System, method, device, and medium for calculating trust scores for OT assets
The system addresses the limitations of traditional OT asset trust computation by integrating direct and indirect factors, providing a more accurate and comprehensive trust scoring method for OT assets, thereby improving risk management and prioritization.
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- SIEMENS AG
- Filing Date
- 2025-01-27
- Publication Date
- 2026-07-30
AI Technical Summary
Traditional trust computation methods for OT assets do not consider the broader network environment, neglecting communication characteristics and interactions with other assets, leading to inaccurate trust assessments.
A system and method that calculates trust scores for OT assets by considering direct impact factors (vulnerability, incident, patch, compliance, and network scores) and indirect impact factors (degree centrality, betweenness centrality, and neighboring asset trustworthiness), with an adjustment module to prevent extreme scores.
Provides a more accurate and holistic assessment of asset trustworthiness, enhancing risk management and prioritization in OT environments by incorporating both direct and indirect impacts.
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Figure CN2025075483_30072026_PF_FP_ABST
Abstract
Description
System, Method, Device, and Medium for Calculating Trust Scores for OT AssetsTECHNICAL FIELD
[0001] The present disclosure relates to the technical field of OT security, in particular to a system, method, device, and medium for calculating trust scores for OT assets.BACKGROUND
[0002] Traditional trust computation methods for OT (operational technology) assets typically rely on asset security events, vulnerability scores, and their impacts. However, these methods have limitations because they do not consider the broader network environment. Assets exist within an interconnected network, and their communication characteristics and interactions with other assets can significantly influence their trust computation values. This invention aims to address these limitations by taking into account the broader network context in which assets operate.SUMMARY
[0003] Embodiments of the present disclosure propose a system, method, device, and medium for calculating trust scores for OT assets. The system comprises a trust evaluation module configured to calculate a trust score for an asset based on direct impact factors and indirect impact factors. The direct impact factors include vulnerability scores, incident scores, patch scores, compliance scores, network scores, and interaction scores. The indirect impact factors include degree centrality, betweenness centrality, and the trustworthiness of neighboring assets. The system further comprises an adjustment module configured to prevent extreme trust scores by recalibrating the final trust score. This invention provides a more accurate and holistic assessment of asset trustworthiness by considering both direct and indirect impacts, thereby improving risk management and prioritization in OT environments.BRIEF DESCRIPTION OF THE DRAWINGS
[0004] To make technical solutions of examples of the present disclosure clearer, accompanying drawings to be used in description of the examples will be simply introduced hereinafter. Obviously, the accompanying drawings to be described hereinafter are only some examples of the present disclosure. Those skilled in the art may obtain other drawings according to these accompanying drawings without creative labor.
[0005] Fig. 1: An exemplary schematic diagram of a system for calculating trust scores for OT assets according to an embodiment of the present disclosure.
[0006] Fig. 2: An exemplary flowchart of a method for calculating trust scores for OT assets according to an embodiment of the present disclosure.
[0007] Fig. 3: An exemplary structural diagram of an electronic device according to an embodiment of the present disclosure.
[0008] List of reference numbers: DETAILED DESCRIPTION
[0009] To make the purpose, technical scheme, and advantages of the disclosure clearer, the following examples are given to further explain the disclosure in detail. Nouns and pronouns related to people in this patent application are not limited to specific gender.
[0010] To be concise and intuitive in description, the scheme of the disclosure is described below by describing several representative embodiments. Many details in the embodiments are only used to help understand the scheme of the disclosure. However, it is obvious that the technical scheme of the disclosure can be realized without being limited to these details. To avoid unnecessarily blurring the scheme of the disclosure, some embodiments are not described in detail, but only the framework is given. Hereinafter, "including" refers to "including but not limited to" , "according to... " refers to "at least according to..., but not limited to... " . When the number of an element is not specifically indicated below, it means that the element can be one or more or can be understood as at least one. The terms "a" or "an" in this disclosure should not be understood as one, but as at least one.
[0011] Fig. 1 is an exemplary schematic diagram of a system for calculating trust scores for operational OT assets according to an embodiment of the present disclosure. As shown in Figure 1, the system 100 includes a trust evaluation module 101 and an adjustment module 102. The trust evaluation module calculates trust scores based on direct and indirect impact factors. The direct impact factors include vulnerability scores, incident scores, patch scores, compliance scores, network scores, and interaction scores. The indirect impact factors include degree centrality, betweenness centrality, and the trustworthiness of neighboring assets. The adjustment module recalibrates the trust score to prevent extremes. By considering both direct and indirect impacts, the invention provides a more accurate and holistic assessment of asset trustworthiness, improving risk management and prioritization in OT environments.
