Detection data full life cycle safety risk assessment and traceability system and method

Abstract

The invention discloses a detection data full life cycle safety risk assessment and traceability system and method, and relates to the technical field of detection data safety management and control and traceability. The system comprises a life cycle structure construction module, a risk factor identification module, a traceability evidence configuration module and a risk traceability deduction module. The method comprises the steps of constructing a node circulation structure, identifying risk factors and establishing mapping, configuring a minimum traceability evidence set and establishing mapping, jointly deducing candidate risk paths, obtaining a final risk path through screening and pruning, and synchronously generating a traceability path. According to the invention, the integration of detection data full-life-cycle risk assessment and traceability is realized, the management and control efficiency and traceability integrity are improved, and the safety management and control requirements of the detection data full-life cycle can be effectively adapted.

Description

Technical Field

[0001] This invention relates to the field of testing data security management and traceability technology, specifically to a system and method for testing data full lifecycle security risk assessment and traceability. Background Technology

[0002] Throughout the entire lifecycle of data collection, transmission, processing, use, archiving, and destruction, data faces multiple security risks, including tampering, forgery, unauthorized access, leakage, and misuse. Security risk assessment and accountability have become critical technical requirements in the industry. Existing security management technologies often employ segmented and modular designs, implementing risk assessment and data accountability as independent functional modules. These two modules only have a sequential execution relationship and lack unified logical reasoning support.

[0003] Traditional risk assessment methods often rely on discrete state monitoring and local anomaly detection, which can only identify the safety of a single link and cannot correlate the flow, state evolution, and risk formation of data throughout its entire lifecycle. Data tracing generally adopts a post-event tracing model, collecting evidence and backtracking after risk assessment is completed. This results in a broad tracing scope, high evidence redundancy, and non-unique tracing paths, making it difficult to quickly locate the source of risk.

[0004] Meanwhile, existing technologies fail to establish an inherent logical connection between lifecycle nodes, risk events, and traceability evidence. Risk assessment and traceability processes are disconnected, failing to achieve mutual constraints and verification. In actual operation, problems such as risk identification without effective traceability, incomplete evidence chains, and unverifiable assessment results easily arise, making it difficult to meet the integrated, traceable, and verifiable security control requirements in high-reliability testing scenarios. Summary of the Invention

[0005] The purpose of this invention is to provide a system and method for full lifecycle security risk assessment and traceability of detection data, so as to solve the problems mentioned in the background art.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: The method for assessing and tracing security risks throughout the entire lifecycle of detection data includes the following steps: S1. The entire lifecycle of the detection data is decomposed into a structured form to obtain several quantifiable and uniquely identified state nodes, and the legal flow relationship between each state node is constructed to form a full lifecycle node flow structure. S2. Real-time acquisition of actual status information of detection data within each status node, identification of risk factors of corresponding status nodes based on actual status information, and establishment of correspondence between status nodes and risk factors; S3. Configure a preset minimum source evidence set for each type of risk factor, so that each risk factor corresponds to a unique set of minimum source evidence that meets the source tracing requirements, and establish the correspondence between risk factors and minimum source evidence sets. S4. Based on the correspondence between state nodes and risk factors, and between risk factors and the minimum source evidence set, candidate risk paths are jointly deduced; candidate risk paths are dynamically screened and pruned to obtain the final risk path, and a source path corresponding to the final risk path is generated simultaneously.

[0007] Furthermore, S1 includes the following: The detection data is divided into four stages from generation to destruction: collection, transmission, storage, processing, use, sharing, archiving, and destruction. These stages are abstracted into independent status nodes, and each status node is assigned a unique identifier. Define the set of state attributes of the data within a node, including data identifier, timestamp, node identifier, operation type, and data format, and define the legal state space of the node; Establish directed edges between legally transitionable state nodes, and summarize all directed edges to form a set of transition relationships; State nodes are combined with legal flow relationships to form a full lifecycle node flow structure, and the flow structure is checked for closure.

[0008] Furthermore, S2 includes the following: The actual state information corresponding to the preset state attribute set is collected in real time at each state node, and the actual state information is compared with the legal state space of the corresponding node one by one to extract the difference features. The discrepancies include abnormal values ​​for a single state attribute and abnormal combinations of state attributes. Pre-set risk factors corresponding to different data security anomaly types, establish a unique correspondence between difference features and risk factors, match and determine the risk factors associated with the status node based on the difference features of the status node, and associate the status node with the corresponding risk factor to construct the mapping relationship between the status node and the risk factor.

