Determine the electric field distribution

Abstract

In one example, a method includes receiving an indication of an electrical parameter associated with at least a portion of a computing device. The method also includes determining whether the indication indicates an expected electric field distribution associated with a specified hardware configuration of the computing device.

Description

Background Art

[0001] A computing device may be modified during various stages of the manufacturing process or by an end user. Certain modifications to a computing device may cause the computing device to have different functionality than it had prior to the modification. BRIEF DESCRIPTION OF THE DRAWINGS

[0002] Non-limiting examples will now be described with reference to the accompanying drawings, in which:

[0003] Figure 1 is a flow chart of an example method of determining certain information about a computing device;

[0004] Figure 2 is a simplified schematic diagram of an example system for implementing certain methods;

[0005] Figure 3 is a flow chart of an example method of determining certain information about a computing device;

[0006] Figure 4 is a simplified schematic diagram of an example apparatus for implementing certain methods;

[0007] Figure 5 is a simplified schematic diagram of an example apparatus for implementing certain methods;

[0008] Figure 6 are simplified schematic diagrams of example apparatus for implementing certain methods; and

[0009] Figure 7 is a simplified schematic diagram of an example machine-readable medium associated with a processor. DETAILED DESCRIPTION

[0010] There may be situations where the components installed in a computing device are different from the expected components of the computing device. For example, a computing device may be tampered with during the manufacturing process, before distribution to an end user, or even after an end user receives the computing device.

[0011] There may be various opportunities for entities to tamper with computing devices or provide compromised or unauthorized components to be installed in computing devices during the supply chain or after distribution to end users. For example, on a production line, compromised components may be installed on computing devices intentionally or unintentionally. In another example, attacks on computing devices may be conducted in untrusted environments, such as during shipment from a manufacturing facility to an end user, or even when the computing device is unattended (e.g., not in the care of the end user).

[0012] Figure 1A flow chart of a method 100 of determining certain information about a computing device is depicted, which may be a computer-implemented method. The method 100 may be implemented by an entity such as an end user, a manufacturer, or other verification entity. The method 100 may be implemented using, for example, processing circuitry of a personal computer, a dedicated processing device, a server, a cloud-based service, or any other computing device.

[0013] The method 100 includes, at block 102 , receiving an indication of an electrical parameter associated with at least a portion of a computing device.

[0014] In some examples, an electrical parameter may be measured at a specified location associated with a computing device. In some examples, the electrical parameter may include quantities such as capacitance, inductance, impedance, etc. The indication may include or indicate an electrical value such as a voltage, charge, and / or current value. Measurement of the electrical value (e.g., over time) may be used to determine the electrical parameter.

[0015] In some examples, a component (e.g., a capacitor, an inductor, a resistor, etc.) may be associated with an electrical parameter (e.g., capacitance, inductance, impedance, etc.). The electrical parameter may vary with the electric field surrounding the component and / or the electric field generated by the component itself. A component may be associated with an electrical value (e.g., a voltage and / or current measured across the component, etc.). Thus, the electrical value may be a measurable quantity (associated with the component) that can be used to determine the electrical parameter (e.g., capacitance, inductance, impedance, etc.).

[0016] In some examples, measuring the electrical value may include measuring at least one of: voltage, current, evolution of voltage and / or current over a specified time, charge / discharge time, resonant frequency, and / or voltage change of a polarized component (e.g., a capacitor), etc.

[0017] In some examples, receiving an indication of an electrical parameter may include receiving a value (or an indication thereof) of the electrical parameter (e.g., a capacitance value, an inductance value, an impedance value, etc.). In some examples, receiving an indication of the electrical parameter may include receiving an electrical value (or an indication thereof) that may be used to determine the value of the electrical parameter.

[0018] In some examples, the electrical parameter may be associated with a component of the computing device itself (e.g., the component may be part of a circuit module of the computing device). In some examples, the electrical parameter may be associated with a sensor or other device used to obtain certain information about the computing device (e.g., the component may not be part of a circuit module of the computing device; instead, the component may be part of a sensor or other device).

