A digital identity verification method and system based on hierarchical true value verification

Abstract

This invention discloses a digital identity verification method and system based on layered truth verification, belonging to the fields of information security and discrete logic technology, and is particularly suitable for dynamic identity status management in financial anti-fraud scenarios. Existing technologies employ a "static snapshot + probability judgment" architecture, which cannot address the verification requirements of dynamically changing identity status over time. This invention, based on the underlying theory of Discrete Spatiotemporal Scaling Law (T-DS), layers identity-related propositions into a first type of proposition (structural propositions, permanently locked, corresponding to the T-DS anchor layer) and a second type of proposition (factual propositions, dynamically falsifiable, corresponding to the Working Memory layer). Through modules such as parent quarantine, clone verification, dual-track memory management, and chain auditing, it achieves a unity between the unforgeability of identity anchors and the dynamic updability of identity status. The system includes a proposition layering module, a first-type verification module, an evidence structure module, a contradiction detection module, a weight comparison module, a truth database module, an audit chain module, a parent quarantine module, a clone verification module, and a memory management module.

Description

[Technical Field]

[0001] This invention relates to the fields of information security and discrete logic technology, specifically to a digital identity verification method and system based on hierarchical truth verification, which is particularly suitable for dynamic identity status management in financial anti-fraud scenarios. [Background Technology]

[0002] With the rapid development of digital finance, financial crimes such as identity forgery, account misuse, and telecommunications fraud are becoming increasingly rampant. Existing digital identity verification systems mainly employ the following technical approaches:

[0003] (1) Biometric technology: Identity verification is performed using static biometric features such as fingerprints, faces, and irises. However, once biometric features are copied or bypassed by AI face-swapping, deepfakes, or other technologies, identity verification fails. More seriously, biometric features are irreplaceable sensitive information, and once a centralized database is leaked, it will cause irreversible and catastrophic consequences.

[0004] (2) Artificial intelligence risk control model: Risk judgment is based on probability scoring of user behavior. This type of model has a dual dilemma of false positives (normal users are wrongly rejected) and false negatives (professional fraud gangs bypass the model through behavioral simulation). Its essence is to use probabilistic uncertainty to fight against the deterministic requirement of identity verification.

[0005] (3) Centralized static identity database: Identity status is stored in a centralized database in the form of snapshots. Once the status is confirmed and entered into the database, it is permanently locked. This architecture cannot adapt to the dynamic evolution of identities. For example, user documents have been updated, but the system still refuses service based on the old status (false positive); fraudulent accounts initially appear normal, and the system does not re-verify them after confirmation until the case is discovered (slips through the net).

[0006] The common flaw in existing technical solutions lies in their use of a "static snapshot + probabilistic judgment" architecture, which fails to address the verification requirements of dynamically changing identity status over time. A deeper problem is that existing systems assume information is continuously and infinitely divisible, lacking coupling with the underlying discrete physical structure, leading to singularities and undecidability at boundaries.

[0007] Starting from first principles, inventor Wang Weidong proposed the Discrete-Time Scale Law (T-DS), revealing that the essence of space is a 10-square discrete chessboard (S=10), and the essence of time is 12 continuous rivers (T=12), with the number of missing segments Δ=2 constituting quantum leap channels. Based on this theory, this invention constructs a hierarchical truth verification architecture: the first type of proposition (structural proposition) corresponds to the T-DS anchor layer, permanently locked to ensure unforgeability; the second type of proposition (factual proposition) corresponds to the T-DS dynamic evolution layer, dynamically updated to ensure strong system adaptability. Both work collaboratively within the same architecture without interfering with each other. [Summary of the Invention]

[0008] The present invention aims to solve the above-mentioned problems existing in the prior art and provides a digital identity verification method and system based on hierarchical truth verification. By hierarchically dividing identity-related propositions into analytical propositions and comprehensive propositions, and allowing them to enter different verification channels, the unforgeability of identity anchors and the dynamic updability of identity status are achieved.

[0009] The technical solution adopted by this invention to solve its technical problem is:

[0010] A digital authentication method based on hierarchical truth verification includes the following steps:

[0011] S1. Receive identity-related propositions to be verified, and perform hierarchical judgment on the propositions to determine whether they belong to the first type of proposition or the second type of proposition; wherein, the first type of proposition is a structural proposition, which includes mathematical axioms, logical definitions, and algorithm rules, corresponding to the anchor layer parameters in the T-DS discrete-time scaling law; the second type of proposition is a factual proposition, which includes identity status declarations, behavioral evidence, and risk assessment conclusions, corresponding to the dynamic evolution layer in the T-DS discrete-time scaling law.