[0009] Furthermore, S3 includes the following: Several sets of minimum traceability evidence are pre-defined. Each set of minimum traceability evidence consists of basic evidence that can uniquely support the traceability of the corresponding risk with minimal redundancy and a complete traceability chain. Establish a unique correspondence between risk factors and the minimum source evidence set, and configure a corresponding minimum source evidence set for each risk factor; Risk factors are associated with and stored in relation to their corresponding minimal source evidence sets, forming a mapping relationship between risk factors and minimal source evidence sets.

[0010] Furthermore, S4 includes the following: Based on the full life cycle node flow structure, and combined with the mapping relationship between state nodes and risk factors, and risk factors and minimum traceability evidence set, the flow of state nodes, the association of risk factors, and the binding of minimum traceability evidence set are synchronously and jointly deduced to form a candidate risk path composed of state nodes, risk factors, and minimum traceability evidence set in sequence. Calculate the association completeness of each candidate risk path, and filter and prune the candidate risk paths according to the preset association completeness threshold, retaining the valid paths with an association completeness not less than the threshold as the final risk paths; Based on the final risk path and the corresponding minimum source evidence set, while determining the final risk path, a source path is simultaneously generated, consisting of the corresponding state nodes, risk factors, and minimum source evidence set in an associated order.

[0011] The system for assessing and tracing the security risks of detection data throughout its entire lifecycle includes: a lifecycle structure construction module, a risk factor identification module, a traceability evidence configuration module, and a risk traceability simulation module. The lifecycle structure construction module decomposes the entire lifecycle of the detection data into a structured form, obtaining several quantifiable and uniquely identified state nodes, and constructs the legal flow relationships between each state node to form a full lifecycle node flow structure. The risk factor identification module collects the actual status information of the detection data in each status node in real time, identifies the risk factors of the corresponding status node based on the actual status information, and establishes the correspondence between the status node and the risk factor. The source tracing evidence configuration module configures a preset minimum source tracing evidence set for each type of risk factor, so that each risk factor corresponds to a unique minimum source tracing evidence set that meets the source tracing requirements, and establishes a correspondence between risk factors and minimum source tracing evidence sets. The risk tracing and deduction module jointly deduces candidate risk paths based on the correspondence between state nodes and risk factors, and between risk factors and the minimum tracing evidence set. It then dynamically filters and prunes the candidate risk paths to obtain the final risk path and simultaneously generates the tracing path corresponding to the final risk path.

[0012] Furthermore, the lifecycle structure construction module includes a node partitioning unit and a flow verification unit; The node partitioning unit divides the detection data from generation to destruction into multiple stages and abstracts them into independent state nodes. It assigns a unique identifier to each state node, defines a set of state attributes and a legal state space, and constructs legal flow relationships between state nodes. The flow verification unit performs a closure verification on the flow structure of nodes throughout the entire lifecycle to ensure that there are no isolated nodes that cannot be traced, no inflows without a legitimate source, and no outflows without a legitimate destination.

[0013] Furthermore, the risk factor identification module includes a status acquisition unit and a risk matching unit; The state acquisition unit collects the actual state information corresponding to the preset state attribute set in real time at each state node, compares the actual state information with the legal state space and extracts the difference features; The risk matching unit matches corresponding risk factors based on the differences in characteristics, and establishes and records the mapping relationship between status nodes and risk factors.

[0014] Furthermore, the source tracing evidence configuration module includes an evidence preset unit and an evidence mapping unit; The evidence pre-set unit pre-sets several sets of minimum traceability evidence. Each set of minimum traceability evidence satisfies the requirements of unique support for risk traceability, minimal evidence redundancy, and complete traceability link. The evidence mapping unit establishes a unique correspondence between risk factors and the minimum source evidence set, and configures the corresponding minimum source evidence set for each risk factor to form a mapping relationship.

