CN116707749A - Multi-level multi-chain user authority dynamic adjustment method based on mixed reputation - Google Patents
Multi-level multi-chain user authority dynamic adjustment method based on mixed reputation Download PDFInfo
- Publication number
- CN116707749A CN116707749A CN202310540670.1A CN202310540670A CN116707749A CN 116707749 A CN116707749 A CN 116707749A CN 202310540670 A CN202310540670 A CN 202310540670A CN 116707749 A CN116707749 A CN 116707749A
- Authority
- CN
- China
- Prior art keywords
- period
- value
- target node
- node
- reputation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
- H04L9/50—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols using hash chains, e.g. blockchains or hash trees
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/10—Network architectures or network communication protocols for network security for controlling access to devices or network resources
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/20—Network architectures or network communication protocols for network security for managing network security; network security policies in general
Landscapes
- Engineering & Computer Science (AREA)
- Computer Security & Cryptography (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Computer Hardware Design (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a multi-level multi-chain user authority dynamic adjustment method based on mixed reputation, which comprises the following steps: acquiring the service type and transaction information of the blockchain transaction participated by the target node in the period t; t is an integer greater than 0; respectively determining a chain attribute quantized value of a block chain in which a target node is positioned in a period t, a node attribute quantized value of the target node in the period t and a behavior quantized value of the target node in the period t according to the service type and the cross-chain transaction information; determining a mixed reputation value of the target node in the period t based on preset weight, a chain attribute quantization value, a node attribute quantization value and a behavior quantization value of the blockchain in which the target node is positioned in the period t and a mixed reputation value of the target node in the period t-1; adjusting the weight value of the target node in the period t+1 based on the mixed reputation value in the period t; the weight value of each node is positively correlated with the mixed reputation value.
Description
Technical Field
The invention belongs to the technical field of blockchains, and particularly relates to a multi-level multi-chain user authority dynamic adjustment method based on mixed reputation.
Background
Blockchain concepts have been proposed and have attracted worldwide attention due to the adoption of decentralised infrastructure and distributed storage technologies. The blockchain technology has now become an important point of attention and research in various countries worldwide, and the development of various industries is being changed.
With the advent of a large number of complex collaborative services, transaction platforms of cross-region block chain systems are continuously emerging. However, node rights management between cross-chain transaction platforms and a large number of blockchain systems remains a challenge. The existing large-scale cross-chain platform generally manages the accessed blockchain in a hierarchical manner, and sets corresponding authority for nodes of the blockchain. The prior art scheme is mainly developed for a non-blockchain system or a single blockchain, realizes the adjustment of user permission and solves the user grading requirement. However, the prior art solutions have the following problems and drawbacks:
1) The problems of security, atomicity and the like of the existing cross-link platform focusing cross-link transaction are mostly ignored in node authority setting and management;
2) Because the cross-chain transaction provides new characteristics, the existing single-blockchain node authority management technology cannot be fully applicable to cross-link point authority setting and management;
3) The node authority management technology proposed by the existing cross-link platform is usually static and unchanged, and as the running time of the platform changes, the cross-link point authority setting and management are stiff.
Disclosure of Invention
In order to solve the problems in the related art, the invention provides a multi-level multi-chain user authority dynamic adjustment method based on mixed reputation. The technical problems to be solved by the invention are realized by the following technical scheme:
the invention provides a multi-level multi-chain user authority dynamic adjustment method based on mixed reputation, which is applied to a hierarchical multi-block chain environment, wherein the hierarchical multi-block chain environment comprises a plurality of block chains and a plurality of different levels, each block chain belongs to one level, and each level comprises at least one block chain, and the method comprises the following steps:
acquiring the business type and cross-chain transaction information of the blockchain transaction participated by the target node in the period t and the mixed credit value of the target node in the period t-1; t is an integer greater than 0;
respectively determining a chain attribute quantization value of a blockchain in which the target node is positioned in a period t, a node attribute quantization value of the target node in the period t and a behavior quantization value of the target node in the period t according to the service type and the transaction information; wherein the chain attribute quantization value of each blockchain is related to the service type and hierarchy; the node attribute quantized value of each node is related to the service type;
determining a mixed reputation value of the target node in a period t based on a preset weight, a chain attribute quantization value of the block chain of the target node in the period t, a node attribute quantization value of the target node in the period t, a behavior quantization value of the target node in the period t and a mixed reputation value of the target node in the period t-1;
adjusting a weight value of the target node in a period t+1 based on the mixed reputation value in the period t; wherein the weight value of each node is positively correlated with the mixed reputation value.
