System and apparatus adapted to facilitate trustworthiness evaluation, and processing method associated therewith

Abstract

An apparatus suitable for facilitating credibility evaluation is provided. The apparatus may include a first module and a second module. The first module may be configured to receive at least one input signal that may be processed by the second module to generate one or more output signals. The input signal (s) may be associated with at least one user demand and / or at least one security target. The input signal (s) may be processed by identifying at least one security metric associated with the at least one security demand. The security requirement (s) may be based on the at least one user requirement and / or the at least one security goal, determine a positive determination, a negative determination, or an uncertain determination of satisfaction of a security metric with respect to the at least one security goal and / or the at least one user requirement, and derive at least one confidence score accordingly.

Description

Technical Field

[0001] The present disclosure generally relates to one or both of a system and a device suitable for facilitating a credibility assessment. Specifically, according to an embodiment of the present disclosure, the present disclosure may relate to a system and / or device suitable for facilitating a credibility assessment associated with software associated with, for example, an automotive system (e.g., an automotive software system). The present disclosure also relates to a processing method that may be associated with the system and / or device. Background Art

[0002] Generally, software-based (e.g., computer code) control of a vehicle can be considered more prevalent. It is expected that (one or more) software failures / vulnerabilities may potentially affect the functionality and safety of one or more key vehicle systems, which may lead to concerns about safety and / or reliability. (One or more) failures and / or vulnerabilities may generally be caused by software errors, which may cause the corresponding software to behave in an unexpected manner. In one example, this unexpected manner may be in the form of additional functionality that the developer did not consider. In another example, an unexpected system crash may occur when executing the software.

[0003] Currently, various techniques have been used to try to identify and / or analyze weaknesses in order to minimize potential failures. These techniques may include, for example, formal verification, static / dynamic analysis of code, and fuzzing.

[0004] The present disclosure contemplates that conventional techniques do not facilitate identifying and / or analyzing vulnerabilities in an efficient manner, as software patches appear to be required more frequently than desired / necessary, and that such problem or problems need to be addressed (or at least mitigated). Summary of the invention

[0005] According to one aspect of the present disclosure, a device suitable for facilitating a credibility assessment associated with, for example, a vehicle is provided. The vehicle may, for example, be associated with a system infrastructure (e.g., a software-based infrastructure). For example, according to an embodiment of the present disclosure, the system infrastructure associated with the vehicle may correspond to the previously mentioned automotive-based software system. In addition, according to an embodiment of the present disclosure, the credibility assessment may, for example, be based on one or both of at least one credibility score and a total score. It is contemplated that according to an embodiment of the present disclosure, (one or more) credibility scores and / or the total score may, for example, be an indicative assessment of the credibility associated with the system infrastructure. In one embodiment, the device may be suitable for facilitating a credibility assessment associated with an automotive software system.

[0006] In one embodiment, the device may, for example, include a first module and a second module. The first module may, for example, be coupled to the second module.

[0007] The first module may, for example, be configured to receive at least one input signal, and the second module may, for example, be configured to process the input signal(s) in such a way as to generate one or more output signals.

[0008] According to an embodiment of the present disclosure, (one or more) input signals may be associated with, for example, one or both of at least one user requirement and at least one security goal (i.e., at least one user requirement and / or at least one security goal; at least one of at least one user requirement and at least one security goal).

[0009] Furthermore, in one embodiment, the input signal(s) may be processed by:

[0010] Identifying (eg, by way of a feature selection based process) at least one security metric associated with at least one security requirement. According to embodiments of the present disclosure, the security requirement(s) may be based on, for example, at least one user requirement and / or at least one security goal.

[0011] Determining (e.g., by way of analysis-based processing) a positive determination, a negative determination, or an indeterminate determination (i.e., one of a positive determination, a negative determination, and an indeterminate determination) regarding satisfaction of a security metric with respect to at least one security goal and / or at least one user requirement

[0012] • deriving (eg, by way of an analysis-based process) at least one confidence score based on the positive determination, the negative determination, or the inconclusive determination (ie, one of the positive determination, the negative determination, and the inconclusive determination).

[0013] In one embodiment, the output signal(s) may be based on the credibility score(s), for example.Furthermore, according to embodiments of the present disclosure, the output signal(s) may indicate a credibility assessment.

[0014] In one embodiment, the second module may be configured, for example, to process the input signal(s) by identifying a plurality of security metrics. Each security metric (of the plurality of security metrics) may, for example, be associated with at least one security goal and / or at least one user requirement. According to an embodiment of the present disclosure, a credibility score may be derived in association with each security metric, for example, based on a positive determination, a negative determination, or an uncertain determination (i.e., one of a positive determination, a negative determination, and an uncertain determination) of satisfaction of the security metric with respect to the security goal and / or the user requirement.

[0015] In one embodiment, the second module may, for example, be configured to derive a plurality of confidence scores based on a plurality of security metrics.

[0016] In one embodiment, the second module may be configured to aggregate multiple credibility scores to generate a total score. In addition, according to an embodiment of the present disclosure, the credibility evaluation may be based on the total score, for example.

[0017] In one embodiment, the device may, for example, also include a third module, which may, for example, be configured to transmit (one or more) output signals to facilitate one or both of visual perception and auditory perception (i.e., visual perception and / or auditory perception, at least one of visual perception and auditory perception) of one or both of (one or more) credibility scores and the total score (i.e., (one or more) credibility scores and / or the total score; at least one of (one or more) credibility scores and the total score).

[0018] According to embodiments of the present invention, it is expected that at least one measurable credibility evaluation result (i.e., credibility assessment) can be facilitated in the above manner. Specifically, it is understandable that, according to embodiments of the present invention, the above credibility score and / or total score can be, for example, with at least one measurable credibility evaluation result.

[0019] According to embodiments of the present disclosure, it is expected that facilitating measurable credibility evaluation results can, for example, facilitate a quantifiable overview of a vehicle-based software system during the life cycle of, for example, a vehicle (e.g., a car). Such a quantifiable overview can, for example, be useful to, for example, interested parties (e.g., (one or more) developers, (one or more) software architects, (one or more) system architects, and / or (one or more) security and privacy managers). For example, identifying security metrics associated with the credibility of a vehicle-based software system can potentially generate one or more quantitative scores associated with one or more security risks during the development and / or deployment phases, which provides a brief and / or intuitive security evaluation for interested parties (e.g., (one or more) developers and / or (one or more) other stakeholders). It is expected that according to embodiments of the present disclosure, credibility evaluations can, for example, be communicated via an interactive dashboard (e.g., an electronic dashboard module), which can, for example, facilitate the traceability of security defects in software modules / platforms associated with vehicle-based software systems.

[0020] Furthermore, it is contemplated that by facilitating measurable credibility evaluation results (i.e., credibility assessments), the cybersecurity health of automotive-based software systems can be evaluated before the vehicle is on the road. By doing so, the number of product (e.g., vehicle) recalls due to software defects can potentially be at least reduced. Additionally, software defects can be addressed during the development lifecycle phase. In this regard, it is understood that according to embodiments of the present disclosure, the overall software product development can, for example, be made more efficient and / or maintenance costs can be potentially reduced.

[0021] According to embodiments of the present disclosure, it is expected that facilitating measurable credibility evaluation results (i.e., credibility assessments) can be used, for example, to evaluate safety risks and generate credibility reports that can build a software credibility database for risk assessment during the development phase. It is further expected that according to embodiments of the present disclosure (e.g., in conjunction with the after-sales phase), facilitating measurable credibility evaluation results (i.e., credibility assessments) can be used, for example, to assign one or more credibility scores of automotive software modules associated with an automotive-based software system to one or more relevant stakeholders (e.g., (one or more) users of (one or more) vehicles and / or (one or more) software architects) in order to, for example, improve the safety level.

[0022] The above-mentioned advantageous aspects (one or more) of the device of the present disclosure may also be similarly (all) applied to the (one or more) aspects of the following processing methods of the present disclosure. Similarly, all the following advantageous aspects (one or more) of the processing methods of the present disclosure may also be similarly (all) applied to the above-mentioned aspects (one or more) of the device of the present disclosure.