[0015] Furthermore, the risk tracing and simulation module includes a path simulation unit and a screening and synchronous generation unit; The path deduction unit is based on the full life cycle node flow structure and combines relevant mapping relationships to conduct joint deduction, forming a candidate risk path composed of state nodes, risk factors, and minimum traceability evidence set in sequence; The screening and synchronous generation unit calculates the association completeness of candidate risk paths, performs screening and pruning based on the preset association completeness threshold to obtain the final risk path, and simultaneously generates the corresponding source tracing path while determining the final risk path.

[0016] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention constructs a standardized and traceable flow structure by structurally decomposing and modeling the entire lifecycle of detection data, enabling the quantification and verification of the data's entire process status; it improves the accuracy and timeliness of risk identification by collecting status information in real time and comparing it with the legal space to identify risk factors; it reduces data redundancy while ensuring the integrity of traceability by configuring a unique minimum traceability evidence set for each type of risk factor; and it generates traceability paths simultaneously while obtaining the final risk path by jointly deducing node flow, risk association, and evidence binding, and by quantifying, filtering, and pruning risk paths, thereby achieving integrated execution of risk assessment and traceability. This effectively improves the efficiency of detection data security management and enhances the coherence and reliability of the traceability link, making it suitable for security management and traceability scenarios throughout the entire lifecycle of detection data. Attached Figure Description

[0017] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a schematic diagram of the modules of the detection data full life cycle security risk assessment and traceability system of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Please see Figure 1 The present invention provides the following technical solution: The system for assessing and tracing the security risks of detection data throughout its entire lifecycle includes: a lifecycle structure construction module, a risk factor identification module, a traceability evidence configuration module, and a risk traceability simulation module. The lifecycle structure construction module decomposes the entire lifecycle of the detection data into a structured form, obtaining several quantifiable and uniquely identified state nodes, and constructs the legal flow relationships between each state node to form a full lifecycle node flow structure. The risk factor identification module collects the actual status information of the detection data in each status node in real time, identifies the risk factors of the corresponding status node based on the actual status information, and establishes the correspondence between the status node and the risk factor. The source tracing evidence configuration module configures a preset minimum source tracing evidence set for each type of risk factor, so that each risk factor corresponds to a unique minimum source tracing evidence set that meets the source tracing requirements, and establishes a correspondence between risk factors and minimum source tracing evidence sets. The risk tracing and deduction module jointly deduces candidate risk paths based on the correspondence between state nodes and risk factors, and between risk factors and the minimum tracing evidence set. It then dynamically filters and prunes the candidate risk paths to obtain the final risk path and simultaneously generates the tracing path corresponding to the final risk path.

[0020] The lifecycle structure construction module includes a node partitioning unit and a flow verification unit; The node partitioning unit divides the detection data from generation to destruction into multiple stages and abstracts them into independent state nodes. It assigns a unique identifier to each state node, defines a set of state attributes and a legal state space, and constructs legal flow relationships between state nodes. The flow verification unit performs a closure verification on the flow structure of nodes throughout the entire lifecycle to ensure that there are no isolated nodes that cannot be traced, no inflows without a legitimate source, and no outflows without a legitimate destination.

[0021] The risk factor identification module includes a status acquisition unit and a risk matching unit; The state acquisition unit collects the actual state information corresponding to the preset state attribute set in real time at each state node, compares the actual state information with the legal state space and extracts the difference features; The risk matching unit matches corresponding risk factors based on the differences in characteristics, and establishes and records the mapping relationship between status nodes and risk factors.

[0022] The evidence configuration module includes an evidence preset unit and an evidence mapping unit; The evidence pre-set unit pre-sets several sets of minimum traceability evidence. Each set of minimum traceability evidence satisfies the requirements of unique support for risk traceability, minimal evidence redundancy, and complete traceability link. The evidence mapping unit establishes a unique correspondence between risk factors and the minimum source evidence set, and configures the corresponding minimum source evidence set for each risk factor to form a mapping relationship.

[0023] The risk tracing and simulation module includes a path simulation unit and a screening and synchronous generation unit; The path deduction unit is based on the full life cycle node flow structure and combines relevant mapping relationships to conduct joint deduction, forming a candidate risk path composed of state nodes, risk factors, and minimum traceability evidence set in sequence; The screening and synchronous generation unit calculates the association completeness of candidate risk paths, performs screening and pruning based on the preset association completeness threshold to obtain the final risk path, and simultaneously generates the corresponding source tracing path while determining the final risk path.