In some embodiments, the determining the hybrid reputation value of the target node in the period t and the hybrid reputation value of the target node in the period t-1 based on the preset weight, the chain attribute quantization value of the blockchain in the period t, the node attribute quantization value of the target node in the period t, the behavior quantization value of the target node in the period t, includes:
determining an initial mixed reputation value of the target node in a period t based on a preset weight, a chain attribute quantization value of the block chain in which the target node is located in the period t, a node attribute quantization value of the target node in the period t and a behavior quantization value of the target node in the period t;
and determining the mixed reputation value of the target node in the period t according to the mixed reputation value in the period t-1 and the initial mixed reputation value in the period t.
In some embodiments, the determining the hybrid reputation value of the target node for period t from the hybrid reputation value for period t-1 and the initial hybrid reputation value for period t comprises:
when the initial mixed reputation value in the period t is smaller than the mixed reputation value in the period t-1, taking the average value of the mixed reputation value in the period t-1 and the initial mixed reputation value in the period t as the mixed reputation value of the target node in the period t;
when the initial mixed reputation value in the period t is larger than or equal to the mixed reputation value in the period t-1, taking the weighted average of the mixed reputation value in the period t-1 and the initial mixed reputation value in the period t as the mixed reputation value of the target node in the period t; wherein the weights used to determine the weighted average are t and t-1.
In some embodiments, the mixed reputation value of the target node over period t is represented by the following formula:
wherein A represents the target node, t represents the period t, t-1 represents the period t-1, R A (t) represents an initial mixed reputation value over the period t,representing within said period t-1Mixed reputation value->Representing the mixed reputation value over the period t.
In some embodiments, the transaction information of the blockchain transaction that the target node participates in during period t includes: the chain attribute quantization value of the blockchain where the transaction party of the target node in each blockchain transaction is located in a period t, the satisfaction degree of the target node to the target node of the transaction party in each blockchain transaction in the period t, the mixed credit value of the transaction party of the target node in each blockchain transaction in the period t in a period t-1, and the transaction amount of the target node in each blockchain transaction in the period t;
the determining, according to the service type and the transaction information, a chain attribute quantization value of the blockchain in which the target node is located in a period t, a node attribute quantization value of the target node in the period t, and a behavior quantization value of the target node in the period t, respectively, includes:
determining a chain attribute quantization value of a block chain in which the target node is positioned in a period t and a node attribute quantization value of the target node in the period t according to the service type;
and determining the behavior quantization value of the target node in the period t according to the chain attribute quantization value of the blockchain in which the transaction party is located, the satisfaction degree, the mixed credit value of the transaction party in the period t-1 and the transaction amount.
In some embodiments, the behavior quantization value of the target node over the period t is expressed by the following formula:
wherein f A,3 (t) represents a behavior quantization value of the target node within the period t, n represents a total number of blockchain transactions the target node participates in within the period t, f A,1,i (t) represents transactions of the target node in the ith blockchain transaction during period tChain attribute quantization value, s, of the blockchain in which the party is located A,i (t) represents satisfaction of the target node with the target node by a transacting party in the ith blockchain transaction during period t,representing a mixed reputation value, a, of a transaction party in an ith blockchain transaction for the target node during period t-1 A,i (t) represents the transaction amount of the target node in the ith blockchain transaction during period t.
In some embodiments, the preset weights include: chain attribute weights, node attribute weights, and behavior weights;
the determining an initial mixed reputation value of the target node in the period t based on a preset weight, a chain attribute quantization value of the block chain of the target node in the period t, a node attribute quantization value of the target node in the period t and a behavior quantization value of the target node in the period t comprises:
and according to the chain attribute weight, the node attribute weight and the behavior weight, carrying out weighted calculation on the chain attribute quantized value of the block chain where the target node is located in the period t, the node attribute quantized value of the target node in the period t and the behavior quantized value of the target node in the period t to obtain the initial mixed reputation value of the target node in the period t.