[0023] According to one aspect of the present disclosure, according to an embodiment of the present disclosure, a processing method is provided that may be suitable, for example, for facilitating a credibility evaluation. The credibility evaluation may be associated with, for example, a vehicle. The vehicle may, for example, be associated with a system infrastructure (e.g., a software-based infrastructure). For example, according to an embodiment of the present disclosure, the system infrastructure associated with the vehicle may correspond to the previously mentioned automotive-based software system. In addition, according to an embodiment of the present disclosure, the credibility evaluation may, for example, be based on one or both of at least one credibility score and a total score. It is contemplated that according to an embodiment of the present disclosure, (one or more) credibility scores and / or the total score may, for example, be an indicative assessment of the credibility associated with the system infrastructure. In one embodiment, the processing method may, for example, be suitable for facilitating a credibility evaluation associated with an automotive software system.

[0024] According to an embodiment of the present disclosure, the processing method may, for example, include an analysis step.

[0025] In one embodiment, the analyzing step may, for example, include processing (eg, according to aspects of the present disclosure, by a device as previously mentioned) at least one input signal to generate at least one output signal.

[0026] The input signal(s) may, for example, be associated with / include / indicate one or both of at least one user requirement and at least one security goal (i.e., at least one user requirement and / or at least one security goal; at least one of at least one user requirement and at least one security goal).

[0027] In one embodiment, the input signal(s) may be processed, for example, by:

[0028] Identifying (e.g., by way of feature selection-based processing) at least one security metric associated with at least one security requirement. According to embodiments of the present disclosure, the security requirement(s) may be based, for example, on security goal(s) and / or user requirement(s).

[0029] Determining (e.g., by way of analysis-based processing) a positive determination, a negative determination, or an indeterminate determination (i.e., one of a positive determination, a negative determination, and an indeterminate determination) regarding satisfaction of a security metric with respect to at least one security goal and / or at least one user requirement

[0030] • deriving (eg, by way of an analysis-based process) at least one confidence score based on the positive determination, the negative determination, or the inconclusive determination (ie, one of the positive determination, the negative determination, and the inconclusive determination).

[0031] In one embodiment, the output signal(s) may be based on the confidence score(s), for example.

[0032] In one embodiment, the output signal(s) may, for example, be indicative of a confidence rating.

[0033] In one embodiment, the input signal(s) may be processed, for example, by identifying a plurality of security metrics. Each of the plurality of security metrics may be associated, for example, with at least one security goal and / or at least one user requirement.

[0034] In one embodiment, a confidence score may be derived in association with each security metric, for example based on a positive determination, a negative determination, or an uncertain determination (i.e., one of a positive determination, a negative determination, and an uncertain determination) regarding satisfaction of the security metric with respect to security goals and / or user requirements.

[0035] In one embodiment, multiple confidence scores may be derived, for example, based on multiple security metrics.

[0036] In one embodiment, the processing method may, for example, further include aggregating multiple credibility scores to generate an overall score.

[0037] In one embodiment, the credibility rating may be based on an overall score, for example.

[0038] According to embodiments of the present invention, it is expected that at least one measurable credibility evaluation result (i.e., credibility assessment) can be facilitated in the above manner. Specifically, it is understandable that, according to embodiments of the present invention, the above credibility score and / or total score can be, for example, with at least one measurable credibility evaluation result.

[0039] According to embodiments of the present disclosure, it is expected that facilitating measurable credibility evaluation results can, for example, facilitate a quantifiable overview of a vehicle-based software system during the life cycle of, for example, a vehicle (e.g., a car). Such a quantifiable overview can, for example, be useful to, for example, interested parties (e.g., (one or more) developers, (one or more) software architects, (one or more) system architects, and / or (one or more) security and privacy managers). For example, identifying security metrics associated with the credibility of a vehicle-based software system can potentially generate one or more quantitative scores associated with one or more security risks during the development and / or deployment phases, which provides a brief and / or intuitive security evaluation for interested parties (e.g., (one or more) developers and / or (one or more) other stakeholders). It is expected that according to embodiments of the present disclosure, credibility evaluations can, for example, be communicated via an interactive dashboard (e.g., an electronic dashboard module), which can, for example, facilitate the traceability of security defects in software modules / platforms associated with vehicle-based software systems.

[0040] Furthermore, it is contemplated that by facilitating measurable credibility evaluation results (i.e., credibility assessments), the cybersecurity health of automotive-based software systems can be evaluated before the vehicle is on the road. By doing so, the number of product (e.g., vehicle) recalls due to software defects can potentially be at least reduced. Additionally, software defects can be addressed during the development lifecycle phase. In this regard, it is understood that according to embodiments of the present disclosure, the overall software product development can, for example, be made more efficient and / or maintenance costs can be potentially reduced.

[0041] According to embodiments of the present disclosure, it is expected that facilitating measurable credibility evaluation results (i.e., credibility assessments) can be used, for example, to evaluate safety risks and generate credibility reports that can build a software credibility database for risk assessment during the development phase. It is further expected that according to embodiments of the present disclosure (e.g., in conjunction with the after-sales phase), facilitating measurable credibility evaluation results (i.e., credibility assessments) can be used, for example, to assign one or more credibility scores of automotive software modules associated with an automotive-based software system to one or more relevant stakeholders (e.g., (one or more) users of (one or more) vehicles and / or (one or more) software architects) in order to, for example, improve the safety level.

[0042] The present disclosure also contemplates a computer program that may include instructions that, when executed by a computer, cause the computer to perform the analysis steps as discussed with reference to the processing method.

[0043] The present disclosure still further contemplates a computer-readable storage medium (not shown) having stored therein data representing software executable by a computer, the software including instructions that, when executed by a computer, perform the analysis steps as discussed with reference to the processing method. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Embodiments of the present disclosure are described hereinafter with reference to the following drawings, in which:

[0045] Figure 1 A system that may include at least one device according to an embodiment of the present disclosure is shown;

[0046] Figure 2 The embodiment according to the present disclosure is shown in more detail. Figure 1 equipment; and

[0047] Figure 3 The embodiment according to the present disclosure is shown Figure 1 System-related processing methods. DETAILED DESCRIPTION

[0048] According to embodiments of the present disclosure, the present disclosure anticipates that software patch repair may have undesirable economic impacts (e.g., increased costs) associated with, for example, the automotive field. For example, software patch repair may potentially be expensive once a vehicle is in production or already on the road.

[0049] According to embodiments of the present disclosure, it is contemplated that providing a framework, for example, for evaluating the trustworthiness associated with an automotive system may be helpful. For example, the present disclosure contemplates that a framework for evaluating the trustworthiness of software associated with an automotive-based software system (e.g., a software system associated with a vehicle such as an automobile) may help to at least reduce the frequency with which software patching occurs (or preferably, eliminate the need for software patching to occur).

[0050] The present disclosure contemplates that software credibility may be considered, for example, as a confidence that a set of requirements have been met. According to embodiments of the present invention, it is further contemplated that credibility associated with software may be used to evaluate one or more automotive software modules associated with an automotive-based software system by, for example, providing / deriving one or more credibility scores. According to embodiments of the present invention, (one or more) credibility scores may be provided / derived, for example, based on one or more perspectives (e.g., multi-dimensional).

[0051] According to embodiments of the present disclosure, it is expected that facilitating measurable credibility evaluation results can, for example, facilitate a quantifiable overview of a vehicle-based software system during the life cycle of, for example, a vehicle (e.g., a car). Such a quantifiable overview can, for example, be useful to, for example, interested parties (e.g., (one or more) developers, (one or more) software architects, (one or more) system architects, and / or (one or more) security and privacy managers). For example, identifying security metrics associated with the credibility of a vehicle-based software system can potentially generate one or more quantitative scores associated with one or more security risks during the development and / or deployment phases, which provides a brief and / or intuitive security evaluation for interested parties (e.g., (one or more) developers and / or (one or more) other stakeholders). It is expected that according to embodiments of the present disclosure, credibility evaluations can, for example, be communicated via an interactive dashboard (e.g., an electronic dashboard module), which can, for example, facilitate the traceability of security defects in software modules / platforms associated with vehicle-based software systems.