[0012] S2. If the proposition is a proposition of the first type, perform a uniqueness check: calculate the hash value of the proposition, and search the truth database to see if a proposition of the first type with the same hash value and in an active state already exists; if it already exists, reject the proposition from being added to the database; if it does not exist, mark the proposition as active and permanently lock it, and its truth state cannot be overturned by any subsequent evidence. The permanent locking corresponds to the immutable property of the anchor layer in the T-DS scaling law.

[0013] S3. If the proposition is of the second type, an evidence structure is required; the evidence structure shall include at least: evidence weight value, evidence source identifier, verification method identifier, and reproducibility marker.

[0014] S4. Perform semantic contradiction detection between the second type of proposition and the activated second type of proposition in the truth database. When two propositions are detected to be semantically mutually exclusive, compare their evidence weight values. If the evidence weight value of the new proposition is greater than that of the old proposition, mark the old proposition as falsified and remove its activation mark, and mark the new proposition as activated. If the evidence weight value of the new proposition is less than or equal to that of the old proposition, reject the new proposition from being added to the database. The falsification mechanism corresponds to the dynamic update and overflow replacement rules of Working Memory in the T-DS scaling law.

[0015] S5. Output the verification result, which includes the activation state, falsification state, and corresponding evidence structure information of the proposition.

[0016] Furthermore, the hierarchy determination in step S1 includes: detecting whether the content of the proposition contains preset structural keywords; if it contains them, it is determined to be the first type of proposition; if it does not contain them, it is determined to be the second type of proposition.

[0017] Furthermore, the semantic contradiction detection in step S4 includes: detecting whether the contents of the two propositions simultaneously contain a preset pair of mutually exclusive keywords; if they do, they are determined to be semantically mutually exclusive.

[0018] Furthermore, the method also includes: generating an audit chain entry for each verification operation, wherein the audit chain entry includes an operation sequence number, a timestamp, an operation type, operation details, a hash value of the previous destination, and a hash value of the current entry; the hash value of the current entry is calculated jointly by the hash value of the previous destination, the current timestamp, and the current operation content, forming a chained hash structure. The audit chain corresponds to the immutable audit chain module in the T-DS scaling law.

[0019] Furthermore, the method is applied to financial anti-fraud scenarios, and the second type of proposition includes at least one of the following: user identity validity statement, account status statement, transaction environment security statement, device fingerprint information, geolocation information, and behavioral pattern information.

[0020] Furthermore, in the aforementioned financial anti-fraud scenario, the evidence weight values ​​are assigned according to the following rules: comparison results from a national-level identity database have a weight value of 90 to 100; analysis results from the internal risk control system of a financial institution have a weight value of 80 to 90; verification results from a trusted third-party service provider have a weight value of 60 to 80; materials submitted by the user have a weight value of 20 to 40; and information collected locally from a single device has a weight value of 10 to 30.

[0021] The present invention also provides a digital identity verification system based on hierarchical truth verification, comprising:

[0022] The proposition layering module is used to receive identity-related propositions to be verified and determine whether they belong to the first type or the second type of proposition.

[0023] The first type of verification module is used to perform uniqueness verification on the first type of proposition, including a hash calculation unit, a duplicate detection unit, and a permanent locking unit;

[0024] The evidence structure module is used to generate and manage evidence structures for the second type of proposition.

[0025] The contradiction detection module is used to perform semantic contradiction detection between the second type propositions to be added to the database and the second type propositions that have been activated in the truth database.

[0026] The weight comparison module is used to compare the evidence weight values ​​of two propositions when a semantic contradiction is detected, and decide whether to retain the old proposition or accept the new proposition based on the comparison result.

[0027] The truth library module is used to store first-type propositions and second-type propositions in a hierarchical manner. The first-type propositions are stored in a permanently locked manner, corresponding to the T-DS anchor layer. The second-type propositions are stored in a manner with attached evidence structures and support switching between active and falsified states, corresponding to the T-DS dynamic evolution layer.

[0028] The audit chain module is used to generate an immutable audit chain entry for each verification operation, forming an audit log with a chain hash structure.