[0024] The method for assessing and tracing security risks throughout the entire lifecycle of detection data includes the following steps: S1. The entire lifecycle of the detection data is decomposed into a structured form to obtain several quantifiable and uniquely identified state nodes, and the legal flow relationship between each state node is constructed to form a full lifecycle node flow structure. S2. Real-time acquisition of actual status information of detection data within each status node, identification of risk factors of corresponding status nodes based on actual status information, and establishment of correspondence between status nodes and risk factors; S3. Configure a preset minimum source evidence set for each type of risk factor, so that each risk factor corresponds to a unique set of minimum source evidence that meets the source tracing requirements, and establish the correspondence between risk factors and minimum source evidence sets. S4. Based on the correspondence between state nodes and risk factors, and between risk factors and the minimum source evidence set, candidate risk paths are jointly deduced; candidate risk paths are dynamically screened and pruned to obtain the final risk path, and a source path corresponding to the final risk path is generated simultaneously.

[0025] S1 includes the following: The detection data is divided into four stages from generation to destruction: collection, transmission, storage, processing, use, sharing, archiving, and destruction. These stages are abstracted into independent status nodes, and each status node is assigned a unique identifier. Define the set of state attributes of the data within a node, including data identifier, timestamp, node identifier, operation type, and data format, and define the legal state space of the node; Establish directed edges between legally transitionable state nodes, and summarize all directed edges to form a set of transition relationships; State nodes are combined with legal flow relationships to form a full lifecycle node flow structure, and the flow structure is checked for closure.

[0026] In this embodiment, a unique identifier is assigned to each state node, and the node is defined in a quantifiable way, specifically as follows: Define the set of state attributes of the data within a node, including data identifier, timestamp, node identifier, operation type, and data format; define the legal state space of a node, that is, the range of values ​​and combination constraints of the state attributes allowed under this node; Construct a legal transition relationship between any two state nodes. If node Ni can legally transition to node Nj, then establish a directed edge Eij=(Ni,Nj), and summarize all directed edges to form a set of transition relationships. Combine all state nodes with legal transition relationships to form a full lifecycle node transition structure G=(N,E), where N is the set of state nodes, and N={N1,N2,...,Nn}, N1 is the first state node, N2 is the second state node, and so on, Nn is the nth state node; E is the set of legal transition edges; The flow structure G is subjected to closure verification, specifically: traversing all state nodes, determining whether the inflow and outflow edges of each node belong to the set of legal flow edges E; determining that any flow operation issued by any state node can find a corresponding target node in the flow structure G; ensuring that there are no untraceable isolated nodes, inflows without legal sources, or outflows without legal targets, so that the flow structure has complete traceability and can be used for subsequent risk simulation and traceability path generation.

[0027] S2 includes the following: The actual state information corresponding to the preset state attribute set is collected in real time at each state node, and the actual state information is compared with the legal state space of the corresponding node one by one to extract the difference features. The discrepancies include abnormal values ​​for a single state attribute and abnormal combinations of state attributes. Pre-set risk factors corresponding to different data security anomaly types, establish a unique correspondence between difference features and risk factors, match and determine the risk factors associated with the status node based on the difference features of the status node, and associate the status node with the corresponding risk factor to construct the mapping relationship between the status node and the risk factor.

[0028] In this embodiment, for each state node Ni in the full lifecycle node flow structure G=(N,E), a state acquisition unit is deployed to collect the actual state information of the detection data within the node in real time. The actual state information corresponds one-to-one with the set of node state attributes defined in S1, specifically including actual data identifier, actual timestamp, current node identifier, actual operation type, and actual data format. The actual state information of each collected state node Ni is compared one by one with the legal state space of the node Ni preset in S1, and the difference features between the two are extracted. The difference features are single state attribute value anomaly and state attribute combination anomaly. The single state attribute value anomaly means that the actual value of a single state attribute does not conform to the preset legal value, legal format or legal encoding rule of the node. The state attribute combination anomaly means that the actual combination relationship between multiple state attributes does not conform to the preset combination constraint condition of the node. A set of risk factors F is preset, and F = {F1, F2, ..., Fm}, where F1 is the first risk factor, F2 is the second risk factor, and so on, and Fm is the mth risk factor. Each risk factor corresponds to a type of data security anomaly detection and forms a unique correspondence with the difference characteristics of the node status. Based on the extracted differential features, the corresponding risk factor Fk is matched. If a certain state node Ni has differential features, it is determined that the node Ni is associated with the corresponding matched risk factor Fk; if a certain state node Ni has no differential features, it is determined that the node Ni is not associated with any risk factor. Establish a mapping table between state nodes and risk factors, recording each state node Ni and its associated risk factor Fk, forming a mapping set R1, where R1={(Ni,Fk)|Ni∈N,Fk∈F,i=1,2,...,n;k=1,2,...,m}.