[0019] As will be explained in greater detail below, the received indication of the electrical parameter may be used to determine or otherwise infer certain information about the computing device.

[0020] The method 100 includes determining, using a processing circuit module, at block 104 whether the indication indicates an expected electric field distribution associated with a specified hardware configuration of the computing device.

[0021] As will be explained in more detail below, a given hardware configuration of a computing device may affect the electric field distribution. Thus, in some cases, changes in the hardware configuration of a computing device (e.g., changes in the number, location, type, and / or distribution of electronic components in the computing device) may affect the electric field distribution.

[0022] In some cases, changes in the electric field distribution can affect the electrical parameter. For example, if a component (associated with the electrical parameter) is at a certain location relative to the computing device, changes in the hardware configuration of the computing device can affect the electric field observed by the component. In other words, if the component observes a particular electric field at its location, the value of the electrical parameter can be affected by the electric field at its location.

[0023] The electric field observed at a certain location may depend on the hardware configuration of the computing device. Therefore, the electric field distribution may depend on the hardware configuration of the computing device.

[0024] Since the electrical parameters observed at the component may be affected by any changes in the electric field (which may depend on the hardware configuration), the electrical parameters associated with the component may be affected by the hardware configuration. Measurements of the electrical parameters at different locations relative to the computing device may indicate the electric field distribution associated with the hardware configuration of the computing device.

[0025] The indication received in block 102 may be used to determine whether the electric field at a certain location indicates an expected electric field distribution. For example, for a specified hardware configuration, it may be expected that a specific electric field should be observed at a specific location. If the specific electric field is observed at the specific location, then the measurement of the electrical parameter at the location may indicate that the electric field distribution is as expected. Further measurements of the electrical parameter at other locations may be used to provide confirmation that the electric field distribution is as expected. In this case, it may be determined that the computing device has a specified (e.g., expected) hardware configuration.

[0026] However, if the measurement of the electrical parameter at the location indicates a different electric field distribution (e.g., an unexpected electric field distribution), this may indicate that the computing device does not have the specified hardware configuration. For example, if the hardware configuration is not as expected, the electric field distribution may be different than expected. In other words, the received indication of the electrical parameter may indicate that the hardware configuration of the computing device being tested is different from the specified (e.g., expected) hardware configuration of the computing device.

[0027] Thus, in some examples, indications of electrical parameters may be used to determine whether a computing device under test has a specified hardware configuration.

[0028] In some examples, a specified hardware configuration of a computing device may refer to the number, type, and / or distribution of hardware (e.g., electronic hardware) components used in the computing device. Components (e.g., hardware components) of a computing device may affect the distribution of an electric field. In some examples, the components themselves may generate an electric field, which may contribute to the overall electric field distribution associated with the computing device. In some examples, a component may affect an electric field generated by another component (e.g., another component of the computing device or another component of another device such as a sensor). Examples of hardware components include, for example, electrical conductors, resistors, capacitors, inductors, logic gates, microprocessors, and / or any other component capable of generating an electric field or affecting an electric field. Depending on whether the computing device is powered on or off, the hardware components may affect the electric field in different ways.

[0029] In some examples, a circuit module of a computing device may generate an electric field, for example, due to the distribution of current and / or charge flowing through the circuit module throughout the computing device. In some examples, a circuit module of any other component or device (such as a sensor described below) may generate an electric field. In some examples, a circuit module of a computing device and / or a circuit module of any other component or device may affect the electric field distribution associated with a specified hardware configuration of the computing device. The number, type, and / or distribution of components (including electrical conductors) of a computing device may affect the electric field distribution associated with a specified hardware configuration of the computing device. A circuit module of a computing device and / or an electric field generated by such a circuit module may affect a specific electrical parameter observed at a specific location.

[0030] In some examples, the location may refer to a component of the computing device itself. In some examples, the location may refer to a component of another device, such as a sensor that is not part of a circuit module of the computing device itself.