[0029] The parent quarantine module is used to pre-screen the propositions before they enter the proposition hierarchical module; the pre-screening includes expansion detection, loop closure detection, discrete transformation detection, minimum marked state mapping detection, and curvature injection detection; the parent quarantine module corresponds to the parent quarantine engine in the T-DS scaling law;

[0030] The clone verification module is used to simulate the operation of the proposition in an isolated environment to test its compatibility with the existing axiomatic system of the system, the compatibility of behavioral constraints, the compatibility of closed-loop capability, and the system expansion pressure; the proposition is allowed to enter the proposition layering module only when all tests pass; the clone verification module corresponds to the clone verification sandbox in the T-DS scaling law;

[0031] The memory management module includes a temporary memory unit and a long-term memory unit. The temporary memory unit caches recently received propositions in a high-fidelity manner, with limited capacity and no compression, corresponding to the Working Memory in the T-DS scaling law. The long-term memory unit stores fixed propositions in an importance-level manner, corresponding to the Persistent Memory in the T-DS scaling law.

[0032] Furthermore, in the truth base module, the second type of proposition marked as falsifiable is not deleted from the base, but is retained as a historical record, and is marked with the identifier of the new proposition that refutes the proposition and the refutation timestamp, so as to form a complete cognitive evolution chain.

[0033] Furthermore, the memory management module also includes a T-DS anchor layer for storing immutable spatiotemporal scaling law core parameters.

[0034] Furthermore, the system also integrates a T-DS spatiotemporal duality verification module, which is used to verify in real time whether the complementarity of spatial density 3 / 7 and time period 7 / 12 during system operation converges to the 85 / 84 boundary margin.

[0035] Furthermore, the system also integrates a hook proof verification module, which is used to perform two-way hook anchoring verification on key verification conclusions.

[0036] The beneficial effects of this invention are:

[0037] (1) It solves the dilemma of static databases. Existing technologies permanently lock identity status in the form of snapshots, which cannot adapt to dynamic changes. This invention, through the dynamic falsification mechanism of the second type of proposition, enables identity status to be updated in real time with new evidence, so as not to mistakenly kill normal users due to outdated information, nor to miss abnormal operations due to lack of verification.

[0038] (2) Separate management of structural attributes and state attributes has been achieved. The mathematical structure of the identity anchor belongs to the first type of proposition, and permanent locking ensures that it cannot be forged; the identity behavior evidence belongs to the second type of proposition, and dynamic updating ensures that the system is highly adaptable. The two work together under the same architecture without interfering with each other.

[0039] (3) It provides a definitive mechanism for resolving conflicts. When evidence from different sources conflicts with each other, the system does not rely on fuzzy comprehensive scoring, but makes precise comparisons through quantified evidence weight values. The evidence with higher weight covers the evidence with lower weight, and the resolution result is interpretable, traceable, and auditable.

[0040] (4) An immutable audit chain has been constructed. Every verification operation, every state change, and every disproven refutation is recorded in the audit log with a chain hash structure, forming a complete cognitive evolution chain and meeting the compliance requirements of financial regulators for operational traceability.

[0041] (5) Ensuring consistency at the underlying level. The T-DS spatiotemporal duality verification module ensures that the system always operates under the constraints of the discrete spatiotemporal scaling law, preventing underlying drift; the parent quarantine and clone verification module ensures that external knowledge is strictly screened before entering the system, preventing virus contamination. [Attached Image Description]

[0042]

【 Figure 1 Overall Flowchart of a Layered Truth Validation-Based Digital Identity Authentication Method

[0043] Diagram type: Flowchart

[0044] Illustration content:

[0045] This diagram illustrates the complete steps of digital identity verification in a vertical main process, with horizontal branches.

[0046] Step 101 (light blue): Receive propositions - Receive identity-related propositions to be verified.

[0047] Step 102 (purple): Hierarchical determination - Detect whether the proposition content contains structural keywords.

[0048] Step 103 (yellow): Determine the type - determine whether it belongs to the first type of proposition or the second type of proposition.

[0049] Step 104 (blue, left branch): First type of proposition - perform uniqueness check (hash calculation → duplicate detection → permanent lock).

[0050] Step 105 (blue): Hash Duplicate Detection + Permanent Locking - Mark the first occurrence of the first type of proposition as active and lock it permanently.

[0051] Step 106 (green, right branch): Type II proposition - requires attached evidence structure (quadruple: evidence weight value, evidence source identifier, verification method identifier, reproducibility marker).

[0052] Step 107 (orange): Semantic contradiction detection - Perform semantic contradiction detection between the second type of proposition and the activated propositions in the truth bank.

[0053] Step 108 (yellow): Determine if there is a contradiction - check whether the two propositions are semantically mutually exclusive.

[0054] Step 109 (purple): Weight Comparison - Compare the evidence weights of the two propositions.

[0055] Step 110 (red): Falsification decision - the evidence with higher weight covers the evidence with lower weight, and the old proposition is marked as falsified.

[0056] Step 111 (Green): Mark Activation and Add to Database - New propositions are marked as active and added to the database.