[0029] S3 includes the following: Several sets of minimum traceability evidence are pre-defined. Each set of minimum traceability evidence consists of basic evidence that can uniquely support the traceability of the corresponding risk with minimal redundancy and a complete traceability chain. Establish a unique correspondence between risk factors and the minimum source evidence set, and configure a corresponding minimum source evidence set for each risk factor; Risk factors are associated with and stored in relation to their corresponding minimal source evidence sets, forming a mapping relationship between risk factors and minimal source evidence sets.

[0030] In this embodiment, a minimum source tracing evidence set S is preset, and S={S1,S2,...,Sg}, where S1 is the first minimum source tracing evidence set, S2 is the second minimum source tracing evidence set, and so on, with Sg being the g-th minimum source tracing evidence set; each minimum source tracing evidence set consists of several basic pieces of evidence that can uniquely support the source tracing of the corresponding risk, and satisfies the requirements of minimal evidence redundancy and complete source tracing link; Establish a unique correspondence between risk factors and minimal source evidence sets, such that each risk factor Fk in the risk factor set F corresponds to a unique minimal source evidence set St; Based on the mapping relationship set R1 between state nodes and risk factors established by S2, and the unique correspondence between risk factors and minimum source evidence sets, configure the corresponding minimum source evidence set St for each risk factor Fk; Each risk factor and its corresponding minimum source evidence set are associated and stored to form a mapping relationship set R2 between risk factors and minimum source evidence sets, and R2={(Fk,St)|Fk∈F,St∈S,k=1,2,...,m;t=1,2,...,g}.

[0031] S4 includes the following: Based on the full life cycle node flow structure, and combined with the mapping relationship between state nodes and risk factors, and risk factors and minimum traceability evidence set, the flow of state nodes, the association of risk factors, and the binding of minimum traceability evidence set are synchronously and jointly deduced to form a candidate risk path composed of state nodes, risk factors, and minimum traceability evidence set in sequence. Calculate the association completeness of each candidate risk path, and filter and prune the candidate risk paths according to the preset association completeness threshold, retaining the valid paths with an association completeness not less than the threshold as the final risk paths; Based on the final risk path and the corresponding minimum source evidence set, while determining the final risk path, a source path is simultaneously generated, consisting of the corresponding state nodes, risk factors, and minimum source evidence set in an associated order.