[0031] Determination of electrical parameters at a particular location associated with a computing device may indicate an electric field distribution of the computing device. In some examples, the electric field distribution may include electric field contributions due to at least one of: a circuit module (e.g., including hardware components) of the computing device and a circuit module of any other component or device (e.g., a sensor) proximate to the computing device.

[0032] Since the number, type, and / or distribution of components of a computing device can affect the electric field distribution, the electric field distribution can indicate the types of components and / or the distribution of these components in the computing device. If the computing device is tampered with (e.g., if a hardware change occurs), the tampering can affect the electric field distribution. For example, if any component of the computing device is new or damaged in some way, the component can affect (e.g., modify) the electric field distribution. This change in the electric field distribution can be detected by an indication of an electrical parameter. An entity such as a device manufacturer, an end user, or other verification entity can use the indication to determine whether the computing device has been tampered with (e.g., if the hardware configuration of the computing device is not as expected).

[0033] In some examples, method 100 may enable determination of whether a computing device has been tampered with. Tampering may take various forms, such as: adding a damaged component, modifying an existing component, replacing an existing component with a damaged component. Thus, in some examples, method 100 may enable determination of whether a hardware change of a computing device has occurred.

[0034] The method 100 may allow a verification entity, such as an end user or device manufacturer, to be assured that the provenance and / or integrity of a computing device is as expected. The method 100 may facilitate detection of tampering attempts (e.g., in real time or after the event). Thus, another tampering attempt indicator (e.g., on the device packaging) may not be used, or the method 100 may be used with the other tampering attempt indicator to provide additional assurance to the verification entity.

[0035] Figure 2 An example system 200 is shown for implementing certain methods described herein (e.g., method 100). In this example, system 200 enables determination of certain information about a computing device 202 (e.g., a printed circuit assembly (PCA)). For example, system 200 may enable determination of whether computing device 202 has been tampered with (e.g., whether a hardware change of computing device 202 has occurred).

[0036] The example system 200 includes a sensor 204, which in this example includes a capacitor array 206 for measuring an electrical parameter (in this example, capacitance) at a specified location associated with a computing device 202. A capacitor 206a of the capacitor array 206 is located at a location associated with the computing device 202. The capacitor 206a may be sensitive to a local electric field (e.g., generated by the capacitor 206a itself and / or generated or otherwise affected by a circuit module of the computing device 206), which may be affected by the number, type, and / or distribution of components in the computing device 202 that are near the capacitor 206a (although in some cases, components that are far from the capacitor 206a may affect the local electric field observed by the capacitor 206a). For example, the capacitance of the capacitor 206a may be affected by the number, type, and / or distribution of components in the computing device 202. Another capacitor 206b of the capacitor array 206 may be affected by the type and distribution of components in the computing device 202.

[0037] In some examples, capacitor array 206 itself may generate an electric field that may be affected by the hardware configuration of computing device 202. In this case, any change to the hardware configuration may be detectable by causing a change in the electric field generated by capacitor array 206 (and thus causing a detectable change in capacitance in at least one of capacitors 206). In some examples, a change in the hardware configuration of computing device 202 may be detectable in the electric field generated by capacitor array 206 (e.g., its operation) (through capacitor array 206). In some examples, a change in the hardware configuration may affect the electric field generated by capacitor array 206. For example, the number, type, and / or distribution of components in computing device 202 may affect the electric field observed by capacitor array 206 (e.g., whether computing device 202 is powered on or off). In some examples, if the computing device is powered on, computing device 202 itself may generate an electric field (e.g., a parasitic electric field) that may affect the electric field observed by capacitor array 206.

[0038] In some cases, a change in capacitance at any capacitor in capacitor array 206 may indicate that computing device 202 has been tampered with. In some cases, a change in capacitance at a combination of capacitors in capacitor array 206 may indicate that computing device 202 has been tampered with. The change in capacitance may be determined based on a change in a measured electrical value (e.g., current, voltage) associated with capacitors 204a, 204b where such a change is observed. Thus, the measured electrical value may provide an indication of an electrical parameter (i.e., capacitance in this example) measured at a specified location associated with computing device 202.