[0057] Step 112 (grey): Generate audit chain - Generate an immutable audit chain entry for each verification operation.

[0058] Step 113 (light blue): Output verification results - Output the activation state, falsification state, and evidence structure information of the proposition.

[0059]

【 Figure 2 [Propositional layering and dual-channel processing logic diagram]

[0060] Graph type: Logical branch diagram (Y-type)

[0061] Illustration content:

[0062] This diagram uses a Y-shaped branch to illustrate the dual-channel processing logic after the proposition is layered.

[0063] Enter the following at the top (light blue): "Proposition to be verified"

[0064] → Decision box (purple diamond): "Structural keywords?"

[0065] Left branch (blue) - Type I proposition channel:

[0066] - Yes → Hash Calculation → Duplicate Detection → Permanent Locking

[0067] -Enter the T-DS anchor layer (cannot be tampered with)

[0068] -Note "T-DS anchor layer = immutable"

[0069] Right branch (green) - Second type of proposition channel:

[0070] -No → Evidence Structure → Contradiction Detection → Weight Comparison

[0071] - Enter Working Memory (Dynamically Updated)

[0072] -Note "Working Memory = Dynamically Updated"

[0073] Bottom convergence (gray): "Audit chain record | Immutable"

[0074] Bottom label: "T-DS: Anchor layer = immutable, Evolution layer = dynamically updated"

[0075]

【 Figure 3 [Sequence Diagram of Dynamic Falsification Mechanism for Type II Propositions]

[0076] Graph type: Time series diagram

[0077] Illustration content:

[0078] This diagram uses time on the horizontal axis and propositional state on the vertical axis to illustrate the temporal evolution of the dynamic falsification mechanism.

[0079] Timeline: Shows the sequence of events from left to right.

[0080] Event point (vertical rectangle):

[0081] -t1: P1 activation (weight 30, green)

[0082] -t2: P2 activation (weight 95, green)

[0083] -t3: P3 disproves P1 / P2 (weight 98, red), P3 activates (green).

[0084] -t4: P4 disproves P3 (weight 99, red)

[0085] Status line:

[0086] -P1,P2 activation period (green horizontal line)

[0087] -P1,P2 falsification period (red descending line)

[0088] -P3 Activation Period (Green Horizontal Line)

[0089] -P3 Falsification Period (Red Declining Line)

[0090] Bottom label: "The one with higher weighting of evidence covers the one with lower weighting of evidence"

[0091] Top label: "T-DS: Working Memory Dynamic Update and Overflow Replacement Rules"

[0092]

【 Figure 4 A schematic diagram of the chained hash structure of the audit chain.

[0093] Diagram type: Chain structure diagram

[0094] Illustration content:

[0095] This diagram illustrates the immutable structure of the audit chain using horizontal chains.

[0096] Nodes (rectangles, arranged horizontally):

[0097] - Node 1 (light blue): Operation sequence number 001 | Timestamp 2026-05-13 | Hash 0xA1B2 | Previous hash 0x0000

[0098] - Node 2 (green): Operation sequence number 002 | Timestamp 2026-05-13 | Hash 0xC3D4 | Previous hash 0xA1B2

[0099] - Node 3 (yellow): Operation sequence number 003 | Timestamp 2026-05-13 | Hash 0xE5F6 | Previous hash 0xC3D4

[0100] - Node 4 (orange): Operation sequence number 004 | Timestamp 2026-05-13 | Hash 0xG7H8 | Previous hash 0xE5F6

[0101] - Node 5 (red): Operation sequence number 005 | Timestamp 2026-05-13 | Hash 0xI9J0 | Previous hash 0xG7H8

[0102] Arrow connections: Each node points to the next one, marked "hash dependency".

[0103] Tampering illustration (bottom):

[0104] The red dashed line points to node 2, marked "Tampered with this node →".

[0105] The arrow points to a subsequent node, marked "All subsequent hash values ​​are invalid".

[0106] Bottom label: "Chained hash structure: Current hash = f(previous hash + timestamp + operation content)"

[0107]

【 Figure 5 System module architecture diagram

[0108] Diagram type: System architecture diagram

[0109] Illustration content:

[0110] This diagram illustrates the system's 12 modules using a layered architecture.

