CN-121258685-B - Digital asset processing method based on block chain

CN121258685BCN 121258685 BCN121258685 BCN 121258685BCN-121258685-B

Abstract

The invention discloses a digital asset processing method based on a blockchain, which relates to the technical field of blockchains and comprises the following steps of S0, deploying event monitoring acquisition modules at signal receiving and transmitting ports and observation interfaces of node clusters on the chain, deploying P2P communication monitoring acquisition modules at the middle section of nodes close to a data access side and corresponding to the data access side and the data access level, deploying fund flowing pulse acquisition modules on a settlement channel, S1, enabling each acquisition module to work and acquire asset risk signals, outputting acquisition results according to initial acquisition frequency and sampling granularity, judging whether asset risk phenomenon occurs or not through a corresponding analysis module, and S2, when a certain acquisition module detects that a certain type of risk occurs, enabling other acquisition modules closest to the topological position of the current acquisition module to adjust acquisition frequency and sampling granularity.

Inventors

SUN JUNFENG
YIN LEI
LIU MINGMING

Assignees

厦门川佰数字科技有限公司

Dates

Publication Date: 20260512
Application Date: 20251118

Claims (7)

1. A digital asset processing method based on a blockchain is characterized by comprising the following steps: S0, deploying an event monitoring acquisition module at a signal receiving and transmitting port and an observation interface of the on-chain node cluster, deploying a P2P communication monitoring acquisition module at a node middle section which is close to a data access side and corresponds to the data access side and the data access side level, deploying a fund flowing pulse acquisition module on a settlement channel, deploying a metadata consistency acquisition module at an internal data layer of the on-chain node cluster; s1, each acquisition module works and acquires asset risk signals, each acquisition module outputs an acquisition result according to initial acquisition frequency and sampling granularity, and whether asset risk phenomena occur or not is judged through a corresponding analysis module; S2, when a certain acquisition module detects that a certain form of risk occurs, other acquisition modules of the types closest to the topological position of the current acquisition module are enabled to adjust the acquisition frequency and the sampling granularity, so that the acquisition module needing to be adjusted and the current acquisition module are unified in the acquisition frequency and the sampling granularity; S3, dynamically adjusting the acquisition frequency and the sampling granularity of the acquisition module to be adjusted according to whether the same asset risk signal is continuously acquired or not along with the time continuation; S4, when the acquisition frequency and the sampling granularity of each acquisition module are not uniform, processing the acquired data by using a data alignment processing module, and carrying out normalization processing on the acquisition frequency and the sampling granularity; s5, combining metadata consistency analysis results read by metadata solution on a chain to judge the form of asset risk; In the step S3, the dynamic adjustment specifically includes: S3-1, order 1 The acquisition modules maintain the acquisition frequency And sample granularity Continuous and continuous If in the time period of (a) Time period of the first time When the acquisition modules acquire the asset risk signals in the same form again, observing the first Whether the same type of asset risk signals are acquired by the acquisition modules at the same time or not, if so, the occurrence probability of the type of asset risk signals is improved, and the adjusted probability is that Wherein Is the first The first and second acquisition modules are used as auxiliary judgment modes The statistical gain factors brought by the asset risk signals in the same form are acquired by the acquisition modules, if the first If the asset risk signals in the same form are not collected by the collection modules at the same time ; S3-2, if in Time period of the first time When the acquisition modules do not acquire the asset risk signals in the same form, the first step is that The acquisition frequency and the sampling granularity of each acquisition module are determined by And To its initial value And Gradually recovering to make the distance at the moment The time elapsed after the end of the time period is Acquisition frequency at this time And sample granularity The calculation formulas of (a) are respectively that when In the time-course of which the first and second contact surfaces, When (when) In the time-course of which the first and second contact surfaces, When (when) In the time-course of which the first and second contact surfaces, When (when) In the time-course of which the first and second contact surfaces, Wherein 、 Is a time scaling factor.
2. The method for processing the digital asset based on the blockchain as recited in claim 1, wherein in S0, determining which collection mode each risk form corresponds to specifically is: s0-1, transaction pulse type risks of short-time high-frequency calling and abnormal repeated transaction adopt contract event monitoring as a leading judgment mode, and P2P communication monitoring and fund flow pulse acquisition as an auxiliary judgment mode; S0-2, instantaneous gold inlet and outlet concentration, abnormal arbitrage flow and short-period large-amount transfer mobility peak risk, adopting fund flow pulse collection as a leading judgment mode, and contract event monitoring as an auxiliary judgment mode; S0-3, broadcasting storm and spreading diffusion type risks of aggressive diffusion, wherein P2P communication monitoring is adopted as a leading judgment mode, and fund flow pulse acquisition and contract event monitoring are adopted as auxiliary judgment modes; S0-4, predicting machine deviation and under-chain dependency type consistency risk of content hash drift, wherein metadata consistency collection is adopted as a leading judgment mode, and contract event monitoring is adopted as an auxiliary judgment mode.