[0012] Fig. 2 is an exemplary flowchart of a method for calculating trust scores for operational OT assets according to an embodiment of the present disclosure. As shown in Figure 2, the method 200 involves the following steps.
[0013] Step 201 calculating trust scores based on direct and indirect impact factors.
[0014] The direct impact factors include vulnerability scores, incident scores, patch scores, compliance scores, network scores, and interaction scores.
[0015] In one embodiment, Step 201 further comprising calculating an incompleteness score based on the presence of essential asset information in an asset information table, wherein a higher incompleteness score negatively impacts the trust score.
[0016] In one embodiment, the incompleteness score is based on the absence of critical information in the asset information table. Critical information includes, but is not limited to, asset ID, name, host name, hardware information, domain, significance, creation time, end time, IP address, and MAC address. If the asset information table lacks the critical information, generates a higher incompleteness score. A higher incompleteness score reduces the asset's trust score because missing information may obscure the true security posture of the asset. Specifically, traverses the fields in the asset information table, counts the number of missing fields, and calculates the incompleteness score based on predefined weights.
[0017] In one embodiment, Step 201 further comprising calculating a distrust experience score based on the frequency of trust evaluations, wherein a higher frequency of evaluations correlates with higher security levels.
[0018] In one embodiment, the distrust experience score is based on the frequency of trust assessments for the asset. A higher assessment frequency indicates greater attention to the asset's security, thus increasing its trust score. records the historical number of assessments for the asset and generates the distrust experience score based on the assessment frequency. The assessment frequency is positively correlated with the score, meaning that more assessments result in a higher score. Specifically, calculates the distrust experience score by dividing the number of assessments by the maximum possible number of assessments and multiplying the result by 100.
[0019] The indirect impact factors include degree centrality, betweenness centrality, and the trustworthiness of neighboring assets.
[0020] In one embodiment, the degree centrality is calculated based on the number of direct connections an asset has with other nodes in the network.
[0021] In one embodiment, degree centrality measures the importance or influence of an asset in the network based on the number of direct connections it has with other nodes. traverses the network topology, counts the number of direct connections for each asset, and calculates degree centrality by dividing the number of direct connections by the total possible connections in the network.
[0022] In one embodiment, the betweenness centrality is calculated based on the proportion of all links that pass through a particular node compared to its neighboring nodes.
[0023] In one embodiment, betweenness centrality measures the asset's control over data flow in the network based on the proportion of all shortest paths that pass through the asset. calculates all shortest paths between nodes, counts the number of paths passing through the specific asset, and calculates betweenness centrality by dividing the number of shortest paths passing through the asset by the total number of shortest paths.
[0024] In one embodiment, the trustworthiness of neighboring assets is calculated based on the volume of communication and the trust levels of neighboring assets.
[0025] In one embodiment, the trustworthiness impact of neighboring assets is based on the communication volume between the asset and its neighbors, as well as the trust levels of the neighboring assets. For asset the trustworthiness impact value from neighboring assets is calculated by summing the product of the communication volume and the trust level for each neighbor, then dividing by the number of neighbors.
[0026] In one embodiment, uses a weighting method to combine degree centrality, betweenness centrality, and the trustworthiness impact of neighboring assets to generate the indirect impact score. Specifically, the indirect impact score is calculated by multiplying each factor by its respective weight and summing the results. The weights are normalized such that their sum equals one.
[0027] Step 202 recalibrating the trust score to prevent extremes.
[0028] This approach ensures that the trust score remains balanced and reflective of the asset's security posture, even as the network environment evolves.
[0029] In one embodiment, Step 202 further comprising recalibrating the trust score to prevent extremes that could skew the overall average.
[0030] In one embodiment, calculates the comprehensive trust score by combining the direct impact score and the indirect impact score using weighted summation. Specifically, the comprehensive trust score is calculated by multiplying the direct impact score and the indirect impact score by their respective weights and summing the results. The weights are normalized such that their sum equals one.
[0031] In one embodiment, dynamically adjusts the trust score using objective weighting methods to adapt to changes in the network environment or asset behavior. Specifically, periodically recalculates the weights to ensure the accuracy and timeliness of the assessment results.
[0032] In one embodiment, recalibrates the trust score using an adjustment module to prevent extreme values that could skew the overall assessment. Specifically, adjusts the trust score by ensuring it falls within a predefined lower and upper bound.