[0111] Upper-level modules (arranged horizontally):

[0112] -501 Propositional Layering (Purple)

[0113] -502 Type I Checksum (Blue)

[0114] -503 Evidence Structure (Green)

[0115] -504 Contradiction Detection (Orange)

[0116] -505 weight comparison (purple)

[0117] Lower-level modules (arranged horizontally):

[0118] -506 Truth Value Library (Gray)

[0119] -507 Audit Chain (Gray)

[0120] -508 Maternal Quarantine (Cyan)

[0121] -509 Cloning Verification (Brown)

[0122] -510 Memory Management (Pink)

[0123] New module (dark red, [New]):

[0124] -511 T-DS Spatiotemporal Duality Verification Module

[0125] -512 Hook Proof Verification Module

[0126] Connection arrows: Modules are connected by gray arrows, indicating the direction of data flow.

[0127] Input / output arrows: left for input, right for output.

[0128] Bottom label: "New Modules 511 / 512 (Dark Red): T-DS Low-Level Verification and Hook Proof Verification"

[0129]

【 Figure 6 Data Flow Diagram for Financial Account Opening Scenarios

[0130] Graph type: Data flow graph

[0131] Illustration content:

[0132] This diagram illustrates the data flow between the various participants in a financial account opening scenario.

[0133] Participants (arranged horizontally, colored rectangles):

[0134] -User App (light blue)

[0135] -Banking system (green)

[0136] -Ministry of Public Security Population Database (purple)

[0137] -The court system (red)

[0138] Data flow (with arrows connecting the points, and labels indicating propositions and weights):

[0139] -User App → Bank System: P1 Application (Weight 30, Blue)

[0140] -Banking system → Ministry of Public Security population database: P2 comparison (weight 95, green)

[0141] -Ministry of Public Security Population Database → Banking System: P2 Activation (Purple)

[0142] -Court System → Banking System: P3 Judgment (Weight 98, Red)

[0143] -Banking System → User App: P1 / P2 Authentication, P3 Activation (Dark Red)

[0144] Truth library (gray rectangle at the bottom):

[0145] Label "Truth Library | Falsify P1 | Falsify P2 | Activate P3"

[0146] Bottom label: "Financial account opening scenario: P1(30)→P2(95)→P3(98) falsification coverage"

[0147]

【 Figure 7 Data Flow Diagram for Transfer Risk Control Scenarios

[0148] Graph type: Data flow graph

[0149] Illustration content:

[0150] This diagram illustrates the weight comparison and falsification decision in a transfer risk control scenario.

[0151] Participants (arranged horizontally):

[0152] - User actions (light blue)

[0153] - Anti-fraud system (orange)

[0154] -Banking Core (Green)

[0155] Data flow:

[0156] -User Operations → Anti-Fraud System: P4 Account Normal (Weight 25, Blue)

[0157] -Anti-fraud system → Bank core: P5 account abnormal (weight 88, green)

[0158] Weight comparison (central purple diamond):

[0159] Label "Weight Comparison | 88 > 25"

[0160] Falsification ruling (red rectangle below):

[0161] Marked "Falsification Decision | P4 Falsification | P5 Activation"

[0162] Transaction rejected (dark red rectangle at the bottom):

[0163] Mark "Transaction Rejected"

[0164] Bottom label: "Transfer risk control scenario: P4(25) vs P5(88) → 88 covers 25 → Transaction rejected"

[0165]

【 Figure 8 [New] Mapping diagram between T-DS scaling law and hierarchical truth verification

[0166] Graph type: Mapping graph

[0167] Illustration content:

[0168] The left side of this diagram represents the T-DS theoretical layer, the right side represents the hierarchical truth verification system layer, and the two sides are mapped together by a bidirectional arrow.

[0169] Left side - T-DS theoretical layer (dark red background box):

[0170] -S = 10 (spatial cardinality)

[0171] -T = 12 (time base)

[0172] -Δ = 2 (number of vacant slots)

[0173] -3 / 7 (spatial density)

[0174] -7 / 12 (time period)

[0175] -85 / 84 (boundary margin)

[0176] - Anchor layer (unalterable, pink)

[0177] - Evolutionary layer (dynamically updated, green)

[0178] Right side - System layer (green background box):

[0179] - First type of proposition (permanently locked, blue)

[0180] - Type II propositions (dynamic falsification, green)

[0181] -Maternal Quarantine Module 508 (Cyan)

[0182] -Duplicate verification module 509 (brown)

[0183] - Audit Chain Module 507 (Gray)

[0184] -Memory Management Module 510 (Pink)

[0185] -T-DS Dual Verification Module 511 (Dark Red)

[0186] - Hook Proof Module 512 (Dark Red)

[0187] Mapping arrows: One-to-one correspondence, indicating the mapping relationship.

[0188] Bottom label: "Each parameter of T-DS has a corresponding module in the hierarchical truth verification system."