3. The method for processing digital asset based on blockchain as in claim 2, wherein in S2, unifying the acquisition frequency and the sampling granularity is as follows: S2-1, each acquisition module acquiescently acquires a risk form corresponding to the dominant judgment mode, and the acquiescently acquires the risk form with the acquiescent acquisition frequency And sample granularity Output of the acquisition result is carried out, wherein For the number of acquisition modules, the sampling granularity determines whether the system acquires data once per block, data once per transaction or log event once per transaction; s2-2, order 1 The asset risk signals are collected by the collection modules, and the default collection frequency is that Default sampling granularity is The initial probability of occurrence of this form of asset risk signal is At this time, the first step is needed The acquisition frequency and the sampling granularity of each acquisition module are adjusted, and the default acquisition frequency and the sampling granularity before adjustment are respectively And So that it is adjusted to the acquisition frequency The granularity of the adjusted sampling 。
4. The method for processing digital assets based on blockchain according to claim 3, wherein in S4, normalization processing of acquisition frequency and sampling granularity is specifically: S4-1, at first Will be the first at the end of the time period And (b) The first sampling time of each acquisition module is aligned, at the moment, the two acquisition modules sample simultaneously, and only the sampling of the next sampling meets the requirement And The data is collected at the moment of the least common multiple, and other data are not collected; s4-2, will be And (b) The maximum value and the minimum value of the acquired data of each acquisition module are mapped to And eliminating the dimension difference of sampling granularity among different acquisition modules.
5. The method for processing a blockchain-based digital asset according to claim 4, wherein in S5, the determination of the form of asset risk is specifically performed by making each acquisition module output a variety of consistency deviation indexes of the metadata consistency acquisition module respectively before each acquisition of asset risk phenomenon Wherein For the number of consistency deviation indicators involved in asset risk, when some form of asset risk phenomenon is detected, if such form of risk would lead to Changes and Actually collect Producing consistent bias changes, probability of such asset risk forms occurring Wherein For consistency deviation influencing coefficient, if not collected Producing a consistent variation Binding to S3-1 pair The final probability of (2) is calculated when In the time-course of which the first and second contact surfaces, For the probability judgment threshold, it is judged that the risk form is established, and early warning is needed.
6. The method for processing the digital asset based on the blockchain is characterized in that a system adopted by the method comprises a signal acquisition module, a signal processing module and a risk judging module, wherein the signal acquisition module is used for acquiring contract event streams, P2P transmission indexes and high-frequency gold-in and gold-out risk signals, the multi-dimensional acquisition is carried out by combining consistency deviation indexes in metadata, the signal processing module is used for carrying out unified time reference and intensity normalization processing on acquisition frequency and sampling granularity, carrying out dynamic adjustment on two output parameter characteristics according to a subsequent acquisition result and carrying out multi-source data fusion processing, and the risk judging module is used for comprehensively judging asset risk forms according to processed data.
7. The blockchain-based digital asset processing method of claim 6, wherein the signal acquisition module comprises a contract event monitoring acquisition module, a P2P communication monitoring acquisition module, a fund flow pulse acquisition module, a metadata consistency acquisition module, a contract event flow analysis module, a P2P transmission index analysis module, a high-frequency gold in-out analysis module and a metadata consistency analysis module, wherein the contract event monitoring acquisition module, the P2P communication monitoring acquisition module and the fund flow pulse acquisition module are respectively used for acquiring contract event flows, P2P transmission indexes and high-frequency gold in-out risk signals, the metadata consistency acquisition module is used for acquiring metadata consistency detected in metadata on-chain, and the contract event flow analysis module, the P2P transmission index analysis module and the high-frequency gold in-out analysis module are respectively used for analyzing risk signals, and the metadata consistency analysis module is used for analyzing various metadata consistency; the signal processing module comprises an acquisition frequency adjustment module, a sampling granularity adjustment module, a data alignment processing module, a risk form corresponding module and a timing module, wherein the timing module is used for counting the duration time after a certain risk form appears, the acquisition frequency adjustment module and the sampling granularity adjustment module are respectively used for adjusting the acquisition frequency and the sampling granularity of each acquisition module, and the data alignment processing module is used for carrying out normalization processing on the acquisition frequency and the sampling granularity of each acquisition module; the risk judging module comprises a metadata consistency judging module and a risk form judging module, wherein the metadata consistency judging module is used for analyzing metadata consistency changes detected by metadata on a chain to assist in judging the risk form, and the risk form judging module is used for judging the risk form with the highest probability.