[0039] exist Figure 2, sensor 204 is depicted as being spatially separated from computing device 202 , but sensor 204 may or may not be spatially separated from computing device 202 .

[0040] In some examples, sensor 204 may be provided as a circuit module that is different / separate from the circuit modules of computing device 202 itself (e.g., capacitor array 206 may be provided as part of a different PCA than computing device 202). For example, sensor 204 may be positioned in an appropriate location relative to computing device 202 in order to perform measurements. In another example, sensor 204 may be mounted as part of the same PCA as computing device 202, but using a circuit module that is separate from the circuit modules of interest in computing device 202 (e.g., sensor 204 may be provided as part of a different layer of the PCA). In some examples, sensor 204 may be mounted in situ to perform measurements (e.g., sensor 204 may be permanently mounted with computing device 202, mounted within a package of computing device 202, or combined with a package of computing device 202).

[0041] In some examples, sensor 204 may be provided as part of a circuit module of computing device 202 itself (e.g., capacitor array 206 may be embedded in computing device 202 itself and use the same circuit module as a circuit module of interest of computing device 202). For example, sensor 204 and computing device 202 may share the same platform, e.g., as part of the same PCA (or a layer thereof).

[0042] If the sensor 204 can be installed in situ with the computing device 202, this can provide the ability to provide measurements over a period of time, which can increase the likelihood of detecting tampering attempts (e.g., during manufacturing or even after supply to the end user). These measurements can be performed at any time using any specified schedule to increase the likelihood of detecting any tampering attempts. The verification entity can rely on the measurements provided by the sensor 204 itself, and in some examples, may not use any other dedicated equipment to detect tampering attempts.

[0043] In some examples, sensor 204 may be positionable proximate to computing device 202 (e.g., temporarily positioned by a verification entity) so that measurements are taken while sensor 204 is in place. In some examples, sensor 204 may include a dedicated device for performing measurements. For example, sensor 204 may include a touch screen (e.g., a capacitive touch screen such as may be used in a smartphone or other touch-sensitive device for receiving user input). Capacitive touch screens may be relatively inexpensive and easy to deploy to obtain measurements. The technology used in a capacitive touch screen may be combined with a PCA that implements the functionality of computing device 202. For example, capacitors used in a touch screen may be mounted in appropriate locations within the PCA (e.g., connected via dedicated circuit module lines that may be connected to a processing circuit module for obtaining measurements associated with the capacitors). In some examples, the circuit module for obtaining measurements (e.g., from capacitor array 206) may already be implemented by computing device 202.

[0044] In some examples, a touch screen can be located near (e.g., above or adjacent to) a computing device, such as a motherboard, to enable measurements to be taken from such a computing device (e.g., to determine whether the computing device has been tampered with). In some examples, a touch screen can be controlled by a computing device (e.g., the computing device can control what is displayed on the touch screen). In some examples, a touch screen can be used to provide user input to a computing device (e.g., a user touch can provide instructions to be executed by the computing device).

[0045] In some examples, a touch screen of a user device may be used in certain scenarios to determine whether a computing device of the user device has been tampered with. For example, a user device such as a clamshell device (e.g., a folding phone, tablet, notebook, or laptop) may include a touch screen that may be located near a computing device of the clamshell device (such as when the clamshell device is closed). When in this closed position, the touch screen may be used to take measurements that can be used to determine whether the computing device of the clamshell device has been tampered with. In another example, for example, a touch screen of a smartphone or tablet may always be near a computing device of the smartphone / tablet (due to the design of the smartphone / tablet). In any case, the touch screen of the user device may be sensitive to any changes in the hardware configuration of the computing device.

[0046] In some examples, isolated electrical contacts (e.g., circuit module lines) in a PCA can form a capacitor-like structure. Measurements of electrical values ​​associated with such electrical contacts can provide an indication. Thus, in some examples, specialized structures of a PCA such as isolated electrical contacts can provide an indication without using any more expensive components, such as specialized capacitors.