[0189]

【 Figure 9 [Maternal Quarantine and Doppelganger Verification Flowchart] [New]

[0190] Diagram type: Flowchart (two-part)

[0191] Illustration content:

[0192] This diagram is divided into two sections, showing the dual verification process before external knowledge enters the main system.

[0193] Top section - Maternal quarantine (cyan background frame):

[0194] Label "Mother Quarantine"

[0195] Six detection steps (arranged horizontally):

[0196] 1. Inflation Detection - No Snake Game

[0197] 2. Loop closure detection - convergence is required.

[0198] 3. Discrete Transformation - Continuous → Discrete

[0199] 4. Minimum Marked State - 1_PCU Mapping

[0200] 5. Curvature Injection - Non-zero Verification

[0201] 6. Three Iron Laws - Verification

[0202] All approved → "Allow entry" (green)

[0203] Any failure → "Reject" (red, right arrow)

[0204] Next section - Cloning verification (brown background frame):

[0205] Marked "Duplicate Verification (Shadow Sandbox)"

[0206] Four test steps (arranged horizontally):

[0207] 1. Axiomatic Compatibility Test

[0208] 2. Behavioral compatibility test

[0209] 3. Closed-loop compatibility test

[0210] 4. Expansion pressure test

[0211] All passed → "Allow access to the topic layer" (green)

[0212] Any failure → "Reject" (red, right arrow)

[0213] Intermediate connection: Mother passes quarantine → Doppelganger verification

[0214] Bottom label: "T-DS: External knowledge ≠ usability; must undergo parent body quarantine + clone verification."

Detailed Implementation Methods

[0215] Example 1: Method Example

[0216] like Figure 1 As shown, this embodiment provides a digital identity verification method based on hierarchical truth verification, including the following steps:

[0217] Step 101: Receive the identity-related propositions to be verified.

[0218] Step 102: Perform a hierarchical determination on the proposition. Detect whether the proposition content contains preset structural keywords, including but not limited to: "axiom," "theorem," "BASE," "period," "hash algorithm," "anchor structure," "S=10," "T=12," "Δ=2," "Z_7," and "PCU-B7." If it contains these keywords, it is determined to be a first-type proposition (structural proposition); otherwise, it is determined to be a second-type proposition (factual proposition).

[0219] Step 103: Determine the proposition type. If it is a first-type proposition, proceed to step 104; if it is a second-type proposition, proceed to step 106.

[0220] Step 104: Perform uniqueness verification. Calculate the proposition hash value using the FNV-1a variant algorithm.

[0221] Step 105: Determine if this is the first occurrence. If a first-type proposition with the same hash value already exists in the truth bank and is in an active state, then the addition to the truth bank is rejected; if it does not exist, then it is marked as active and permanently locked.

[0222] Step 106: Require the attached evidence structure (quadruple: evidence weight value, evidence source identifier, verification method identifier, reproducibility marker).

[0223] Step 107: Perform semantic contradiction detection.

[0224] Step 108: Determine if a contradiction has been detected.

[0225] Step 109: Compare the evidence weight values.

[0226] Step 110: Execute the falsification ruling.

[0227] Step 111: Mark the proposition as active and add it to the database.

[0228] Step 112: Generate audit chain entries.

[0229] Step 113: Output the verification results.

[0230] Example 2: System Example

[0231] like Figure 5 As shown, this embodiment provides a digital identity verification system based on hierarchical truth verification, including a propositional hierarchical module 501, a first type verification module 502, an evidence structure module 503, a contradiction detection module 504, a weight comparison module 505, a truth database module 506, an audit chain module 507, a parent quarantine module 508, a clone verification module 509, a memory management module 510, a T-DS spatiotemporal dual verification module 511, and a hook proof method verification module 512.

[0232] Example 3: Application of Financial Account Opening Scenarios

[0233] like Figure 6As shown, a user initiates a remote account opening application through a bank's app, and the system generates proposition P1. After passing the initial inspection by the parent quarantine module 508, it enters the proposition layering module 501. P1 is determined to be a second-type proposition with an evidentiary structure and a weight value of 30. The contradiction detection module 504 does not find any mutually exclusive propositions, and P1 is marked as active and stored in the database. Subsequently, the Ministry of Public Security's population database API comparison generates P2 with a weight value of 95, which is directly marked as active. If the court system subsequently generates P3 "User X's identity is invalid - judicial judgment" with a weight value of 98, the contradiction detection module 504 detects mutual exclusion, and the weight comparison module 505 compares 98>95>30. P1 and P2 are marked as falsified, and P3 is activated. The audit chain module 507 records the complete falsification chain.