[0032] In this embodiment, based on the mapping relationship set R1 between state nodes and risk factors obtained in S2, and the mapping relationship set R2 between risk factors and minimum traceability evidence set obtained in S3, the full life cycle node flow structure G=(N,E) constructed in S1 is used as the flow basis. The state node flow, risk factor association, and minimum traceability evidence set binding are simultaneously integrated into the deduction process. Through association and linkage, the joint deduction of the full life cycle flow process of detection data is realized, forming several candidate risk paths. The specific logic of the joint simulation is as follows: taking the full life cycle node flow structure G=(N,E) as the flow basis, according to the mapping relationship set R1, the risk factor Fk associated with each state node Ni is bound; through the mapping relationship set R2, the minimum traceability evidence set St corresponding to each risk factor Fk is associated to form a linkage link of "Ni→Fk→St". All linkage links that conform to the node legal flow relationship E are used as candidate risk paths, forming a candidate risk path set P, and P={P1,P2,...,Ph}, where P1 is the first candidate risk path, P2 is the second candidate risk path, and so on, and Ph is the h-th candidate risk path. For each candidate risk path Pd in ​​the candidate risk path set P, calculate its correlation completeness C(Pd) to determine the correspondence completeness and correlation rationality of the path. The specific calculation formula is: C(Pd)=(a×C1+b×C2) / (a+b), where C1 is the correlation completeness of "state node-risk factor" in candidate risk path Pd, C1=number of effective (Ni,Fk) pairs in path Pd / total (Ni,Fk) pairs in path Pd. If all Ni and Fk correlations in path Pd meet R1, then C1=1; C2 is the correlation completeness of "risk factor-minimum source evidence set" in candidate risk path Pd, C2=number of effective (Fk,St) pairs in path Pd / total (Fk,St) pairs in path Pd. If all Fk and St correlations in path Pd meet R2, then C2=1; a and b are weight coefficients, and a>0, b>0. A preset association completeness threshold T is used to dynamically filter and prune candidate risk paths. Specifically, if the association completeness C(Pd) of a candidate risk path Pd is ≥ T, the path is determined to be a valid path and is retained; if the association completeness C(Pd) of a candidate risk path Pd is < T, the path is determined to be a redundant path and is removed; all retained valid paths constitute the final risk path set Q = {Q1, Q2, ..., Qp}. Based on each final risk path in the final risk path set Q, and combined with its associated minimum source evidence set St, a source path is generated simultaneously while determining the final risk path. The source path corresponds one-to-one with the final risk path and is composed of the corresponding state node Ni, risk factor Fk, and minimum source evidence set St in the order of the linkage link.

[0033] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0034] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for assessing and tracing security risks throughout the entire lifecycle of detection data, characterized by: The method includes the following steps: S1. The entire lifecycle of the detection data is decomposed into a structured form to obtain several quantifiable and uniquely identified state nodes, and the legal flow relationship between each state node is constructed to form a full lifecycle node flow structure. S2. Real-time acquisition of actual status information of detection data within each status node, identification of risk factors of corresponding status nodes based on actual status information, and establishment of correspondence between status nodes and risk factors; S3. Configure a preset minimum source evidence set for each type of risk factor, so that each risk factor corresponds to a unique set of minimum source evidence that meets the source tracing requirements, and establish the correspondence between risk factors and minimum source evidence sets. S4. Based on the correspondence between state nodes and risk factors, and between risk factors and the minimum source evidence set, candidate risk paths are jointly deduced; candidate risk paths are dynamically screened and pruned to obtain the final risk path, and a source path corresponding to the final risk path is generated simultaneously.

2. The method for full lifecycle security risk assessment and traceability of detection data according to claim 1, characterized in that: S1 includes the following: The detection data is divided into four stages from generation to destruction: collection, transmission, storage, processing, use, sharing, archiving, and destruction. These stages are abstracted into independent status nodes, and each status node is assigned a unique identifier. Define the set of state attributes of the data within a node, including data identifier, timestamp, node identifier, operation type, and data format, and define the legal state space of the node; Establish directed edges between legally transitionable state nodes, and summarize all directed edges to form a set of transition relationships; State nodes are combined with legal flow relationships to form a full lifecycle node flow structure, and the flow structure is checked for closure.

3. The method for full lifecycle security risk assessment and traceability of detection data according to claim 2, characterized in that: S2 includes the following: The actual state information corresponding to the preset state attribute set is collected in real time at each state node, and the actual state information is compared with the legal state space of the corresponding node one by one to extract the difference features. The discrepancies include abnormal values ​​for a single state attribute and abnormal combinations of state attributes. Pre-set risk factors corresponding to different data security anomaly types, establish a unique correspondence between difference characteristics and risk factors, and match and determine the risk factors associated with a node based on the difference characteristics of the status node. Associate and record the status nodes with the corresponding risk factors to construct a mapping relationship between status nodes and risk factors.

4. The method for full lifecycle security risk assessment and traceability of detection data according to claim 3, characterized in that: S3 includes the following: Several sets of minimum traceability evidence are pre-defined. Each set of minimum traceability evidence consists of basic evidence that can uniquely support the traceability of the corresponding risk with minimal redundancy and a complete traceability chain. Establish a unique correspondence between risk factors and the minimum source evidence set, and configure a corresponding minimum source evidence set for each risk factor; Risk factors are associated with and stored in relation to their corresponding minimal source evidence sets, forming a mapping relationship between risk factors and minimal source evidence sets.