[0052] Furthermore, it is contemplated that by facilitating measurable credibility evaluation results (i.e., credibility assessments), the cybersecurity health of automotive-based software systems can be evaluated before the vehicle is on the road. By doing so, the number of product (e.g., vehicle) recalls due to software defects can potentially be at least reduced. Additionally, software defects can be addressed during the development lifecycle phase. In this regard, it is understood that according to embodiments of the present disclosure, the overall software product development can, for example, be made more efficient and / or maintenance costs can be potentially reduced.

[0053] According to embodiments of the present disclosure, it is expected that facilitating measurable credibility evaluation results (i.e., credibility assessments) can be used, for example, to evaluate safety risks and generate credibility reports that can build a software credibility database for risk assessment during the development phase. It is further expected that according to embodiments of the present disclosure (e.g., in conjunction with the after-sales phase), facilitating measurable credibility evaluation results (i.e., credibility assessments) can be used, for example, to assign one or more credibility scores of automotive software modules associated with an automotive-based software system to one or more relevant stakeholders (e.g., (one or more) users of (one or more) vehicles and / or (one or more) software architects) in order to, for example, improve the safety level.

[0054] The following will refer to Figures 1 to 3 The foregoing is discussed in more detail.

[0055] refer to Figure 1 , shows a system 100 according to an embodiment of the present disclosure. As shown in the figure, according to an embodiment of the present disclosure, the system 100 may include one or more devices 102, at least one apparatus 104, and an optional communication network 106.

[0056] The device(s) 102 may be coupled to the apparatus(s) 104. Specifically, the device(s) 102 may be coupled to the apparatus(s) 104 via a communication network 106, for example.

[0057] In one embodiment, (one or more) devices 102 can be coupled to a communication network 106, and (one or more) apparatuses 104 can be coupled to the communication network 106. The coupling can be in the form of one or both of a wired coupling and a wireless coupling. According to an embodiment of the present disclosure, (one or more) devices 102 can generally be configured to communicate with (one or more) apparatuses 104 via the communication network 106.

[0058] Generally, according to an embodiment of the present disclosure, (one or more) devices 102 may be configured to receive one or more input signals and process (one or more) input signals to generate / derive one or more output signals. In addition, according to an embodiment of the present disclosure, (one or more) devices 104 may, for example, be configured to generate (one or more) input signals and transmit (one or more) input signals to one or both of (one or more) devices 102.

[0059] According to an embodiment of the present disclosure, the system 100 may be suitable for facilitating credibility assessment, for example. According to an embodiment of the present disclosure, facilitating credibility assessment may involve facilitating measurable credibility assessment results, for example.

[0060] According to embodiments of the present disclosure, it is generally contemplated that system 100 may, for example, relate to / correspond to / include a framework associated with software credibility assessment, which may, for example, focus on defining measurable safety metrics from one or more perspectives, which may be used to evaluate (e.g., automatically evaluate) one or more credibility scores of one or more software modules that may be included in a software system. According to embodiments of the present disclosure, the software system may, for example, correspond to / be associated with an automotive-based software system.

[0061] In one embodiment, the framework may, for example, include / associated with:

[0062] · derive / define one or more security metrics, and

[0063] · Evaluate / assess security metric(s),

[0064] As will be discussed below in sequence according to the embodiments of the present disclosure.

[0065] According to an embodiment of the present disclosure, it is expected that in order to derive / define one or more appropriate / useful security metrics (e.g., correct metrics), one or more parameters should be established. According to an embodiment of the present disclosure, (one or more) parameters may, for example, include / are based on / associated with any of the following:

[0066] At least one secure environment,

[0067] At least one safety goal, and

[0068] At least one security requirement,

[0069] or any combination thereof.

[0070] In one embodiment, the parameter(s) may be based, for example, on the security environment, security goal(s), and security requirement(s).

[0071] The security environment may be associated, for example, with at least one threat model and at least one attack surface analysis, which may be useful for analyzing malicious intent of one or more adversaries.

[0072] The safety goal(s) may, for example, be associated with an identification of one or more objectives and / or constraints affecting the system 100 , which may be useful for guiding one or more subsequent safety activities.

[0073] The security requirement(s) may be based, for example, on one or both of the security goal(s) and the user requirement(s). In general, the security requirement(s) may be based, for example, on security assurance and / or security functionality. The security requirement(s) may be used, for example, to define corresponding security metrics or metrics, which may be useful for evaluating trustworthiness (i.e., credibility assessment).

[0074] The present disclosure contemplates that by doing so, it may be appreciated that one or more security risks associated with one or more software modules / components of a software system may potentially be quantifiable, according to embodiments of the present disclosure.

[0075] It is contemplated that according to embodiments of the present disclosure, (one or more) derived / defined security metrics may be evaluated (e.g., automatically evaluated) based on, for example, evidence extracted from one or more different testing tools and industry-related standards and regulations. According to embodiments of the present disclosure, a credibility metric may be used to generate a credibility score based on an evaluation associated with the security metric. For example, at least one credibility metric may be used to further aggregate evidence about different security metrics to generate one or more credibility scores. As an option, according to embodiments of the present disclosure, the credibility score may, for example, be aggregated into a total score for a software component / module.

[0076] Hereinafter, the system 100 will now be discussed based on an example context of a vehicle-based software system associated with a vehicle (eg, a car) according to an embodiment of the present disclosure.

[0077] In this regard, in an example context, the previously mentioned security goal(s) may be established based on standard(s) and regulation(s) related to the automotive domain / domain. Furthermore, the security goal(s) may identify goals(s) and constraints(s) that impact the automotive-based systems(s). Additionally, the derived / defined security metrics(s) as previously discussed may be evaluated (e.g., automatically evaluated) based on, for example, evidence extracted from one or more different test tools and automotive cybersecurity standards and regulations. Furthermore, the previously mentioned security requirements(s) may be guided by security goal(s) and automotive-related OEM (original equipment manufacturer) requirements.

[0078] As mentioned previously, according to an embodiment of the present disclosure, the system 100 may include one or more devices 102 , at least one apparatus 104 , and an optional communication network 106 .

[0079] Device(s) 102 may correspond, for example, to one or more computers (e.g., electronic devices / modules with computing capabilities (such as electronic mobile devices that can be carried into a vehicle) or electronic modules (such as electronic dashboard modules that can be installed in a vehicle in a "plug and play" manner, for example, or existing electronic control units or ECUs that have high-performance computing capabilities and connect to existing vehicle networks to receive all types of vehicle data, sensor data, and user data)). In one embodiment, device(s) 102 may include one or more processors (not shown) that may be configured to perform one or more processing tasks.

[0080] Generally, as previously mentioned, according to embodiments of the present disclosure, the device(s) 102 may be configured to receive input signal(s) and process the input signal(s) in a manner so as to generate / derive one or more output signals. According to embodiments of the present disclosure, the input signal(s) may, for example, correspond to / include / indicate one or both of safety goals(s) (e.g., safety goals(s) established based on standards(s) and regulations(s) related to the automotive field) and user requirements(s) (e.g., OEM requirements).

[0081] According to an embodiment of the present disclosure, (one or more) devices 102 may be configured, for example, to process (one or more) input signals by any one of feature selection-based processing, analysis-based processing, and aggregation-based processing, or any combination thereof (i.e., feature selection-based processing, analysis-based processing, and / or aggregation-based processing) to generate / derive (one or more) output signals.

[0082] With respect to feature selection-based processing, the device(s) 102 may, for example, be configured to identify / extract / define one or more parameters associated with security requirement(s), which may be based on security goal(s) and / or user requirement(s). The identified / extracted / defined parameters may, for example, correspond to / include / associated with one or more security metrics, which may be associated with security requirement(s).