[0234] Example 4: Application of Transfer Risk Control Scenarios

[0235] like Figure 7 As shown, user Y initiates a large transfer. The system generates P4 "Account Y Status Normal - User Operation" with a weight of 25. The anti-fraud system generates P5 "Account Y Status Abnormal - Behavioral Graph Detection" with a weight of 88. The contradiction detection module 504 detects mutual exclusion, and the weight comparison module 505 compares 88 > 25. P4 is disproven, P5 is activated, and the system rejects the transfer.

[0236] Example 5: T-DS Spatiotemporal Duality Verification

[0237] Every 7 cycles (Z_7 cycle complete), the T-DS spatiotemporal duality verification module 511 automatically performs a low-level self-check: verifying 3 / 7 + 7 / 12 = 85 / 84 ≈ 1.0119, with a boundary margin of 0.0119 corresponding to the 1_PCU boundary return signal. If the deviation exceeds 1%, a low-level self-check alarm is triggered, suspending all verification operations until repair.

Claims

1. A digital identity verification method based on hierarchical truth verification, characterized in that, Includes the following steps: S1. Receive identity-related propositions to be verified, and perform hierarchical judgment on the propositions to determine whether they belong to the first type of proposition or the second type of proposition; wherein, the first type of proposition is a structural proposition, which includes mathematical axioms, logical definitions, and algorithm rules, corresponding to the anchor layer parameters in the T-DS discrete-time scaling law (spatial cardinality S=10, time cardinality T=12, number of vacant parts Δ=2, Z_7 period is full, curvature is non-zero), and its truth state is permanently locked and cannot be overturned; the second type of proposition is a factual proposition, which includes identity status declaration, behavioral evidence, and risk assessment conclusions, corresponding to the dynamic evolution layer in the T-DS discrete-time scaling law, and its truth state can be updated with new evidence; S2. If the proposition is a proposition of the first type, perform a uniqueness check: calculate the hash value of the proposition, and search the truth database to see if a proposition of the first type with the same hash value and in an active state already exists; if it already exists, reject the proposition from entering the database; if it does not exist, mark the proposition as active and permanently lock it, and its truth state cannot be overturned by any subsequent evidence; the permanent lock corresponds to the immutable property of the anchor layer in the T-DS scaling law; S3. If the proposition is of the second type, an evidence structure is required; the evidence structure shall include at least: evidence weight value, evidence source identifier, verification method identifier, and reproducibility mark; wherein, the evidence weight value is a numerical value that quantifies credibility, the evidence source identifier records the data source that generated the evidence, the verification method identifier records the technical means used to verify the evidence, and the reproducibility mark records whether other verifiers can independently reproduce the evidence; S4. Perform semantic contradiction detection between the second type of proposition and the activated second type of proposition in the truth database; when two propositions are detected to be semantically mutually exclusive, compare their evidence weight values; if the evidence weight value of the new proposition is greater than that of the old proposition, mark the old proposition as falsified and cancel its activation mark, and mark the new proposition as activated; if the evidence weight value of the new proposition is less than or equal to that of the old proposition, reject the new proposition from entering the database; the falsification mechanism corresponds to the dynamic update and overflow replacement rules of Working Memory in the T-DS scaling law; S5. Output the verification result, which includes the activation state, falsification state, and corresponding evidence structure information of the proposition.

2. The method according to claim 1, characterized in that, The hierarchical determination in step S1 includes: detecting whether the content of the proposition contains preset structural keywords; the structural keywords include: "axiom", "theorem", "BASE", "period", "hash algorithm", "anchor structure", "S=10", "T=12", "Δ=2", "Z_7", "PCU-B7"; if it contains them, it is determined to be the first type of proposition; if it does not contain them, it is determined to be the second type of proposition.

3. The method according to claim 1, characterized in that, The semantic contradiction detection in step S4 includes: detecting whether the contents of two propositions simultaneously contain a preset pair of mutually exclusive keywords; if they are simultaneously contained, they are determined to be semantically mutually exclusive; the mutually exclusive keyword pairs include, but are not limited to: "valid identity" and "invalid identity", "normal account" and "frozen account", "secure transaction" and "abnormal transaction".

4. The method according to claim 1, characterized in that, Also includes: An audit chain entry is generated for each verification operation. The audit chain entry includes the operation sequence number, timestamp, operation type, operation details, hash value of the previous destination, and hash value of the current entry. The hash value of the current entry is calculated by combining the hash value of the previous destination, the current timestamp, and the current operation content, forming a chain hash structure; the audit chain corresponds to the immutable audit chain module in the T-DS scaling law.