5. The method for full lifecycle security risk assessment and traceability of detection data according to claim 4, characterized in that: S4 includes the following: Based on the full life cycle node flow structure, and combined with the mapping relationship between state nodes and risk factors, and risk factors and minimum traceability evidence set, the flow of state nodes, the association of risk factors, and the binding of minimum traceability evidence set are synchronously and jointly deduced to form a candidate risk path composed of state nodes, risk factors, and minimum traceability evidence set in sequence. Calculate the association completeness of each candidate risk path, and filter and prune the candidate risk paths according to the preset association completeness threshold, retaining the valid paths with an association completeness not less than the threshold as the final risk paths; Based on the final risk path and the corresponding minimum source evidence set, while determining the final risk path, a source path is simultaneously generated, consisting of the corresponding state nodes, risk factors, and minimum source evidence set in an associated order.

6. A system for assessing and tracing the security risks of testing data throughout its entire lifecycle, applied to the method for assessing and tracing the security risks of testing data throughout its entire lifecycle as described in any one of claims 1-5, characterized in that: The system includes: a life cycle structure construction module, a risk factor identification module, a source tracing evidence configuration module, and a risk source tracing deduction module; The lifecycle structure construction module decomposes the entire lifecycle of the detection data into a structured form, obtaining several quantifiable and uniquely identified state nodes, and constructs the legal flow relationship between each state node to form a full lifecycle node flow structure. The risk factor identification module collects the actual status information of the detection data in each status node in real time, identifies the risk factors of the corresponding status node based on the actual status information, and establishes the correspondence between the status node and the risk factor. The source tracing evidence configuration module configures a preset minimum source tracing evidence set for each type of risk factor, so that each risk factor corresponds to a unique minimum source tracing evidence set that meets the source tracing requirements, and establishes a correspondence between risk factors and minimum source tracing evidence sets. The risk tracing and deduction module jointly deduces candidate risk paths based on the correspondence between state nodes and risk factors, and between risk factors and the minimum tracing evidence set. It then dynamically filters and prunes the candidate risk paths to obtain the final risk path and simultaneously generates the tracing path corresponding to the final risk path.

7. The detection data full lifecycle security risk assessment and traceability system according to claim 6, characterized in that: The lifecycle structure construction module includes a node partitioning unit and a flow verification unit; The node partitioning unit divides the detection data from generation to destruction into multiple stages and abstracts them into independent state nodes. It assigns a unique identifier to each state node, defines a set of state attributes and a legal state space, and constructs a legal flow relationship between state nodes. The flow verification unit performs a closure verification on the flow structure of nodes throughout the entire lifecycle to ensure that there are no isolated nodes that cannot be traced, no inflows without a legitimate source, and no outflows without a legitimate destination.

8. The detection data full lifecycle security risk assessment and traceability system according to claim 6, characterized in that: The risk factor identification module includes a status acquisition unit and a risk matching unit; The state acquisition unit collects the actual state information corresponding to the preset state attribute set in real time at each state node, compares the actual state information with the legal state space and extracts the difference features. The risk matching unit matches corresponding risk factors based on the differences in characteristics, and establishes and records the mapping relationship between status nodes and risk factors.

9. The detection data full lifecycle security risk assessment and traceability system according to claim 6, characterized in that: The source tracing evidence configuration module includes an evidence preset unit and an evidence mapping unit; The evidence pre-setting unit pre-sets several sets of minimum traceability evidence, each set of minimum traceability evidence satisfying the following conditions: unique support for risk traceability, minimal evidence redundancy, and complete traceability link. The evidence mapping unit establishes a unique correspondence between risk factors and the minimum source evidence set, and configures a corresponding minimum source evidence set for each risk factor to form a mapping relationship.

10. The detection data full lifecycle security risk assessment and traceability system according to claim 6, characterized in that: The risk tracing and simulation module includes a path simulation unit and a screening and synchronous generation unit; The path deduction unit is based on the full life cycle node flow structure and combines relevant mapping relationships to perform joint deduction, forming a candidate risk path composed of state nodes, risk factors, and minimum traceability evidence sets in sequence. The screening and synchronous generation unit calculates the association completeness of candidate risk paths, performs screening and pruning based on a preset association completeness threshold to obtain the final risk path, and simultaneously generates the corresponding source tracing path while determining the final risk path.

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