[0083] With respect to analysis-based processing, the device(s) 102 may, for example, be configured to generate / derive one or more credibility scores associated with a security metric. For example, a credibility score may be derived in association with a security metric. In one embodiment, the credibility score(s) may be generated / derived based on one or more analysis techniques, which may include any one or any combination of penetration testing, fuzzing, vulnerability assessment, and model-based assessment.

[0084] With respect to aggregation-based processing, device(s) 102 may, for example, be configured to aggregate the credibility score(s) to generate an overall score (eg, an overall credibility score).

[0085] According to an embodiment of the present disclosure, (one or more) output signals may, for example, correspond to / include / indicate one or both of (one or more) credibility scores and the total score (i.e., (one or more) credibility scores and / or the total score). In one example, an output signal may correspond to a credibility score, and another output signal may correspond to another credibility score. In another example, an output signal may correspond to a credibility score, another output signal may correspond to another credibility score, and yet another output signal may correspond to the total score. In yet another example, (one or more) output signals may correspond to (one or more) credibility scores. In yet another example, (one or more) output signals may correspond to the total score.

[0086] According to an embodiment of the present disclosure, the (one or more) devices 104 may be configured, for example, to generate (one or more) input signals and / or transmit (one or more) input signals. For example, the (one or more) input signals may be transmitted from the (one or more) devices 104 to the (one or more) devices 102. In one example, the (one or more) devices 104 may be associated with / correspond to / include one or more databases (e.g., (one or more) publicly available online databases and / or (one or more) private databases) that may be associated with known / established industry standards and regulations (e.g., standards and regulations related to the automotive field), and one or more input signals associated with / correspond to / include such known / established industry standards and regulations may be transmitted from the (one or more) devices 104. In another example, the (one or more) devices 104 may be used by one or more users (e.g., one or more users associated with an OEM) to generate one or more input signals including / associated with / corresponding to user requirements (e.g., OEM requirements), and the (one or more) generated input signals may be transmitted from the (one or more) devices 104. In yet another example, the device(s) 104 may be configured to transmit one or more input signals associated with / corresponding to / including known / established industry standards and regulations, and generate one or more input signals that may include / associated with / correspond to user requirements. In yet another example, one or more devices 104 may be configured to transmit one or more input signals associated with / corresponding to / including known / established industry standards and regulations, and another one or more devices 104 may be configured to generate one or more input signals that may include / associated with / correspond to user requirements.

[0087] The communication network 106 may correspond to, for example, an Internet communication network, a wired communication network, a wireless communication network, or any combination thereof. Communication via the communication network 106 (i.e., communication between (one or more) devices 102 and (one or more) apparatuses 104) may be by one or both of wired communication and wireless communication.

[0088] The above-mentioned example background will now be discussed in more detail based on a first example scenario and a second example scenario according to embodiments of the present disclosure hereinafter.

[0089] According to an embodiment of the present disclosure, a first example scenario may, for example, involve an infotainment system associated with a vehicle. It is expected that the infotainment system may be related to / associated with a control area network (CAN) component of the vehicle. In addition, the infotainment system may be able to provide a wireless connection to the Internet / cloud service, which may be a potentially huge attack surface exposure for malicious adversaries. It is expected that the (one or more) security goals and / or (one or more) user requirements associated with the infotainment system may be based on / correspond to multiple categories. In a specific example, the (one or more) security goals and / or (one or more) user requirements associated with the infotainment system may be based on / correspond to five categories, namely "container", "encryption", "separation", "application source" and "remotely connected application" (e.g., "remotely connected application"). It is expected that for each category (e.g., for each category of (one or more) security goals / user requirements), it is possible to define / identify / extract one or more security metrics (e.g., by means of a feature selection-based process as previously discussed) based on (one or more) security requirements (e.g., (one or more) user requirements from one or more users such as developers, customers and / or OEM stakeholders).

[0090] For example, with respect to a category such as "separation", a requirement associated with secure development is that the infotainment system will require sufficient (e.g., strong) separation to support different application domains. Therefore, multiple security metrics can be defined / extracted / identified based on such requirements. In a specific example, any one of a first security metric, a second security metric, and a third security metric, or any combination thereof, can be defined / extracted / identified. In a more specific example, a first security metric can relate to privileged separation that can be associated with determining whether protection has been / can be provided for non-privileged applications that cannot obtain access to privileged system resources (e.g., a CAN bus), a second security metric can relate to security domains that can be associated with determining whether specific domains have been / can be defined and assigned to different applications, and a third security metric can relate to container isolation that can be associated with determining whether critical applications have been / can be isolated into containers. For example, (one or more) security metrics can be subjected to the analysis-based processing discussed previously (which can be similar to the evaluation process according to one embodiment of the present disclosure). It is expected that a positive determination (e.g., "yes"), negative determination (e.g., "no"), or uncertain determination (e.g., "unknown" / "not applicable") associated with (one or more) security metrics can be the basis / bases of a multi-dimensional (e.g., multiple perspectives) credibility score, which can include / associated with a "trust" rating supplemented by a "confidence" rating and an "initial expectation" rating.

[0091] In a first general example, with respect to a first security metric, if it is positively determined (e.g., by (one or more) devices 102 by way of analysis-based processing) that protection for non-privileged applications that cannot obtain access to privileged system resources has been / can be provided, then the confidence score may be higher than a negative determination and / or an uncertain determination. Conversely, if it is negatively determined (e.g., by (one or more) devices 102 by way of analysis-based processing) that protection for non-privileged applications that cannot obtain access to privileged system resources has been / can be provided, then the confidence score may be lower than a positive determination and / or an uncertain determination. If there is an uncertain determination as to whether protection for non-privileged applications that cannot obtain access to privileged system resources has been / can be provided (e.g., by (one or more) devices 102 by way of analysis-based processing), then the confidence score may be higher than a negative determination, but the confidence score may be lower than a positive determination. According to an embodiment of the present disclosure, in this manner, for example, a first confidence score may be determined in association with the first security metric (e.g., by (one or more) devices 102 by way of analysis-based processing).

[0092] In a second general example, with respect to the second security metric, if it is positively determined (e.g., by (one or more) devices 102 through an analysis-based process) that a particular domain has / can be defined and assigned to different applications, the confidence score may be higher than a negative determination and / or an uncertain determination. Conversely, if it is negatively determined (e.g., by (one or more) devices 102 through an analysis-based process) that a particular domain has / can be defined and assigned to different applications, the confidence score may be lower than a positive determination and / or an uncertain determination. If there is an uncertain determination as to whether a particular domain has / can be defined and assigned to different applications (e.g., by (one or more) devices 102 through an analysis-based process), the confidence score may be higher than a negative determination, but the confidence score may be lower than a positive determination. According to an embodiment of the present disclosure, in this manner, for example, a second confidence score may be determined (e.g., by (one or more) devices 102 through an analysis-based process) in association with the second security metric.

[0093] In a third general example, with respect to a third security metric, if it is positively determined (e.g., by (one or more) devices 102 through an analysis-based process) that a critical application has / can be isolated into a container, the confidence score may be higher than a negative determination and / or an uncertain determination. Conversely, if it is negatively determined (e.g., by (one or more) devices 102 through an analysis-based process) that a critical application has / can be isolated into a container, the confidence score may be lower than a positive determination and / or an uncertain determination. If there is an uncertain determination as to whether a critical application has / can be isolated into a container (e.g., by (one or more) devices 102 through an analysis-based process), the confidence score may be higher than a negative determination, but the confidence score may be lower than a positive determination. According to an embodiment of the present disclosure, in this manner, for example, a third confidence score may be determined (e.g., by (one or more) devices 102 through an analysis-based process) in association with the third security metric.