5. The method according to claim 1, characterized in that, The method is applied to financial anti-fraud scenarios, and the second type of proposition includes at least one of the following: user identity validity statement, account status statement, transaction environment security statement, device fingerprint information, geolocation information, and behavioral pattern information.

6. The method according to claim 5, characterized in that, In the aforementioned financial anti-fraud scenario, the evidence weight values ​​are assigned according to the following rules: comparison results from a national-level identity database have a weight value of 90 to 100; analysis results from the internal risk control system of financial institutions have a weight value of 80 to 90. Verification results from trusted third-party service providers have a weighting of 60 to 80; materials submitted by users themselves have a weighting of 20 to 40. Information collected locally from a single device is weighted between 10 and 30.

7. A digital identity verification system based on hierarchical truth verification, characterized in that, include: The proposition layering module is used to receive identity-related propositions to be verified and determine whether they belong to the first type or the second type of proposition. The first type of verification module is used to perform uniqueness verification on the first type of proposition, including a hash calculation unit, a duplicate detection unit, and a permanent locking unit; The hash calculation unit is used to calculate the hash value of the proposition; The duplicate detection unit is used to search the truth database to see if a first type of proposition with the same hash value and in an active state already exists. The permanent locking unit is used to mark the first type of proposition as active and permanently lock it upon its first appearance. The evidence structure module is used to generate and manage evidence structures for the second type of proposition; the evidence structure includes evidence weight value, evidence source identifier, verification method identifier, and reproducibility marker. The contradiction detection module is used to perform semantic contradiction detection between the second type propositions to be added to the database and the second type propositions that have been activated in the truth database. The weight comparison module is used to compare the evidence weight values ​​of two propositions when a semantic contradiction is detected, and decide whether to retain the old proposition or accept the new proposition based on the comparison result. The truth library module is used to store first-type propositions and second-type propositions in a hierarchical manner. The first-type propositions are stored in a permanently locked manner, corresponding to the T-DS anchor layer. The second-type propositions are stored in a manner with attached evidence structures and support switching between active and falsified states, corresponding to the T-DS dynamic evolution layer. The audit chain module is used to generate an immutable audit chain entry for each verification operation, forming an audit log with a chain hash structure. The parent quarantine module is used to pre-screen the propositions before they enter the proposition hierarchical module; the pre-screening includes expansion detection, loop closure detection, discrete transformation detection, minimum marked state mapping detection, and curvature injection detection. The maternal quarantine module corresponds to the maternal quarantine engine in the T-DS scaling law; The clone verification module is used to simulate the operation of the proposition in an isolated environment to test its compatibility with the existing axiomatic system of the system, the compatibility of behavioral constraints, the compatibility of closed-loop capability, and the system expansion pressure; the proposition is allowed to enter the proposition layering module only when all tests pass; the clone verification module corresponds to the clone verification sandbox in the T-DS scaling law; The memory management module includes a temporary memory unit and a long-term memory unit. The temporary memory unit caches recently received propositions in a high-fidelity manner, with limited capacity and no compression, corresponding to the Working Memory in the T-DS scaling law. The long-term memory unit stores fixed propositions in an importance-level manner, corresponding to the Persistent Memory in the T-DS scaling law.

8. The system according to claim 7, characterized in that, In the truth base module, second-type propositions marked as falsified are not deleted from the base, but are retained as historical records and marked with the identifier of the new proposition that refutes the proposition and the timestamp of the refutation, in order to form a complete cognitive evolution chain; the cognitive evolution chain corresponds to the audit chain historical tracing in the T-DS scaling law.

9. The system according to claim 7, characterized in that, The memory management module also includes a T-DS anchor layer, which stores the core parameters of the immutable spatiotemporal scaling law, including spatial cardinality S=10, time cardinality T=12, number of vacancy parts Δ=2, 3 / 7 spatial density, 7 / 12 time period, and 85 / 84 boundary margin.

10. The system according to claim 7, characterized in that, The system also integrates a T-DS spatiotemporal duality verification module, which is used to verify in real time whether the complementarity of spatial density 3 / 7 and time period 7 / 12 during system operation converges to the 85 / 84 boundary margin. If there is a deviation, the system's underlying self-check is triggered.

11. The system according to claim 7, characterized in that, The system also integrates a hook proof verification module, which is used to perform bidirectional hook anchoring on key verification conclusions: the lower hook locks the necessary conditions of the conclusion, the upper hook verifies the sufficient conditions of the axiom, and the middle converges to the theorem; ensuring that the proof does not go astray, does not hang in the air, and is traceable.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 6.

13. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 6.

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