In some embodiments, the initial mixed reputation value of the target node over period t is represented by the following formula:
R A (t)＝ω 1 (t)·f 1 (t)+ω A,2 (t)·f A,2 (t)+ω A,3 (t)·f A,3 (t)；
wherein R is A (t) represents the initial mixed reputation value, ω, of the target node over period t 1 (t) represents the chain attribute weight, ω A,2 (t) represents the node attribute weight, ω A,3 (t) represents the behavior weight, f 1 (t) represents a chain attribute quantized value, f, of the blockchain in which the target node is located within a period t A,2 (t) TableA node attribute quantized value f of the target node in a period t A,3 (t) represents a quantized value of the behavior of the target node in a period t, ω 1 (t)+ω A,2 (t)+ω A,3 (t)＝1。
In some embodiments, when a blockchain belongs to different levels, the blockchain has different preset chain attribute quantization values, and when a blockchain corresponds to different service types, the preset chain attribute quantization values of the blockchain in the same level are different; when a node corresponds to a different traffic type, the node has a different node attribute quantization value.
In some embodiments, the chain attribute quantization value for each blockchain is the authority value for that blockchain; the node attribute quantization value of each node is the weight value of the node.
The invention has the following beneficial technical effects:
1) The method can comprehensively evaluate the mixed reputation of the node based on the blockchain attribute, the node attribute, the cross-chain transaction information and the node reputation value and further adjust the node authority, so that the dynamic adjustment of the node authority in the hierarchical multi-blockchain environment is realized;
2) Technical support can be provided for construction and operation of a cross-chain platform, so that the cross-chain application platform and the blockchain can be widely applied to various key industries;
3) The block chain link points can be stimulated to adhere to a transaction protocol and acquire high satisfaction evaluation, so that block chain application specific implementation and application demonstration are promoted;
4) The method can provide support for the research of blockchain and cross-chain basic theory and promote the ecological construction of the cross-blockchain.
The present invention will be described in further detail with reference to the accompanying drawings and examples.
Drawings
FIG. 1 is a flowchart of a method for dynamically adjusting multi-level multi-chain user rights based on mixed reputation according to an embodiment of the present invention;
FIG. 2 is a graph of the effects of theoretical variation of mixed reputation values of an exemplary blockchain node provided by embodiments of the present invention.
Detailed Description
The present invention will be described in further detail with reference to specific examples, but embodiments of the present invention are not limited thereto.
In the description of the present invention, the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description of the present invention, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Further, one skilled in the art can engage and combine the different embodiments or examples described in this specification.
Although the invention is described herein in connection with various embodiments, other variations to the disclosed embodiments can be understood and effected by those skilled in the art in practicing the claimed invention, from a study of the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other elements or steps, and the "a" or "an" does not exclude a plurality. A single processor or other unit may fulfill the functions of several items recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.
FIG. 1 is a flow chart of a method for dynamically adjusting multi-level multi-chain user permissions based on hybrid reputation, which is applied to a hierarchical multi-blockchain environment including a plurality of blockchains and a plurality of different levels, each blockchain belonging to a level, each level including at least one blockchain, according to an embodiment of the present invention. As shown in fig. 1, the method comprises the steps of:
s101, acquiring the business type and cross-chain transaction information of the blockchain transaction participated by the target node in a period t and the mixed credit value of the target node in the period t-1; t is an integer greater than 0.
Here, the target node may be any user node (i.e., blockchain node) on any blockchain in a hierarchical multi-blockchain environment.
Here, the period t represents each period, for example, a first period when t=1, and a second period when t is 2.
Here, the traffic type and transaction information of the blockchain transaction that the target node participates in the period t may include: the method comprises the steps of quantifying a chain attribute of a blockchain where a transaction party of a target node in each blockchain transaction is located in a period t, satisfaction of the transaction party of the target node in each blockchain transaction in the period t to the target node, mixing credit values of the transaction party of the target node in each blockchain transaction in the period t in a period t-1, and transaction (gold) amounts of the target node in each blockchain transaction in the period t.
S102, respectively determining a chain attribute quantized value of a block chain where a target node is located in a period t, a node attribute quantized value of the target node in the period t and a behavior quantized value of the target node in the period t according to the service type and the transaction information; wherein the chain attribute quantization value of each blockchain is related to the service type and hierarchy; the node attribute quantization value of each node is related to the traffic type.