[0094] In the context of the first, second, and third general examples described above, a positive determination may be associated, for example, with a confidence score of 90 out of a maximum score of 100 (e.g., a score of 90%), an uncertain determination may be associated, for example, with a confidence score of 50 out of a maximum score of 100 (e.g., a score of 50%), and a negative determination may be associated, for example, with a confidence score of 10 out of a maximum score of 100 (e.g., a score of 10%). For example, in the context of the first general example, when the (one or more) devices 102 can positively determine (i.e., positively determine) that protection has been / can be provided for unprivileged applications that cannot obtain access to privileged system resources, the (one or more) devices 102 may be configured to generate a first confidence score of 90%. Additionally, in the context of the second general example, when the device 102 can positively determine (i.e., positively determine) that a specific domain has been / can be defined and assigned to different applications, the (one or more) devices 102 may be configured to generate a second confidence score of 90%. Furthermore, in the context of the third general example, when device(s) 102 negatively determines (i.e., negatively determines) that a critical application has / can be isolated into a container, device(s) 102 can be configured to generate a third confidence score of 10%.

[0095] In this regard, in conjunction with the first example scenario, according to an embodiment of the present disclosure, a multidimensional credibility score may be, for example, based on any combination of a first credibility score, a second credibility score, and a third credibility score. In one embodiment, a multidimensional credibility score may be, for example, based on a first credibility score, a second credibility score, and a third credibility score. For example, according to an embodiment of the present disclosure, (one or more) devices 102 may be, for example, configured to (for example, by performing at least one processing task in association with an aggregation-based process) based on a first credibility score (for example, 90%), a second credibility score (for example, 90%), and a third credibility score (such as 10%) aggregation (for example, the calculated average of 90%, 90%, and 10% to derive an aggregate score of 63.33%) to derive / generate a multidimensional credibility score. According to an embodiment of the present disclosure, it is understandable that the previously mentioned total score may, for example, be associated with / correspond to / include a multidimensional credibility score. In one embodiment, the total score may, for example, correspond to a multidimensional credibility score.

[0096] According to an embodiment of the present disclosure, a second example scenario may, for example, involve an over-the-air (OTA) module associated with a vehicle.

[0097] It is expected that software updates associated with the vehicle's software system may be possible by way of OTA. However, there may potentially be concerns about security vulnerabilities associated with (one or more) OTA-based software updates, because connecting an electronic control unit (ECU) to, for example, the Internet may potentially cause the ECU to be potentially vulnerable to a wide range of attacks (e.g., cyber attacks). Vulnerable updates may not only affect the performance of the vehicle in terms of recalls or lost sales, but may also affect the performance of the vehicle in terms of loss of life. According to an embodiment of the present disclosure, the present disclosure contemplates that one or more security goals may be defined in association with the OTA module for the purpose of avoiding / mitigating one or more attack types, which may, for example, include (one or more) unlimited data attacks, (one or more) mixed bundling attacks, (one or more) partial bundling installation attacks, and (one or more) freezing attacks. One or more security requirements may be defined for each attack type.

[0098] For example, in the context of an attack type such as a (one or more) hybrid bundling attack, (one or more) security requirements may be defined as requiring metadata to be broadcast between a primary device (e.g., a primary device such as an OTA module) and one or more secondary devices (e.g., one or more secondary devices such as one or more servers / databases from which (one or more) software updates may be hosted). In order to meet the defined security requirements, one or more security metrics may be defined / extracted / identified. According to an embodiment of the present disclosure, (one or more) security metrics may include any one of a first security metric, a second security metric, and a third security metric, or any combination thereof.

[0099] In a second example scenario, a first security metric may, for example, relate to synchronization of bundled information, wherein the (one or more) devices 102 may be configured to determine (e.g., by way of analysis-based processing) whether the primary device may have the capability to broadcast metadata of the bundled information to all secondary devices. For example, a second security metric may relate to (one or more) trusted communications between the primary device and one or more secondary devices, wherein the (one or more) devices 102 may be configured to determine (e.g., by way of analysis-based processing) whether the (one or more) ECUs authenticate (e.g., between the primary device and one or more secondary devices). A third security metric may, for example, relate to network reliability, wherein the (one or more) devices 102 may be configured to determine (e.g., by way of analysis-based processing) whether a network used to broadcast bundled information may be considered reliable.

[0100] Similar to the first example scenario, in the second example scenario, (one or more) security metrics may be subjected to the previously discussed analysis-based processing (which may be similar to the evaluation process according to one embodiment of the present disclosure). It is expected that a positive determination (e.g., "yes"), a negative determination (e.g., "no"), or an uncertain determination (e.g., "unknown" / "not applicable") related to (one or more) security metrics may be the basis / bases of a multi-dimensional credibility score, which may include / associated with a "trust" rating supplemented with a "confidence" rating and an "initial expectation" rating. In this regard, the (one or more) relevant parts previously discussed in connection with the first example scenario may be appropriately applied similarly to the second example scenario.

[0101] Specifically, the previous discussion related to the first, second, and third general examples in the context of the first example scenario can be similarly applied in the context of the second example scenario. In one example, in the second example scenario, a first credibility score can be determined (e.g., by (one or more) devices 102 through analysis-based processing) in association with a first security metric, for example, based on a positive determination, a negative determination, or an uncertain determination related to synchronization of bundled information. In another example, in the second example scenario, a second credibility score can be determined (e.g., by (one or more) devices 102 through analysis-based processing) in association with a first security metric, for example, based on a positive determination, a negative determination, or an uncertain determination related to (one or more) trusted communications between a primary device and one or more secondary devices. In yet another example, in the second example scenario, a third credibility score can be determined (e.g., by (one or more) devices 102 through analysis-based processing) in association with a third security metric, for example, based on a positive determination, a negative determination, or an uncertain determination related to network reliability.

[0102] According to an embodiment of the present disclosure, in a similar manner as discussed with reference to the first example scenario, in the second example scenario, a multidimensional credibility score (e.g., which may be associated with / correspond to / include the previously mentioned total score) may be based, for example, on any combination of the first credibility score, the second credibility score, and the third credibility score.

[0103] According to embodiments of the present invention, it is expected that at least one measurable credibility evaluation result (i.e., credibility assessment) can be facilitated in the above manner. Specifically, it is understandable that, according to embodiments of the present invention, the above credibility score and / or total score can be, for example, with at least one measurable credibility evaluation result.

[0104] According to embodiments of the present disclosure, it is expected that facilitating measurable credibility evaluation results can, for example, facilitate a quantifiable overview of a vehicle-based software system during the life cycle of, for example, a vehicle (e.g., a car). Such a quantifiable overview can, for example, be useful to, for example, interested parties (e.g., (one or more) developers, (one or more) software architects, (one or more) system architects, and / or (one or more) security and privacy managers). For example, identifying security metrics associated with the credibility of a vehicle-based software system can potentially generate one or more quantitative scores associated with one or more security risks during the development and / or deployment phases, which provides a brief and / or intuitive security evaluation for interested parties (e.g., (one or more) developers and / or (one or more) other stakeholders). It is expected that according to embodiments of the present disclosure, credibility evaluations can, for example, be communicated via an interactive dashboard (e.g., an electronic dashboard module), which can, for example, facilitate the traceability of security defects in software modules / platforms associated with vehicle-based software systems.

[0105] Furthermore, it is contemplated that by facilitating measurable credibility evaluation results (i.e., credibility assessments), the cybersecurity health of automotive-based software systems can be evaluated before the vehicle is on the road. By doing so, the number of product (e.g., vehicle) recalls due to software defects can potentially be at least reduced. Additionally, software defects can be addressed during the development lifecycle phase. In this regard, it is understood that according to embodiments of the present disclosure, the overall software product development can, for example, be made more efficient and / or maintenance costs can be potentially reduced.

