAG are defined as transaction batches, and the directed edges between vertices are defined as causal reference relationships and STC anchoring relationships; (2) Force the embedding of its physical node into each vertex structure. The STC core fields include at least the coordinate summary. UTC timestamp and clock source identifier ; (3) Global fragmentation Periodically partition the local partition. Randomly sample vertices within the range to verify the information they carry. Effectiveness to curb long-term cheating behavior; Step 4.2: Perform Leader election and deterministic commit based on STC entropy source, specifically including: (1) The Bullshark protocol proceeds in rounds; each round elects a leader using a deterministic algorithm: based on the network's STC. The median, as the primary entropy source, is used through a collision-resistant hash function. Derivative primary seed ; Total number of candidate nodes for this sub-seed Take the modulus to obtain the Leader offset. In the list of candidate nodes arranged lexicographically by pk, the first... Each node is elected as the Leader in this round; since the main entropy source depends on the real time median of the network's STC, malicious nodes cannot predict or manipulate the sub-seeds, thus making it impossible to predict the Leader sequence and effectively resisting targeted network attacks. (2) The vertex submitted by the current leader receives at least When a vertex receives a strong visible vote from several other nodes, it has reached a deterministic commit. This represents the number of fault-tolerant nodes. (3) If the Leader times out in the current round, or if the vertex it submits fails to achieve strong visibility within the specified time, the "scythe rule" of the next round is triggered, skipping the submission attempt of the current round and directly entering the next round of consensus; Step 4.3: Calculate the consensus timestamp of the free vertices, specifically including: (1) Discard the node local clock and force the use of the STC. As a timing reference; (2) For the same round The leader failed to reach the free vertex submitted by the leader. First, extract the vertices. direct ancestor set and its descendants ; (3) Merge sets Filter out All Node declaration Calculate the median of this time series. and will Officially designated as the vertex The final consensus timestamp; Step 4.4: Establish the total order arrangement rule for the vertices of the DAG, and set the global linearization sort priority of the vertices in the DAG as follows: ① Round (ascending order): Prioritize processing vertices with smaller round numbers; ② Consensus timestamp ( Ascending order: Within the same round, assign... Vertices with smaller numerical values ​​have higher priority. ③ Vertex hash lexicographical order: If the timestamps are the same, they are arranged according to the lexicographical order of the vertex hash values; ④ Random number XOR result ascending order: If the hash values ​​are still the same, they are arranged in ascending order according to the preset random number XOR result to resolve extreme conflicts; Step 4.5: Perform block timestamp deviation verification, specifically including: (1) Physical nodes When a new block is generated, its block header timestamp must include a valid one. ; (2) Local Fragmentation Maintain a preset maximum permissible deviation window for STC-UTC. ; (3) When a node receives a new block, it verifies the deviation between the block header timestamp and the locally maintained valid STC-UTC reference; if the absolute value of the deviation exceeds the threshold... If the block is not found, it will be immediately discarded and refused to be added to the blockchain.

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