When the credit value of any node in the period t is calculated, the credit value can be calculated by the following general credit calculation formula:wherein f i (t) an influence factor quantification value representing the reputation value of the influence node during period t, and f i (t) ∈ (0, 1) (assuming N influencing factors), ω i (t) represents the calculated weight of each influencing factor in the period t, and, < ->The invention adopts the chain attribute, the node attribute and the node action as influencing factors when calculating the reputation value of any node, so that the reputation value of any node can be calculated through the chain attribute quantized value of the block chain where the node is positioned, the node attribute quantized value of the node and the action quantized value of the node when calculating the reputation value of the node.
Here, for each blockchain, when the blockchain belongs to a different hierarchy, the blockchain has a different preset chain attribute quantization value, and when the blockchain corresponds to a different service type, the preset chain attribute quantization value of the blockchain at the same hierarchy is different. For example, each blockchain has a preset chain attribute quantization value when belonging to each hierarchy in each cycle and under each traffic type, and when the blockchain corresponds to a different traffic type in each cycle, the preset chain attribute quantization value of the blockchain at the same hierarchy is different.
Here, for each node, the node has a different node attribute quantization value when the node corresponds to a different traffic type. For example, each node has a preset node attribute quantization value in each period and under each traffic type, and the preset node attribute quantization value of the node is different under different traffic types.
In some embodiments, for each blockchain, the chain attribute quantization value of the blockchain is a privilege value of the blockchain, and each blockchain has a preset privilege value when belonging to each hierarchy in each period and under each service type, and the preset privilege value of the blockchain in the same hierarchy is different when the blockchain corresponds to different service types in each period. For each node, the node attribute quantized value of the node is the authority value of the node, and each node has a preset authority value in the 1 st period and under each service type, and the preset authority values of the node are different in the 1 st period and under different service types.
The step S102 may be implemented by steps S1021 to S1022:
s1021, determining a chain attribute quantized value of the block chain in which the target node is located in a period t and a node attribute quantized value of the target node in the period t according to the service type.
For example, when the preset chain attribute quantization value of each level of each service type is unchanged in all cycles, and the service type of the blockchain transaction in which the target node participates in the cycle t is w, and the blockchain in which the target node is located belongs to the level 1, the preset chain attribute quantization value of the level 1 of the blockchain in which the target node is located in the service type w may be selected from the preset chain attribute quantization values of each level of the blockchain in which the target node is located in various service types, as the chain attribute quantization value of the blockchain in the cycle t in which the target node is located.
For example, when each node has a preset node attribute quantization value in all periods and under each service type, and the preset node attribute quantization value of the node is different under different service types, and the service type of the blockchain transaction participated by the target node in period t is w, the preset node attribute quantization value of the target node under the service type w can be selected from the preset node attribute quantization values of the target node under various service types as the node attribute quantization value of the target node in period t.
For another example, when each node has a preset weight value only in the 1 st period and under each service type, and the weight value in each period is adjusted and updated by adopting the method shown in fig. 1, and the service type of the blockchain transaction participated by the target node in the period t is w, the weight value of the target node in the period t and under the service type w can be used as the node attribute quantization value of the target node in the period t; when the preset authority value of the target node under the service type w is not regulated and updated before the period t, the authority value of the target node under the service type w in the period t is the preset authority value of the target node under the service type w; and when the preset authority value of the target node under the service type w is adjusted and updated before the period t, the authority value of the target node under the service type w in the period t is the authority value obtained by the last adjustment and update of the authority value of the target node under the service type w before the period t.
S1022, determining the behavior quantization value of the target node in the period t according to the chain attribute quantization value of the blockchain where the target node in the period t is located in each blockchain transaction, the satisfaction degree of the target node in the period t to the target node by the transaction party in each blockchain transaction, the mixed credit value of the target node in the period t in each blockchain transaction by the transaction party in the period t-1 and the transaction (gold) amount of the target node in each blockchain transaction in the period t.