[0106] According to embodiments of the present disclosure, it is expected that facilitating measurable credibility evaluation results (i.e., credibility assessments) can be used, for example, to evaluate safety risks and generate credibility reports that can build a software credibility database for risk assessment during the development phase. It is further expected that according to embodiments of the present disclosure (e.g., in conjunction with the after-sales phase), facilitating measurable credibility evaluation results (i.e., credibility assessments) can be used, for example, to assign one or more credibility scores of automotive software modules associated with an automotive-based software system to one or more relevant stakeholders (e.g., (one or more) users of (one or more) vehicles and / or (one or more) software architects) in order to, for example, improve the safety level.

[0107] The following will refer to Figure 2 The above-described device(s) 102 are discussed in greater detail.

[0108] refer to Figure 2 , device 102 is shown in greater detail in the context of example embodiment 200 , according to an embodiment of the present disclosure.

[0109] In example embodiment 200, device 102 may correspond to electronic module 200a, which may, for example, be capable of performing one or more processing tasks associated with facilitating at least one measurable credibility evaluation result. According to embodiments of the present disclosure, the measurable credibility evaluation result(s) may, for example, be based on one or both of the previously discussed credibility scores and the previously discussed total scores.

[0110] According to an embodiment of the present disclosure, the electronic module 200a may, for example, correspond to a mobile device or an installable electronic module (e.g., an electronic dashboard module) that can be carried by a user into a vehicle or an existing electronic control unit or ECU connected to an existing vehicle network with high-performance computing capabilities.

[0111] The electronic module 200a may, for example, include a housing 200b. In addition, the electronic module 200a may, for example, carry any one of the first module 202, the second module 204, the third module 206, or any combination thereof.

[0112] In one embodiment, according to an embodiment of the present disclosure, the electronic module 200a can carry the first module 202, the second module 204 and / or the third module 206. In a specific example, the electronic module 200a can carry the first module 202, the second module 204 and the third module 206.

[0113] In this regard, it is understood that, in one embodiment, the housing 200b may be shaped and sized to carry any one or any combination of the first module 202, the second module 204, and the third module 206.

[0114] The first module 202 may be coupled to one or both of the second module 204 and the third module 206. The second module 204 may be coupled to one or both of the first module 202 and the third module 206. The third module 206 may be coupled to one or both of the first module 202 and the second module 204. In one example, according to an embodiment of the present disclosure, the first module 202 may be coupled to the second module 204, and the second module 204 may be coupled to the third module 206. The coupling between the first module 202, the second module 204, and / or the third module 206 may be, for example, by one or both of wired coupling and wireless coupling. According to an embodiment of the present disclosure, each of the first module 202, the second module 204, and the third module 206 may correspond to one or both of a hardware-based module and a software-based module.

[0115] In one example, the first module 202 may correspond to a hardware-based receiver that may be configured to receive one or more input signals.

[0116] The second module 204 may correspond, for example, to a hardware-based processor that may be configured to perform one or more processing tasks associated with any one or any combination of the following:

[0117] Feature selection based processing

[0118] Analysis-based processing

[0119] Aggregation-based processing

[0120] Specifically, according to an embodiment of the present disclosure, the second module 204 may be configured, for example, to process (one or more) received input signals by feature selection-based processing, analysis-based processing and / or aggregation-based processing so as to generate / derive one or more output signals.

[0121] In one example, according to an embodiment of the present disclosure, the third module 206 may correspond to a hardware-based transmitter, which may be configured to transmit (one or more) output signals from the electronic module 200a. In another example, the third module 206 may correspond to a hardware-based display unit, which may be configured to display (one or more) output signals so that (one or more) output signals may be visually perceptible (e.g., by one or more users). According to an embodiment of the present disclosure, (one or more) output signals may, for example, correspond to / include / indicate one or both of (one or more) credibility scores and total scores. In addition, (one or more) output signals may, for example, be transmitted from the electronic module 200a to one or more devices and / or one or more other devices that are capable of, for example, displaying (one or more) output signals for visual consumption (i.e., visually perceptible by one or more users).

[0122] The present disclosure contemplates the possibility that the first and second modules 202 / 204 may be integrated software-hardware-based modules (e.g., electronic components that may carry software programs / algorithms associated with receiving and processing functions / electronic modules that are programmed to perform receiving and processing functions). The present disclosure further contemplates the possibility that the first and third modules 202 / 206 may be integrated software-hardware-based modules (e.g., electronic components that may carry software programs / algorithms associated with receiving and transmitting functions / electronic modules that are programmed to perform receiving and transmitting functions). The present disclosure further contemplates the possibility that the first and third modules 202 / 206 may be integrated hardware modules (e.g., hardware-based transceivers) that are capable of performing receiving and transmitting functions.

[0123] In view of the foregoing, it is to be understood that, according to embodiments of the present disclosure, the present disclosure generally contemplates a device 102 suitable for facilitating a credibility assessment associated with, for example, a vehicle (not shown). The vehicle may, for example, be associated with a system infrastructure (e.g., a software-based infrastructure). For example, according to embodiments of the present disclosure, the system infrastructure associated with the vehicle may correspond to the previously mentioned automotive-based software system. Further, according to embodiments of the present disclosure, the credibility assessment may, for example, be based on one or both of at least one credibility score and a total score. It is contemplated that according to embodiments of the present disclosure, (one or more) credibility scores and / or total scores may, for example, be indicative assessments of credibility associated with the system infrastructure. In one embodiment, the device 102 may be suitable for facilitating a credibility assessment associated with an automotive software system.

[0124] In one embodiment, the device 102 may include a first module 202 and a second module 204. The first module 202 may be coupled to the second module 204.

[0125] The first module 202 may be configured to receive at least one input signal, and the second module 204 may be configured to process the input signal(s) in such a manner as to generate one or more output signals.

[0126] According to an embodiment of the present disclosure, (one or more) input signals may be associated with, for example, one or both of at least one user requirement and at least one security goal (i.e., at least one user requirement and / or at least one security goal; at least one of at least one user requirement and at least one security goal).

[0127] Furthermore, in one embodiment, the input signal(s) may be processed by:

[0128] Identifying (eg, by way of a feature selection based process) at least one security metric associated with at least one security requirement. According to embodiments of the present disclosure, the security requirement(s) may be based on, for example, at least one user requirement and / or at least one security goal.

[0129] Determining (e.g., by way of analysis-based processing) a positive determination, a negative determination, or an indeterminate determination (i.e., one of a positive determination, a negative determination, and an indeterminate determination) regarding satisfaction of a security metric with respect to at least one security goal and / or at least one user requirement

[0130] • deriving (eg, by way of an analysis-based process) at least one confidence score based on the positive determination, the negative determination, or the inconclusive determination (ie, one of the positive determination, the negative determination, and the inconclusive determination).

[0131] In one embodiment, the output signal(s) may be based on the credibility score(s), for example.Furthermore, according to embodiments of the present disclosure, the output signal(s) may indicate a credibility assessment.

[0132] In one embodiment, the second module 204 may be configured, for example, to process the input signal(s) by identifying a plurality of security metrics. Each security metric (of the plurality of security metrics) may be associated, for example, with at least one security goal and / or at least one user requirement. According to an embodiment of the present disclosure, a credibility score may be derived in association with each security metric, for example, based on a positive determination, a negative determination, or an uncertain determination (i.e., one of a positive determination, a negative determination, and an uncertain determination) of satisfaction of the security metric with respect to the security goal and / or the user requirement.

[0133] In one embodiment, the second module 204 may, for example, be configured to derive a plurality of confidence scores based on a plurality of security metrics.

[0134] In one embodiment, the second module 204 may be configured to aggregate multiple credibility scores to generate a total score. In addition, according to an embodiment of the present disclosure, the credibility evaluation may be based on the total score, for example.

[0135] In one embodiment, the device 102 may also include a third module 206, which may, for example, be configured to transmit (one or more) output signals to facilitate one or both of visual perception and auditory perception (i.e., visual perception and / or auditory perception, at least one of visual perception and auditory perception) of one or both of (one or more) credibility scores and the total score (i.e., (one or more) credibility scores and / or the total score; at least one of (one or more) credibility scores and the total score).