Description

Digital asset processing method based on block chain Technical Field The invention relates to the technical field of blockchains, in particular to a digital asset processing method based on a blockchain. Background With the rapid growth of digital asset size, blockchain systems are assuming more and more value recording and status verification functions in the links of clearing, settlement, cross-chain transmission, etc. However, in the prior art, abnormal fluctuation or risk status of digital assets usually depends on a single-dimensional monitoring manner, such as statistics only through transaction frequency or contract call volume, and lack of synchronous correlation analysis of multi-source on-link and off-link information, resulting in insufficient comprehensiveness and real-time performance of risk detection. At present, the mainstream asset monitoring platform generally adopts a mode of fixed sampling frequency and uniform sampling granularity to collect data, and is delayed in response to complex risk phenomena such as sudden traffic pulses, abnormal arbitrage flows, prophetic machine deviation and the like. Because different risk events have obvious differences in time scale and data density, short-time high-frequency transaction anomalies are easily missed if the low-frequency acquisition is adopted, and calculation resource waste and on-chain data redundancy are caused if the high-frequency acquisition is adopted. In addition, the existing system lacks a cooperative adjustment mechanism between acquisition modules, and the acquisition strategies of other associated modules cannot be dynamically adjusted according to the sudden abnormality of a certain data source, so that uniform time reference and strength scale are difficult to form between multi-source information. Therefore, it is necessary to devise a blockchain-based digital asset processing method for fine identification. Disclosure of Invention The present invention is directed to a digital asset processing method based on blockchain to solve the above-mentioned problems set forth in the background art. In order to solve the technical problems, the invention provides a digital asset processing method based on a blockchain, which comprises the following steps: S0, deploying an event monitoring acquisition module at a signal receiving and transmitting port and an observation interface of the on-chain node cluster, deploying a P2P communication monitoring acquisition module at a node middle section which is close to a data access side and corresponds to the data access side and the data access side level, deploying a fund flowing pulse acquisition module on a settlement channel, deploying a metadata consistency acquisition module at an internal data layer of the on-chain node cluster; s1, each acquisition module works and acquires asset risk signals, each acquisition module outputs an acquisition result according to initial acquisition frequency and sampling granularity, and whether asset risk phenomena occur or not is judged through a corresponding analysis module; S2, when a certain acquisition module detects that a certain form of risk occurs, other acquisition modules of the types closest to the topological position of the current acquisition module are enabled to adjust the acquisition frequency and the sampling granularity, so that the acquisition module needing to be adjusted and the current acquisition module are unified in the acquisition frequency and the sampling granularity; S3, dynamically adjusting the acquisition frequency and the sampling granularity of the acquisition module to be adjusted according to whether the same asset risk signal is continuously acquired or not along with the time continuation; S4, when the acquisition frequency and the sampling granularity of each acquisition module are not uniform, processing the acquired data by using a data alignment processing module, and carrying out normalization processing on the acquisition frequency and the sampling granularity; s5, combining metadata consistency analysis results read by the metadata solution on the chain to judge the form of the asset risk. According to the above technical solution, in S0, it is clear which collection mode each risk form corresponds to specifically: s0-1, transaction pulse type risks of short-time high-frequency calling and abnormal repeated transaction adopt contract event monitoring as a leading judgment mode, and P2P communication monitoring and fund flow pulse acquisition as an auxiliary judgment mode; S0-2, instantaneous gold inlet and outlet concentration, abnormal arbitrage flow and short-period large-amount transfer mobility peak risk, adopting fund flow pulse collection as a leading judgment mode, and contract event monitoring as an auxiliary judgment mode; S0-3, broadcasting storm and spreading diffusion type risks of aggressive diffusion, wherein P2P communication monitoring is adopted as a leading judgment mode, and fund flow p