Specifically, the behavior quantization value of the target node in the period t is expressed by the following formula:
wherein f A,3 (t) represents a behavior quantization value of the target node in the period t, n represents a total number of blockchain transactions the target node participates in the period t, f A,1,i (t) represents the chain attribute quantization value, s, of the blockchain where the target node is located in the ith blockchain transaction during period t A,i (t) represents the satisfaction of the target node by the transaction party in the ith blockchain transaction of the target node in period t, +.>Representing a mixed reputation value, a, of a transaction party in an ith blockchain transaction for a target node in period t for period t-1 A,i (t) represents the weekThe amount of transactions in the ith blockchain transaction by the target node during period t.
S103, determining a mixed reputation value of the target node in the period t based on preset weights, a chain attribute quantized value of the blockchain where the target node is located in the period t, a node attribute quantized value of the target node in the period t, a behavior quantized value of the target node in the period t and a mixed reputation value of the target node in the period t-1.
In some embodiments, S103 may be implemented by S1031 to S1032:
s1031, calculating an initial mixed reputation value of the target node in the period t based on the preset weight, the chain attribute quantization value of the block chain of the target node in the period t, the node attribute quantization value of the target node in the period t, the behavior quantization value of the target node in the period t and the mixed reputation value of the target node in the period t-1.
Here, the preset weights include: chain attribute weights, node attribute weights, and behavior weights; based on this, the initial mixed reputation value of the target node over period t is expressed by the following formula:
R A (t)＝ω 1 (t)·f 1 (t)+ω A,2 (t)·f A,2 (t)+ω A,3 (t)·f A,3 (t); wherein R is A (t) represents the initial mixed reputation value, ω, of the target node over period t 1 (t) represents the chain attribute weight, ω A,2 (t) represents node attribute weight, ω A,3 (t) represents the behavior weight, f 1 (t) represents the chain attribute quantization value, f, of the blockchain in which the target node is located within the period t A,2 (t) represents the node attribute quantization value of the target node in the period t, f A,3 (t) represents the quantized value of the behavior of the target node in the period t, ω 1 (t)+ω A,2 (t)+ω A,3 (t)＝1。
S1032, determining the mixed reputation value of the target node in the period t according to the mixed reputation value in the period t-1 and the initial mixed reputation value in the period t.
Here, when the initial mixed reputation value in the period t is smaller than the mixed reputation value in the period t-1, taking the average value of the mixed reputation value in the period t-1 and the initial mixed reputation value in the period t as the mixed reputation value of the target node in the period t; when the initial mixed reputation value in the period t is greater than or equal to the mixed reputation value in the period t-1, taking the weighted average of the mixed reputation value in the period t-1 and the initial mixed reputation value in the period t as the mixed reputation value of the target node in the period t; wherein the weights used to determine the weighted average are t and t-1. That is, the mixed reputation value of the target node over period t may be expressed by the following formula:
wherein A represents a target node, t represents a period t, t-1 represents a period t-1, R A (t) represents an initial hybrid reputation value over period t,representing the mixed reputation value over period t-1.
The reputation value variation effect shown in fig. 2 can be achieved by the method for determining the mixed reputation value of the target node in the period t in step S1032. The inflection point of the broken line in FIG. 2 isAs can be seen from fig. 2, by the method for determining the hybrid reputation value of the target node in the period t, the hybrid reputation value of the target node is difficult to increase, but is easy to decrease, so that the target node can be stimulated to follow the transaction protocol and obtain high satisfaction evaluation so as to improve the hybrid reputation value of the target node.
S104, adjusting the weight value of the target node in the period t+1 based on the mixed credit value in the period t; wherein the weight value of each node is positively correlated with the mixed reputation value.
Here, when the mixed reputation value of the target node in the period t is high, the weight value of the target node in the period t+1 may be increased, whereas when the mixed reputation value of the target node in the period t is low, the weight value of the target node in the period t+1 may be decreased.
Specifically, the authority value of the target node in the period t can be obtained, and the authority value of the target node in the period t is adjusted according to the obtained mixed reputation value of the target node in the period t to obtain the authority value of the target node in the period t+1, so that the authority value of the target node in the period t+1 is increased or decreased, and the specific authority adjustment mode is not limited in this embodiment.
The foregoing is a further detailed description of the invention in connection with the preferred embodiments, and it is not intended that the invention be limited to the specific embodiments described. It will be apparent to those skilled in the art that several simple deductions or substitutions may be made without departing from the spirit of the invention, and these should be considered to be within the scope of the invention.