[0136] According to embodiments of the present invention, it is expected that at least one measurable credibility evaluation result (i.e., credibility assessment) can be facilitated in the above manner. Specifically, it is understandable that, according to embodiments of the present invention, the above credibility score and / or total score can be, for example, with at least one measurable credibility evaluation result.

[0137] According to embodiments of the present disclosure, it is expected that facilitating measurable credibility evaluation results can, for example, facilitate a quantifiable overview of a vehicle-based software system during the life cycle of, for example, a vehicle (e.g., a car). Such a quantifiable overview can, for example, be useful to, for example, interested parties (e.g., (one or more) developers, (one or more) software architects, (one or more) system architects, and / or (one or more) security and privacy managers). For example, identifying security metrics associated with the credibility of a vehicle-based software system can potentially generate one or more quantitative scores associated with one or more security risks during the development and / or deployment phases, which provides a brief and / or intuitive security evaluation for interested parties (e.g., (one or more) developers and / or (one or more) other stakeholders). It is expected that according to embodiments of the present disclosure, credibility evaluations can, for example, be communicated via an interactive dashboard (e.g., an electronic dashboard module), which can, for example, facilitate the traceability of security defects in software modules / platforms associated with vehicle-based software systems.

[0138] Furthermore, it is contemplated that by facilitating measurable credibility evaluation results (i.e., credibility assessments), the cybersecurity health of automotive-based software systems can be evaluated before the vehicle is on the road. By doing so, the number of product (e.g., vehicle) recalls due to software defects can potentially be at least reduced. Additionally, software defects can be addressed during the development lifecycle phase. In this regard, it is understood that according to embodiments of the present disclosure, the overall software product development can, for example, be made more efficient and / or maintenance costs can be potentially reduced.

[0139] According to embodiments of the present disclosure, it is expected that facilitating measurable credibility evaluation results (i.e., credibility assessments) can be used, for example, to evaluate safety risks and generate credibility reports that can build a software credibility database for risk assessment during the development phase. It is further expected that according to embodiments of the present disclosure (e.g., in conjunction with the after-sales phase), facilitating measurable credibility evaluation results (i.e., credibility assessments) can be used, for example, to assign one or more credibility scores of automotive software modules associated with an automotive-based software system to one or more relevant stakeholders (e.g., (one or more) users of (one or more) vehicles and / or (one or more) software architects) in order to, for example, improve the safety level.

[0140] The (one or more) above-mentioned advantageous aspects of the device 102 of the present disclosure may also be (all) similarly applied to the (one or more) aspects of the following processing methods of the present disclosure. Similarly, all the (one or more) below-mentioned advantageous aspects of the processing methods of the present disclosure may also be (all) similarly applied to the (one or more) aspects of the above-mentioned device 102 of the present disclosure. It should be understood that these descriptions are similarly applied to the previously discussed system 100 of the present disclosure.

[0141] refer to Figure 3 , showing a processing method associated with the system 100 according to an embodiment of the present disclosure. According to an embodiment of the present disclosure, the processing method 300 may be suitable for facilitating a measurable credibility evaluation result, for example.

[0142] According to an embodiment of the present disclosure, the processing method 300 may, for example, include any one of an input step 302 , an analysis step 304 , and an output step 306 , or any combination thereof.

[0143] In one embodiment, the processing method 300 may include an input step 302, an analysis step 304, and an output step 306. In another embodiment, the processing method 300 may include an input step 302 and an analysis step 304. In yet another embodiment, the processing method 300 may include an analysis step 304 and an output step 306. In yet another embodiment, the processing method 300 may include an analysis step 304.

[0144] With respect to the input step 302 , one or more input signals may be received, for example, the input signal(s) may be received by the device(s) 102 for processing according to an embodiment of the present disclosure.

[0145] With respect to the analysis step 304, the input signal(s) may be processed in a manner to generate / derive one or more output signals. For example, the device(s) 102 may process the received input signal(s) by feature selection-based processing, analysis-based processing, and / or aggregation-based processing to generate the output signal(s).

[0146] With respect to the output step 306, at least one output signal may be transmitted. For example, according to an embodiment of the present disclosure, (one or more) output signals may correspond to / include / associated with at least one credibility score and / or total score. In one example, (one or more) output signals may be communicated in a manner such that (one or more) credibility scores and / or total scores may be visually perceptible and auditorily perceptible (i.e., visually perceptible and / or auditorily perceptible) in one or both. In another example, (one or more) output signals may be communicated with one or more other devices 102 and / or one or more devices / other devices 104. (One or more) output signals may be communicated, for example, from at least one device 102.

[0147] The present disclosure also contemplates a computer program (not shown) that may include instructions that, when executed by a computer (not shown), cause the computer to perform the input step 302, the analysis step 304, and / or the output step 306 as discussed with reference to the processing method 300. For example, in one embodiment, when the instructions are executed by the computer, the analysis step 304 may be performed.

[0148] The present disclosure further contemplates a computer-readable storage medium (not shown) having stored therein data representing software executable by a computer (not shown), the software including instructions that, when executed by the computer, perform the input step 302, the analysis step 304, and / or the output step 306 as discussed with reference to the processing method 300. For example, in one embodiment, the analysis step 304 may be performed when the instructions are executed by the computer.

[0149] In view of the foregoing, it is to be understood that the present disclosure generally contemplates a processing method 300 according to an embodiment of the present disclosure that may be, for example, suitable for facilitating a credibility assessment. According to an embodiment of the present disclosure, a credibility assessment may be associated with, for example, a vehicle (not shown). A vehicle may, for example, be associated with a system infrastructure (e.g., a software-based infrastructure). For example, according to an embodiment of the present disclosure, a system infrastructure associated with a vehicle may correspond to the previously mentioned automotive-based software system. Further, according to an embodiment of the present disclosure, a credibility assessment may, for example, be based on one or both of at least one credibility score and a total score. It is contemplated that according to an embodiment of the present disclosure, (one or more) credibility scores and / or a total score may, for example, be an indicative assessment of credibility associated with a system infrastructure. In one embodiment, the processing method 300 may, for example, be suitable for facilitating a credibility assessment associated with an automotive software system.

[0150] According to an embodiment of the present disclosure, the processing method 300 may, for example, include an analyzing step 304 .

[0151] In one embodiment, analyzing step 304 may, for example, include processing at least one input signal to generate at least one output signal.

[0152] The input signal(s) may, for example, be associated with / include / indicate one or both of at least one user requirement and at least one security goal (i.e., at least one user requirement and / or at least one security goal; at least one of at least one user requirement and at least one security goal).

[0153] In one embodiment, the input signal(s) may be processed, for example, by:

[0154] At least one security metric associated with at least one security requirement is identified (e.g., by means of a feature selection-based process). According to an embodiment of the present disclosure, the security requirement(s) may be based on, for example, security goal(s) and / or user requirement(s).

[0155] Determining (e.g., by way of analysis-based processing) a positive determination, a negative determination, or an indeterminate determination (i.e., one of a positive determination, a negative determination, and an indeterminate determination) regarding satisfaction of a security metric with respect to at least one security goal and / or at least one user requirement

[0156] At least one confidence score is derived (eg, by way of an analysis-based process) based on the positive determination, the negative determination, or the inconclusive determination (ie, one of the positive determination, the negative determination, and the inconclusive determination).

[0157] In one embodiment, the output signal(s) may be based on the confidence score(s), for example.

[0158] In one embodiment, the output signal(s) may, for example, be indicative of a confidence rating.

[0159] In one embodiment, the input signal(s) may be processed, for example, by identifying a plurality of security metrics. Each of the plurality of security metrics may be associated, for example, with at least one security goal and / or at least one user requirement.

[0160] In one embodiment, a confidence score may be derived in association with each security metric, for example based on a positive determination, a negative determination, or an uncertain determination (i.e., one of a positive determination, a negative determination, and an uncertain determination) regarding satisfaction of the security metric with respect to security goals and / or user requirements.

[0161] In one embodiment, multiple confidence scores may be derived, for example, based on multiple security metrics.

[0162] In one embodiment, processing method 300 may, for example, further include aggregating multiple credibility scores to generate an overall score.

[0163] In one embodiment, the credibility rating may be based on an overall score, for example.

[0164] According to embodiments of the present invention, it is expected that at least one measurable credibility evaluation result (i.e., credibility assessment) can be facilitated in the above manner. Specifically, it is understandable that, according to embodiments of the present invention, the above credibility score and / or total score can be, for example, with at least one measurable credibility evaluation result.

[0165] According to embodiments of the present disclosure, it is expected that facilitating measurable credibility evaluation results can, for example, facilitate a quantifiable overview of a vehicle-based software system during the life cycle of, for example, a vehicle (e.g., a car). Such a quantifiable overview can, for example, be useful to, for example, interested parties (e.g., (one or more) developers, (one or more) software architects, (one or more) system architects, and / or (one or more) security and privacy managers). For example, identifying security metrics associated with the credibility of a vehicle-based software system can potentially generate one or more quantitative scores associated with one or more security risks during the development and / or deployment phases, which provides a brief and / or intuitive security evaluation for interested parties (e.g., (one or more) developers and / or (one or more) other stakeholders). It is expected that according to embodiments of the present disclosure, credibility evaluations can, for example, be communicated via an interactive dashboard (e.g., an electronic dashboard module), which can, for example, facilitate the traceability of security defects in software modules / platforms associated with vehicle-based software systems.

[0166] Furthermore, it is contemplated that by facilitating measurable credibility evaluation results (i.e., credibility assessments), the cybersecurity health of automotive-based software systems can be evaluated before the vehicle is on the road. By doing so, the number of product (e.g., vehicle) recalls due to software defects can potentially be at least reduced. Additionally, software defects can be addressed during the development lifecycle phase. In this regard, it is understood that according to embodiments of the present disclosure, the overall software product development can, for example, be made more efficient and / or maintenance costs can be potentially reduced.

[0167] According to embodiments of the present disclosure, it is expected that facilitating measurable credibility evaluation results (i.e., credibility assessments) can be used, for example, to evaluate safety risks and generate credibility reports that can build a software credibility database for risk assessment during the development phase. It is further expected that according to embodiments of the present disclosure (e.g., in conjunction with the after-sales phase), facilitating measurable credibility evaluation results (i.e., credibility assessments) can be used, for example, to assign one or more credibility scores of automotive software modules associated with an automotive-based software system to one or more relevant stakeholders (e.g., (one or more) users of (one or more) vehicles and / or (one or more) software architects) in order to, for example, improve the safety level.

[0168] It should be understood that the above-mentioned embodiments may be combined in any appropriate manner (for example, one or more embodiments as discussed in the "Detailed Description" section may be combined with one or more embodiments as described in the "Summary of the Invention" section).

[0169] Those skilled in the art will also appreciate that variations and combinations (not substitutions or replacements) of the above-described embodiments may be combined to form further embodiments.

[0170] In one example, the communication network 106 may be omitted. The communication (i.e., the communication between the (one or more) devices 102 and the (one or more) apparatuses 104) may be by direct coupling. Such direct coupling may be by one or both of wired coupling and wireless coupling.

[0171] In another example, the example context as previously discussed may be associated with a vehicle. The present disclosure contemplates that other example contexts may be possible. For example, another example context may be associated with a consumer appliance (e.g., a laptop or a smart TV).

[0172] In yet another example, it is previously contemplated that the third module 206 may correspond, for example, to a hardware-based display unit that may be configured to display (one or more) output signals so that (one or more) output signals may be visually perceptible (e.g., by one or more users). The present disclosure contemplates that the third module 206 may correspond, for example, to a hardware-based audio unit that may be configured to output the output signals audibly so that the output signals may be audibly perceptible (e.g., by one or more users).

[0173] In yet another example, the third module 206 may, for example, correspond to a hardware-based audio display unit, which may be configured to transmit (one or more) output signals so that the (one or more) output signals may be auditorily and visually perceptible (e.g., by one or more users).

[0174] In the above manner, various embodiments of the present disclosure are described to address at least one of the above disadvantages. These embodiments are intended to be covered by the appended claims, and are not limited to the specific forms or arrangements of the components described above, and it is obvious to those skilled in the art that, in light of this disclosure, many changes and / or modifications may be made that are also intended to be covered by the appended claims.

Claims

1. A device (102) adapted for use in facilitating a credibility assessment associated with an automotive software system, the device (102) comprising: A first module (202) can be configured to receive at least one input signal associated with at least one of: At least one user requirement, and At least one safety goal; A second module (204), the second module (204) being coupled to the first module (202), the second module (204) being configurable to process the at least one input signal in a manner so as to generate at least one output signal, the at least one input signal being processed by: identifying at least one security metric associated with at least one security requirement, the at least one security requirement being based on at least one of the at least one user requirement and the at least one security goal, determining one of a positive determination, a negative determination, and an indeterminate determination of a user requirement, the positive determination, the negative determination, and the indeterminate determination being related to satisfaction of a security metric with respect to at least one of the at least one security goal and the at least one user requirement, deriving at least one confidence score based on one of the positive determination, the negative determination, and the uncertain determination, wherein the at least one output signal is based on the at least one confidence score, and The at least one output signal is indicative of a plausibility assessment.

2. The device (102) of claim 1, wherein the second module (204) is configurable to: process the at least one input signal by identifying a plurality of security metrics, Wherein a confidence score can be derived in association with each security metric based on one of a user requirement positive determination, a negative determination, and an uncertain determination related to satisfaction of the security metric with respect to at least one of a security goal and a user requirement.

3. The device (102) of any one of the preceding claims, wherein the second module (204) is further configurable to derive a plurality of confidence scores based on a plurality of security metrics.

4. The device (102) according to any one of the preceding claims, The second module (204) can also be configured to: aggregate the plurality of credibility scores to generate a total score, and The credibility evaluation is based on the total score.

5. The device (102) of any one of the preceding claims, further comprising a third module (206) configurable to transmit the at least one output signal to facilitate at least one of a visual perception and an auditory perception of at least one of: the at least one credibility score, and The total score.

6. A processing method (300) suitable for facilitating a credibility assessment associated with an automotive software system, the processing method (300) comprising: An analysis step (304), the analysis step (304) comprising processing, by a device according to any one of the preceding claims, at least one input signal to generate at least one output signal, the at least one input signal being associated with at least one of: At least one user requirement, and At least one security goal, The at least one input signal can be processed in the following manner: identifying at least one security metric associated with at least one security requirement based on at least one of the at least one user requirement and the at least one security goal, determining one of a positive determination, a negative determination, and an indeterminate determination of a user requirement, the one of the positive determination, the negative determination, and the indeterminate determination being related to satisfaction of a security metric with respect to at least one of the at least one user requirement and the at least one security goal, deriving at least one confidence score based on one of the positive determination, the negative determination, and the uncertain determination, wherein the at least one output signal is based on the at least one confidence score, and The at least one output signal is indicative of a plausibility assessment.

7. The processing method (300) according to claim 6, wherein the at least one input signal is capable of being processed in a manner that identifies a plurality of security metrics, Wherein a confidence score can be derived in association with each security metric based on one of a user requirement positive determination, a negative determination, and an uncertain determination related to satisfaction of the security metric with respect to at least one of a security goal and a user requirement.

8. The processing method (300) according to any one of claims 6 or 7, wherein a plurality of confidence scores can be derived based on a plurality of security metrics, The processing method (300) further comprises: aggregating the plurality of credibility scores to generate an overall score, and The credibility evaluation is based on the total score.

9. A computer program comprising instructions which, when executed by a computer, cause the computer to perform the analyzing step (304) of the processing method (300) according to any one of claims 6 to 8.

10. A computer-readable storage medium having data representing software executable by a computer stored therein, the software comprising instructions which, when executed by the computer, perform the analysis step (304) of the processing method (300) according to any one of claims 6 to 8.

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