[0033] Embodiments of the present disclosure also propose an electronic device with a processor memory architecture. Fig. 3 is an exemplary structural diagram of an electronic device according to an embodiment of the present disclosure. As shown in Figure 3, electronic device 300 includes a processor 310, a memory 320, and a computer program stored on memory 320 that can run on processor 310. When the computer program is executed by processor 310, the method as described in either of the above is implemented. Among them, memory 320 can be implemented as various storage media such as electrically erasable programmable read-only memory (EEPROM) , flash memory, programmable program read-only memory (PROM) , etc. Processor 310 can be implemented to include one or more central processors or one or more field programmable gate arrays, wherein the field programmable gate array integrates one or more central processor cores. Specifically, the central processing unit or core can be implemented as a CPU, MCU, DSP, and so on.
[0034] It should be noted that not all steps and modules in the above processes and structural diagrams are necessary, and some steps or modules can be ignored according to actual needs. The execution sequence of each step is not fixed and can be adjusted as needed. The division of each module is only for the convenience of describing the functional division used. In actual implementation, a module can be divided into multiple modules, and the functions of multiple modules can also be implemented by the same module. These modules can be in the same device or different devices.
[0035] The hardware modules in each implementation can be implemented mechanically or electronically. For example, a hardware module may include specially designed permanent circuits or logic devices (such as dedicated processors, such as FPGA or ASIC) to complete specific operations. Hardware modules can also include programmable logic devices or circuits temporarily configured by software (such as general-purpose processors or other programmable processors) for performing specific operations. As for the specific use of mechanical methods, either dedicated permanent circuits or temporarily configured circuits (such as software configuration) to implement hardware modules, it can be determined based on cost and time considerations.
[0036] The above is only a preferred embodiment of the present disclosure and is not intended to limit the scope of protection of the present disclosure. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of this disclosure shall be included within the scope of protection of this disclosure.
Claims
1.A system (100) for calculating trust scores for OT assets, comprising:a trust evaluation module (101) , configured to calculate a trust score for an asset based on direct impact factors and indirect impact factors, wherein:the direct impact factors include at least one of vulnerability scores, incident scores, patch scores, compliance scores, network scores, and interaction scores; andthe indirect impact factors include at least one of degree centrality, betweenness centrality, and the trustworthiness of neighboring assets; andan adjustment module (102) , configured to prevent extreme trust scores by recalibrating the final trust score.2.The system according to claim 1, wherein the trust evaluation module is further configured to calculate an incompleteness score based on the presence of essential asset information in an asset information table, wherein a higher incompleteness score negatively impacts the trust score.3.The system according to claim 1, wherein the trust evaluation module is further configured to calculate a distrust experience score based on the frequency of trust evaluations, wherein a higher frequency of evaluations correlates with higher security levels.4.The system according to claim 1, wherein the degree centrality is calculated based on the number of direct connections an asset has with other nodes in the network.5.The system according to claim 1, wherein the betweenness centrality is calculated based on the proportion of all links that pass through a particular node compared to its neighboring nodes.6.The system according to claim 1, wherein the trustworthiness of neighboring assets is calculated based on the volume of communication and the trust levels of neighboring assets.7.The system according to claim 1, wherein the adjustment module is configured to recalibrate the trust score to prevent extremes that could skew the overall average.8.A method (200) for calculating trust scores for OT assets, the method comprising:Calculating (S201) a trust score for an asset based on direct impact factors and indirect impact factors, wherein:the direct impact factors include at least one of vulnerability scores, incident scores, patch scores, compliance scores, network scores, and interaction scores; andthe indirect impact factors include at least one of degree centrality, betweenness centrality, and the trustworthiness of neighboring assets; andpreventing (S202) extreme trust scores by recalibrating the final trust score.9.The method according to claim 8, further comprising calculating an incompleteness score based on the presence of essential asset information in an asset information table, wherein a higher incompleteness score negatively impacts the trust score.10.The method according to claim 8, further comprising calculating a distrust experience score based on the frequency of trust evaluations, wherein a higher frequency of evaluations correlates with higher security levels.11.The method according to claim 8, wherein the degree centrality is calculated based on the number of direct connections an asset has with other nodes in the network.12.The method according to claim 8, wherein the betweenness centrality is calculated based on the proportion of all links that pass through a particular node compared to its neighboring nodes.13.The method according to claim 8, wherein the trustworthiness of neighboring assets is calculated based on the volume of communication and the trust levels of neighboring assets.14.The method according to claim 8, further comprising recalibrating the trust score to prevent extremes that could skew the overall average.15.An electronic device, comprising a processor and a memory, wherein an application program executable by the processor is stored in the memory for causing the processor to execute a method for calculating trust scores for OT assets according to any one of claims 8-14.16.A computer-readable medium comprising computer-readable instructions stored thereon, wherein the computer-readable instructions for executing a method for calculating trust scores for OT assets according to any one of claims 8-14.17.A. computer program product comprising a computer program, upon the computer program is executed by a processor for executing a method for calculating trust scores for OT assets according to any one of claims 8-14.