Claims (10)
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310540670.1A CN116707749A (en) | 2023-05-12 | 2023-05-12 | Multi-level multi-chain user authority dynamic adjustment method based on mixed reputation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310540670.1A CN116707749A (en) | 2023-05-12 | 2023-05-12 | Multi-level multi-chain user authority dynamic adjustment method based on mixed reputation |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116707749A true CN116707749A (en) | 2023-09-05 |
Family
ID=87833033
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310540670.1A Pending CN116707749A (en) | 2023-05-12 | 2023-05-12 | Multi-level multi-chain user authority dynamic adjustment method based on mixed reputation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116707749A (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109767199A (en) * | 2018-12-10 | 2019-05-17 | 西安电子科技大学 | PBFT common recognition system and method, block chain data processing system based on prestige |
| US20190340266A1 (en) * | 2018-05-01 | 2019-11-07 | International Business Machines Corporation | Blockchain implementing cross-chain transactions |
| CN113256149A (en) * | 2021-06-11 | 2021-08-13 | 武汉龙津科技有限公司 | Block chain node reputation adjusting method and device, electronic equipment and storage medium |
| CN114663091A (en) * | 2022-03-25 | 2022-06-24 | 上海电力大学 | Electricity trading method based on multi-chain blockchain architecture |
-
2023
- 2023-05-12 CN CN202310540670.1A patent/CN116707749A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20190340266A1 (en) * | 2018-05-01 | 2019-11-07 | International Business Machines Corporation | Blockchain implementing cross-chain transactions |
| CN109767199A (en) * | 2018-12-10 | 2019-05-17 | 西安电子科技大学 | PBFT common recognition system and method, block chain data processing system based on prestige |
| CN113256149A (en) * | 2021-06-11 | 2021-08-13 | 武汉龙津科技有限公司 | Block chain node reputation adjusting method and device, electronic equipment and storage medium |
| CN114663091A (en) * | 2022-03-25 | 2022-06-24 | 上海电力大学 | Electricity trading method based on multi-chain blockchain architecture |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Xie et al. | Research on Trust Model in Container-Based Cloud Service. | |
| CN107562531A (en) | A kind of data balancing method and device | |
| CN115801896B (en) | Computing power network node allocation method, device, electronic device and storage medium | |
| CN101923615B (en) | Grey fuzzy comprehensive evaluation-based trust quantization method | |
| CN113377866B (en) | A load balancing method and device for virtualized database proxy service | |
| CN106959894A (en) | Resource allocation methods and device | |
| AU2019201625A1 (en) | Elastic storage volume type selection and optimization engine for public cloud environments | |
| CN111882198A (en) | A project performance evaluation method and system | |
| CN108628662A (en) | Mix the resource elastic telescopic method based on load estimation under cloud environment | |
| CN115714817A (en) | Dynamic feedback weighted cloud storage resource scheduling method, device and equipment | |
| CN112668832A (en) | Risk quantitative evaluation method and device based on index management system and electronic equipment | |
| CN115061815A (en) | Optimal scheduling decision method and system based on AHP | |
| CN118158092A (en) | A computing power network scheduling method, device and electronic equipment | |
| CN117472505A (en) | A cloud platform container scheduling method, device, electronic equipment and storage medium | |
| CN111475837A (en) | Network big data privacy protection method | |
| Thomas et al. | Unemployment insurance under moral hazard and limited commitment: public versus private provision | |
| CN116707749A (en) | Multi-level multi-chain user authority dynamic adjustment method based on mixed reputation | |
| Zheng et al. | An RBF neural network–based dynamic virtual network embedding algorithm | |
| CN114661463A (en) | BP neural network-based system resource prediction method and system | |
| CN118690410A (en) | Privacy protection method and system for multi-chain distributed computing environment based on blockchain | |
| Deng et al. | A novel semifragile consensus algorithm based on credit space for consortium blockchain | |
| CN117421197B (en) | A capacity resource calculation method, device and medium in a trusted computing environment | |
| CN108809699B (en) | A method for realizing repeated mapping of large-scale virtual network nodes | |
| CN114640476B (en) | Method, system and medium for evaluating credit of certificate issuer of decentralized identity certificate | |
| CN117764709A (en) | A method and device for determining a user's credit status |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |