CN117436086A - Knowledge graph-based software supply chain security analysis method and system - Google Patents
Knowledge graph-based software supply chain security analysis method and system Download PDFInfo
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- G—PHYSICS
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- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/50—Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
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Abstract
The invention discloses a software supply chain safety analysis method and system based on a knowledge graph, which belong to the technical field of software supply chain safety, wherein the method comprises the following steps: obtaining vulnerability knowledge, component dependency relationship and mapping knowledge between a vulnerability database and a component database; constructing a vulnerability knowledge graph taking a vulnerability as an entity and a component knowledge graph taking a component as an entity, and integrating the vulnerability knowledge graph and the component knowledge graph into a supply chain knowledge graph by utilizing the mapping knowledge; obtaining an inference result of the supply chain knowledge graph through a query statement, wherein the inference result comprises vulnerability information, component information influenced by the vulnerability and a vulnerability propagation path; traversing all vulnerability propagation paths, and filtering noise dependency relationships and redundancy dependency relationships. The invention can construct an automatic tens of millions of level software supply chain knowledge graph, thereby achieving the purposes of improving the accuracy of the software supply chain safety analysis result based on the knowledge graph and maintaining the supply chain safety.
Description
Technical Field
The invention belongs to the technical field of software supply chain safety, and particularly relates to a knowledge graph-based software supply chain safety analysis method and system.
Background
In recent years, as the multiplexing of open source software is increasing, the event of attack to the software supply chain is also increasing frequently, and the security analysis and maintenance of the software supply chain is receiving more and more attention from students. Because of the large and complex loopholes of open sources and component dependency information, most current researches use dependency trees to represent the dependency relationship among components, and it is difficult to construct a complete software supply chain. The existing safety analysis data about the supply chain is limited, and the safety problem of the software supply chain cannot be comprehensively analyzed.
Since the graph is most suitable for representing relationships, the adoption of graph-based knowledge representation and storage has significant advantages in addressing knowledge utilization. For this reason, some researchers begin building vulnerability knowledge maps to support vulnerability-related applications. In the aspect of vulnerability propagation and detection, the knowledge graph can assist a developer in detecting whether software is threatened by vulnerabilities from a vulnerability library or not during software development and maintenance, so that the software security is improved. However, the vulnerability knowledge graph is limited to vulnerability knowledge and cannot provide data for software supply chain security analysis. And most of the current supply chain safety analysis related works based on the knowledge graph directly use the reasoning result of the knowledge graph for analysis, and the redundancy of information in the reasoning result is not considered and filtered. Thus, the result of the supply chain security analysis is not accurate enough, and great inconvenience is brought to the repair of the loopholes in the supply chain.
Disclosure of Invention
Aiming at the defects and improvement demands of the prior art, the invention provides a software supply chain safety analysis method and system based on a knowledge graph, and aims to solve the technical problem that the safety analysis result of the existing software supply chain based on the knowledge graph is inaccurate.
In order to achieve the above object, in a first aspect, the present invention provides a software supply chain security analysis method based on a knowledge graph, comprising the steps of:
s1, obtaining vulnerability knowledge, component dependency relationship and mapping knowledge between a vulnerability database and a component database;
s2, constructing a vulnerability knowledge graph taking a vulnerability as an entity and a component knowledge graph taking a component as an entity, and integrating the vulnerability knowledge graph and the component knowledge graph into a supply chain knowledge graph by utilizing the mapping knowledge;
s3, obtaining an inference result of the supply chain knowledge graph through a query statement, wherein the inference result comprises vulnerability information, component information influenced by the vulnerability and a vulnerability propagation path;
s4, traversing all vulnerability propagation paths, and filtering noise dependency and redundancy dependency.
Further, the step S4 includes: traversing all the vulnerability propagation paths, filtering out components which are Test and all the components behind the components in the vulnerability propagation paths, and replacing a plurality of continuous components which belong to the same group in the same vulnerability propagation path with the components which are closest to the components and are easily affected by the vulnerability.
Further, after the step S4, the method further includes: detecting whether a hysteresis library exists in the processed vulnerability propagation path, wherein the hysteresis library is a component library with no updated version in expected release time, and reminding a user if the hysteresis library exists; the expected release time T is expressed as:
T＝T last +ΔT
wherein T is last Representing the time at which the last version of the component was published; Δt represents the expected distribution time interval; t is t i Representing the time interval between the release of the components of the ith version and the i-1 th version; alpha is a smoothing parameter representing the speed at which the effect of the previous time interval is reduced, and 0<α<1。
Further, the step S1 includes:
s101, crawling data texts from an NVD vulnerability database, a Maven Central component library and a VERACODE vulnerability library by using a crawler technology;
s102, entity extraction, relation extraction and attribute extraction are carried out on the text obtained in the S101 so as to obtain vulnerability knowledge, component dependency relationship and mapping knowledge between a vulnerability database and a component database.
Further, the step S2 includes:
s201, traversing all vulnerability knowledge, creating relations among vulnerability entity nodes, sub-entity nodes and different nodes, and adding the relations to a knowledge graph so as to construct the vulnerability knowledge graph;
s202, traversing all component knowledge, creating component entity nodes and group nodes, building dependency relationships among components and dependency relationships among groups and components, and adding the dependency relationships into a knowledge graph to construct a component knowledge graph;
s203, traversing all mapping knowledge, and establishing an association relationship between the vulnerability knowledge graph and related nodes in the component knowledge graph, thereby constructing a supply chain knowledge graph.
Further, the step S3 includes:
determining a component or a vulnerability to be analyzed in a supply chain, acquiring an entity corresponding to the component or the vulnerability in a supply chain knowledge graph, searching all propagation paths taking the entity as a starting point, and extracting all information on the propagation paths as a reasoning result.
In a second aspect, the present invention provides a knowledge-graph-based software supply chain security analysis system, comprising a computer-readable storage medium and a processor;
the computer-readable storage medium is for storing executable instructions;
the processor is configured to read executable instructions stored in the computer readable storage medium, and execute the software supply chain security analysis method based on the knowledge graph according to the first aspect.
In general, through the above technical solutions conceived by the present invention, the following beneficial effects can be obtained:
according to the method, the vulnerability knowledge graph and the component knowledge graph are constructed by acquiring vulnerability knowledge, component dependency and mapping knowledge between a vulnerability database and a component database, and are integrated into a supply chain knowledge graph; acquiring an inference result of the supply chain knowledge graph through a query statement to obtain a propagation path of the vulnerability in a supply chain; and then filtering the noise dependency relationship and the redundancy dependency relationship, and predicting a hysteresis library to obtain the component information with safety risk. Therefore, more accurate vulnerability propagation influence range information can be obtained, and practical help is brought to the safety analysis and maintenance of the supply chain.
Drawings
FIG. 1 is a schematic flow chart of a software supply chain security analysis method based on a knowledge graph according to an embodiment of the present invention;
FIG. 2 is a diagram of a framework for constructing a vulnerability knowledge graph in the present invention;
FIG. 3 is a diagram of a knowledge graph framework of a building element of the present invention;
FIG. 4 is a diagram of a framework for constructing a supply chain knowledge graph in accordance with the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention. In addition, the technical features of the embodiments of the present invention described below may be combined with each other as long as they do not collide with each other.
In the present invention, the terms "first," "second," and the like in the description and in the drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order.
As shown in fig. 1, the invention provides a software supply chain security analysis method based on a knowledge graph, which comprises the following steps:
s1, obtaining vulnerability knowledge, component dependency relationship and mapping knowledge between a vulnerability database and a component database.
The method comprises the steps of inputting NVD, maven Central and mapping library data links, firstly, crawling data texts by using an intelligent crawler technology, wherein mapping information between a vulnerability library and a component library solves the problem of non-uniform naming of two database software, and can be used as mapping data for fusing a vulnerability knowledge graph and a component knowledge graph. And the automatic crawler technology is adopted to collect data on a large scale and design automatic updating, so that data support is provided for constructing a software supply chain knowledge graph.
And then analyzing the text to perform entity extraction, relation extraction and attribute extraction. The step is output to store knowledge required for constructing a supply chain knowledge graph, namely vulnerability knowledge, component dependency relationship and mapping knowledge between a vulnerability database and a component database.
S2, constructing a vulnerability knowledge graph taking the vulnerability as an entity and a component knowledge graph taking the component as an entity, and integrating the vulnerability knowledge graph and the component knowledge graph into a supply chain knowledge graph by utilizing the mapping knowledge.
The step of inputting knowledge required for constructing a supply chain knowledge graph, firstly traversing all vulnerability knowledge, creating relations among vulnerability entity nodes, sub-entity nodes and different nodes, and adding the relations to the knowledge graph so as to construct the vulnerability knowledge graph, as shown in fig. 2; then traversing all component knowledge, creating component entity nodes and group nodes, establishing dependency relationships among components and dependency relationships among groups and components, and adding the dependency relationships into a knowledge graph to construct a component knowledge graph, wherein the component knowledge graph is shown in FIG. 3; and finally traversing all mapping knowledge, and establishing the association relation between the vulnerability knowledge graph and the related nodes in the component knowledge graph, thereby constructing a supply chain knowledge graph, as shown in fig. 4. The output of this step is a supply chain knowledge graph.
S3, obtaining an inference result of the supply chain knowledge graph through a query statement, wherein the inference result comprises vulnerability information, component information influenced by the vulnerability and a vulnerability propagation path.
The step is input as a supply chain knowledge graph, and the functions of inquiring nodes and relations are realized by defining and writing inquiry sentences. By means of the reasoning function of the knowledge graph, information such as loopholes, component dependence, loophole propagation paths and the like can be inquired in the knowledge graph. The supply chain knowledge graph reasoning result acquisition method provides a more flexible and deep analysis and understanding mode of the supply chain data, and provides more comprehensive data for the safety analysis of the supply chain. The output of the step is a reasoning result, namely the vulnerability propagation range.
Specifically, a component or a vulnerability to be analyzed in a supply chain is determined, an entity corresponding to the component or the vulnerability is obtained in a supply chain knowledge graph, all propagation paths taking the entity as a starting point are searched, and all information on the propagation paths is extracted as a reasoning result.
S4, traversing all vulnerability propagation paths, and filtering noise dependency and redundancy dependency.
The input of the step is a vulnerability propagation range, all vulnerability propagation paths are traversed firstly, components which are Test in the vulnerability propagation paths and all the components behind the components are filtered, the components cannot be affected by the vulnerability in the vulnerability propagation paths, and the components belong to noise dependency relations. Then filtering the internal dependence existing in the vulnerability propagation path, namely, the situation that a plurality of continuous components in the same vulnerability propagation path have dependency relationships with each other and belong to the same group, wherein the internal dependence belongs to a redundant dependency relationship; and replacing a group of continuous internal dependencies in the vulnerability propagation path with the component closest to the components susceptible to the vulnerability, so that initiative of a developer for vulnerability repair is improved.
The final treated vulnerability propagation path may also have libraries that are not updated continuously, and even if the libraries are found to be affected by vulnerabilities, the repair vulnerabilities are not updated immediately, which makes maintenance of supply chain security difficult. It is therefore necessary to predict whether a hysteresis library exists in the vulnerability propagation path after processing, so as to obtain component information with security risk.
If the component has no updated version within the expected release time, the component is judged to be a hysteresis library, and the attention is improved. Through further processing, more accurate data can be provided for the software supply chain safety analysis based on the knowledge graph.
The expected release time T is expressed as:
T＝T last +ΔT
wherein T is last Representing the time at which the last version of the component was published; Δt represents the expected distribution time interval; t is t i Representing the time interval between the release of the components of the ith version and the i-1 th version; alpha is a smoothing parameter representing the speed at which the effect of the previous time interval is reduced, and 0<α<1。
The expected release time T can also be expressed in terms of an error threshold as: t=t last +2ΔT。
It will be readily appreciated by those skilled in the art that the foregoing description is merely a preferred embodiment of the invention and is not intended to limit the invention, but any modifications, equivalents, improvements or alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (7)
1. The software supply chain safety analysis method based on the knowledge graph is characterized by comprising the following steps of:
s1, obtaining vulnerability knowledge, component dependency relationship and mapping knowledge between a vulnerability database and a component database;
s2, constructing a vulnerability knowledge graph taking a vulnerability as an entity and a component knowledge graph taking a component as an entity, and integrating the vulnerability knowledge graph and the component knowledge graph into a supply chain knowledge graph by utilizing the mapping knowledge;
s3, obtaining an inference result of the supply chain knowledge graph through a query statement, wherein the inference result comprises vulnerability information, component information influenced by the vulnerability and a vulnerability propagation path;
s4, traversing all vulnerability propagation paths, and filtering noise dependency and redundancy dependency.
2. The knowledge-based software supply chain security analysis method according to claim 1, wherein the step S4 comprises: traversing all the vulnerability propagation paths, filtering out components which are Test and all the components behind the components in the vulnerability propagation paths, and replacing a plurality of continuous components which belong to the same group in the same vulnerability propagation path with the components which are closest to the components and are easily affected by the vulnerability.
3. The method for analyzing the security of a software supply chain based on a knowledge graph according to claim 1 or 2, wherein after the step S4, further comprises: detecting whether a hysteresis library exists in the processed vulnerability propagation path, wherein the hysteresis library is a component library with no updated version in expected release time, and reminding a user if the hysteresis library exists; the expected release time T is expressed as:
T＝T last +ΔT
wherein T is last Representing the time at which the last version of the component was published; Δt represents the expected distribution time interval; t is t i Representing the time interval between the release of the components of the ith version and the i-1 th version; alpha is a smoothing parameter representing the speed at which the effect of the previous time interval is reduced, and 0<α<1。
4. The knowledge-based software supply chain security analysis method according to claim 1, wherein the step S1 comprises:
s101, crawling data texts from an NVD vulnerability database, a Maven Central component library and a VERACODE vulnerability library by using a crawler technology;
s102, entity extraction, relation extraction and attribute extraction are carried out on the text obtained in the S101 so as to obtain vulnerability knowledge, component dependency relationship and mapping knowledge between a vulnerability database and a component database.
5. The knowledge-based software supply chain security analysis method according to claim 1, wherein the step S2 comprises:
s201, traversing all vulnerability knowledge, creating relations among vulnerability entity nodes, sub-entity nodes and different nodes, and adding the relations to a knowledge graph so as to construct the vulnerability knowledge graph;
s202, traversing all component knowledge, creating component entity nodes and group nodes, building dependency relationships among components and dependency relationships among groups and components, and adding the dependency relationships into a knowledge graph to construct a component knowledge graph;
s203, traversing all mapping knowledge, and establishing an association relationship between the vulnerability knowledge graph and related nodes in the component knowledge graph, thereby constructing a supply chain knowledge graph.
6. The knowledge-based software supply chain security analysis method according to claim 1, wherein the step S3 comprises:
determining a component or a vulnerability to be analyzed in a supply chain, acquiring an entity corresponding to the component or the vulnerability in a supply chain knowledge graph, searching all propagation paths taking the entity as a starting point, and extracting all information on the propagation paths as a reasoning result.
7. A software supply chain safety analysis system based on a knowledge graph, which is characterized by comprising a computer readable storage medium and a processor;
the computer-readable storage medium is for storing executable instructions;
the processor is configured to read executable instructions stored in the computer readable storage medium and execute the knowledge-graph-based software supply chain security analysis method of any one of claims 1 to 6.
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Inventor after: Sun Mingyuan Inventor after: Cheng Hao Inventor after: Li Chaofan Inventor after: Wang Hu Inventor after: Hu Yutao Inventor after: Zou Deqing Inventor before: Cheng Hao Inventor before: Li Chaofan Inventor before: Wang Hu Inventor before: Hu Yutao Inventor before: Sun Mingyuan Inventor before: Zou Deqing |