[0047] In some examples, the capacitive touch screen may include a capacitor array 206. In use, the sensor 204 may be located at an appropriate position relative to the computing device 202 and measured as needed. The sensitivity of the sensor 204, such as a capacitive touch screen, may vary according to the specified needs of the computing device 202. For example, if a specified sensitivity is required to detect changes in the electric field distribution, the sensor 204 may be appropriately selected accordingly (e.g., by selecting a specific number, type and / or distribution of capacitors 206a, 206b). If the sensor 204 is in the form of a capacitive touch screen, the touch screen may be constructed according to the application and / or the specified sensitivity. For example, a certain layer of the touch screen (e.g., a protective layer) may be omitted and / or the circuit module of the touch screen may be modified to increase the sensitivity.

[0048] In some examples, the capacitors 206a, 206b in the capacitor array 206 are distributed at designated locations relative to the computing device 202 (e.g., the capacitors 206a, 206b may be at least partially distributed throughout or adjacent to the computing device 202). In some examples, the locations of the capacitors 206a, 206b may be fixed (e.g., if the sensor 204 is mounted in situ with the computing device 202 or as part of its packaging). In some examples, the locations of the capacitors 206a, 206b may not be fixed (e.g., if the sensor 204 is not mounted as part of the computing device 202, such as may be the case if a user is able to position the sensor 204 as desired).

[0049] In some examples, at least some of the capacitors 206a, 206b may be arranged in a regular pattern (e.g., a grid of capacitors 206a, 206b with regular or repeating spacing between each other). In some examples, at least some of the capacitors 206a, 206b may be arranged in an irregular pattern (e.g., a grid of capacitors 206a, 206b with random, non-repeating or uneven spacing between each other). The specific pattern of the capacitors 206a, 206b may increase the signal-to-noise ratio when measuring electrical parameters. For example, a specific component of interest of the computing device 202 may affect the electric field distribution in a relatively unnoticeable manner. The number, type and / or position of a specific capacitor 206a, 206 relative to the specific component may make it possible to detect any change in the electric field distribution (e.g., due to tampering) even if the change in the electric field distribution may be relatively unnoticeable if a tampering event occurs. In some examples, the capacitor 206a may have different properties (e.g., different capacitance) than another capacitor 206b of the capacitor array 206. The properties of capacitor 206 may be selected based on a specified sensitivity for a specified location of capacitor 206. For example, where a specified location requires a higher sensitivity, a capacitor 206 having a different capacitance may be selected for the specified location (e.g., such that a detectable change in capacitance may be observed if a tampering event occurs).

[0050] The system 200 also includes a measurement module 208 for measuring electrical parameters (e.g., measuring capacitance). The measurement module 208 is communicatively coupled to the sensor 204 to receive instructions therefrom and / or to facilitate the measurement of the electrical parameters. In some examples, the measurement module 208 is to measure electrical values ​​that can be used to determine the capacitance of the capacitors 206a, 206b of the sensor 204 (e.g., voltage and / or current evolution over a specified time, charge / discharge time, resonant frequency, and / or voltage change of a polarized capacitor). In such an example, the measurement module 208 may include a circuit module for determining the voltage and / or current associated with a particular capacitor 206a, 206b of the sensor 204.

[0051] In some examples, measurement module 208 can obtain measurements continuously (e.g., regularly or according to a specified time interval or schedule). In some examples, measurement module 208 can obtain measurements on demand (e.g., measurements can be initiated at the request of another entity such as a user, a scheduler, or an administrative component). In some examples, measurement module 208 can perform measurements when a condition is met (e.g., if computing device 202 can enter a particular state (e.g., a power state) and / or if sensor 204 is in a position suitable for taking measurements).

[0052] In some examples, measurement module 208 may perform measurements at a specified sensitivity based on certain factors.

[0053] In some examples, the purpose of the capacitor 206a, 206b of interest may affect how sensitive the capacitor 206a, 206b should be (or what configuration the computing device 202 should be) in order to detect a capacitance change. For example, the capacitance of the capacitor 206a, 206b and / or its location and / or sensing area size may affect the sensitivity of a particular capacitor 206a, 206b to a perturbation of the electric field distribution. Thus, in some examples, if a particular hardware component does not significantly affect the electric field distribution, the capacitor may be positioned near the hardware component and / or its sensitivity may be selected (e.g., its capacitance may be selected) so that any change in the electric field distribution due to tampering with the particular component can be detected even if the perturbation of the electric field distribution is relatively small. Similarly, if a particular hardware component significantly affects the electric field distribution, the capacitor may be positioned farther away from the hardware component and / or its sensitivity may be selected (e.g., reduced compared to the previous example) so that any change in the electric field distribution due to tampering with the particular component can still be detected.

[0054] In some examples, the capacitors of interest 206a, 206b may be dedicated to detecting any new components installed in the computing device 202. In some examples, the capacitors of interest 206a, 206b may be dedicated to detecting the proximity of tampered components. Any combination of the above examples may be used to affect the sensitivity of the measurement. In some examples, the design of the capacitor array 206 may be selected based on risk factors such as whether a particular component is susceptible to tampering, in which case the capacitor(s) selected for detecting tampering attempts may be positioned and / or specified as appropriate based on the risk factors.

[0055] In some examples, the state of computing device 202 may affect the number and / or type (eg, sensitivity) of measurements being taken, eg, depending on a risk level associated with the state or state change.

[0056] In some examples, the state of computing device 202 can affect the model (e.g., as described herein) used to establish whether the indication indicates an expected electric field distribution. In some examples, the model can be adjusted and / or a different model can be used based on a particular state (e.g., power state) of computing device 202. For example, if a particular state (or state change) is associated with a higher risk that computing device 202 has been tampered with, the model and / or a different model can be adjusted to reflect the higher risk and increase the likelihood of identifying a potential attack.

[0057] In some examples, the power and / or activity of computing device 202 may affect the number and / or type of measurements to be obtained (e.g., by sensor 204). For example, if computing device 202 is powered off for some reason (e.g., accidentally or due to a reboot), the number and / or type of measurements performed may be adjusted appropriately (e.g., to a higher sensitivity than normal in the case where computing device 202 is more likely to have been tampered with due to its particular state). In another example, because electric fields (e.g., parasitic electric fields) generated by the hardware of computing device 202 during its powered-on operation may be reduced or minimized during the power-off period, the sensitivity and / or accuracy of the measurements may be increased during the power-off period. Thus, in some examples, sensor 204 may be able to detect changes in the electric field distribution associated with computing device 202 during the power-off period due to, for example, hardware components not being in expected locations and / or not having expected sizes and the electric field distribution (e.g., generated by sensor 204) being modified by the unexpected hardware configuration.

[0058] In some examples, the sensitivity level of the measurement obtained by sensor 204 may be based (eg, dynamically) on the current and / or previous state of computing device 202. In some examples, the sensitivity level may be informed by a model used to determine whether the indication is indicative of an expected electric field distribution.

[0059] In some examples, the location of the capacitors of interest 206a, 206b relative to the computing device 202 may affect the specified sensitivity. For example, if the location of the capacitors 206a, 206b is believed to be associated with a reduced likelihood of detecting a change in the electric field distribution, the sensitivity of the measurements performed may be appropriately selected (e.g., by causing the sensitivity of the capacitors of interest 206a, 206b to increase, such as by adjusting circuit modules associated with the capacitors of interest 206a, 206b as appropriate).

[0060] System 200 also includes a determination module 210 (e.g., including a processing circuit module) for determining whether the indication indicates an expected electric field distribution of computing device 202. In some examples, determination module 210 can implement block 104 of method 100. Determination module 210 can receive the indication from measurement module 208. Thus, determination module 210 can use the measurements obtained by measurement module 208 to determine whether a component of computing device 202 has been tampered with.

[0061] In some examples, system 200 also includes model 212 (eg, a memory accessible to determination module 210 that includes information about expected electrical parameters and / or electric field distribution of computing device 202 ) that determination module 210 can use to determine whether computing device 202 has been tampered with.

[0062] In some examples, model 212 includes an electric field distribution model such as described herein.

[0063] In some examples, model 212 may be used to compare an expected measurement of an electrical parameter at a specified location relative to computing device 202 with an expected (e.g., initial) measurement of the electrical parameter. For example, the expected measurement of the electrical parameter may be obtained at a trusted time during the manufacture of computing device 202. This expected / initial measurement may be used as a baseline to compare subsequent measurements of the electrical parameter.

[0064] In some examples, model 212 may be used to detect unexpected objects or components near computing device 202 .

[0065] In some examples, determination module 210 may be able to detect differences or inconsistencies between the data provided by model 212 and the indication. In the event such a difference or inconsistency is detected, determination module 210 may determine, based on certain criteria, that computing device 202 has been tampered with. However, if no such difference or inconsistency is detected, determination module 210 may determine that computing device 202 has not been tampered with. Depending on whether it is determined that computing device 202 has been tampered with, determination module 210 may provide a notification regarding the status or trustworthiness of the computing device.

[0066] In some examples, the data provided by model 212 can be used for comparison between the indication and the expected value of the electrical parameter (i.e., as provided by the data). In the event that the difference between the indication and the expected value of the electrical parameter exceeds a specified threshold, this can indicate that computing device 202 has been tampered with.

[0067] In some examples, the model 212 may be based on multiple parameters (e.g., electrical parameters) from a set of measurements. For example, multiple measurements (e.g., capacitance measurements) may be obtained from the capacitor array 206. In some cases, a tampering attempt may not be directly detected from a single measurement, but may be detected by analyzing multiple measurements from the capacitor array 206 (e.g., multiple measurements from a single capacitor 206a at different times and / or measurements from multiple capacitors 206a, 206b at the same time or at different times). For example, the model 212 may implement a machine learning method to analyze the data provided by the measurement module 208. For example, the machine learning-based model 212 may have been trained using measurement data indicating whether the computing device 202 has been tampered with, so that in use, the determination module 210 may use the model 212 to predict whether a certain measurement or a certain set of measurements indicates a tampering attempt. In some examples, the model 212 may be used to infer the probability that a tampering attempt has occurred.

[0068] In some examples, the determination module 210 may detect a non-compliant perturbation of an electric field around a capacitor 206a (or a plurality of capacitors 206a, b) in the capacitor array 206. In some examples, the model 212 may provide or include information about an electric field that complies with an expected electric field associated with a specified hardware configuration of the computing device 202. A certain perturbation of the electric field may comply with the model (i.e., the specified hardware configuration of the computing device 202 may be as expected, for example, the computing device 202 has not been tampered with). However, if the perturbation does not comply with the model 212 (i.e., "non-compliant"), this may indicate that the electric field does not comply with the expected electric field associated with the specified hardware configuration of the computing device 202 (i.e., the specified hardware configuration of the computing device 202 may not be as expected, for example, the computing device 202 has been or may have been tampered with). An example of a non-compliant perturbation may be if the capacitance of the capacitor 206a or the plurality of capacitors 206 changes by a certain value, such as exceeding a threshold. In some examples, a non-compliant disturbance may be detected by analyzing multiple measurements from capacitor 206a (eg, at different times) or multiple capacitors 206a,b (eg, at the same time or at different times).

[0069] System 200 also includes a response module 214 communicatively coupled to determination module 210. Response module 214 may take specific actions depending on whether determination module 210 determines that a tampering attempt has occurred or may have occurred. As will be explained in more detail below, response module 214 may take a variety of possible actions.

[0070] In some examples, response module 214 may send a notification to a user, management infrastructure, or other authentication entity with any information about an attack / potential attack on computing device 202. The notification may include information about the attack, such as obtained measurement(s) indicative of the attack, model 212, and / or a state of computing device 202 (e.g., before, during, or after the attack).

[0071] In some examples, response module 214 may cause limitations on the functionality of computing device 202 .

[0072] In some examples, response module 214 may cause computing device 202 to be locked, powered off, or otherwise disabled (or limited in functionality) until response module 214 receives a management command to allow computing device 202 to increase in functionality (or normal).

[0073] In some examples, response module 214 may cause computing device 202 to be locked, powered off, or otherwise disabled (or limited in functionality) until determination module 210 determines that the measurement(s) provided by measurement module 208 indicate an expected value for the measurement(s). For example, determination module 210 may determine that the obtained measurements indicate a degree of conformance with model 212 (e.g., the difference between the measurement and the expected value may be below a threshold).

[0074] In some examples, response module 214 may implement any combination of the above examples to reduce or limit the functionality of computing device 202 according to a particular protocol to reduce or manage risks associated with a (potentially) compromised computing device 202 .

[0075] Despite Figure 2 208, the determination module 210, the model 212, and the response module 214 may be combined with any other module in the measurement module 208, the determination module 210, the model 212, and the response module 214. Therefore, the processing circuit module for implementing the method 100 may include the processing circuit module associated with any combination of the measurement module 208, the determination module 210, the model 212, and the response module 214.

[0076] In some examples, any of the above modules (e.g., measurement module 208, determination module 210, model 212, and response module 214) include at least one dedicated processor (e.g., application specific integrated circuit (ASIC) and / or field programmable gate array (FPGA), etc.) for implementing the module functions.

[0077] In some examples, the module includes at least one processor for implementing instructions, the instructions causing the at least one processor to implement the module functions described above. In such examples, the instructions may be stored in a machine-readable medium (not shown) accessible to the at least one processor. In some examples, the module itself includes a machine-readable medium. In some examples, the machine-readable medium may be separated from the module itself (e.g., at least one processor of the module may be provided to communicate with the machine-readable medium to access the instructions stored therein).

[0078] Figure 3 A flow chart of a method 300 for determining certain information about a computing device is depicted, which method 300 may be a computer-implemented method. Method 300 may be implemented by an entity such as an end user, a manufacturer, or other verification entity. Method 300 may be implemented using, for example, a processing circuit module of a personal computer, a dedicated processing device, a server, a cloud-based service, or any other computing device. Method 300 may be implemented in conjunction with method 100 or as a part of method 100. Further references Figure 2In this example, method 300 also includes blocks 102 , 104 of method 100 .

[0079] In some examples, determining whether the indication indicates an expected electric field distribution associated with a specified hardware configuration of the computing device (i.e., block 104 of method 300) includes comparing the indication of the electrical parameter with a previously obtained indication of the electrical parameter. Method 300 may also include determining whether any deviation between the indication and the previously obtained indication indicates an unexpected modification of the hardware configuration of the computing device. Determination module 210 may access previously obtained indications (e.g., via Figure 2 Thus, determination module 210 may receive the indication (e.g., when testing whether computing device 202 has the expected provenance) and compare the received indication with a previously obtained indication (e.g., which may be obtained at a trusted point in the manufacturing process and stored in memory or used to generate model 212).

[0080] In some examples, determining whether the indication indicates an expected electric field distribution associated with a specified hardware configuration of the computing device (i.e., block 104 of method 300) includes determining whether the indication satisfies specified criteria regarding the expected electric field distribution. In the event that the specified criteria are met, the provenance of the computing device may meet expectations. In the event that the specified criteria are not met, the provenance of the computing device may not meet expectations.

[0081] In some examples, the specified criteria may include a threshold value that, if exceeded, may indicate a potential tampering attempt (e.g., due to a change in the electric field distribution). For example, when the specified criteria is that the difference between the indication and a previously obtained indication is below a threshold value and / or if the analysis of the indication provides information that the change in the electric field distribution does not indicate a tampering attempt (e.g., based on data provided by model 212), the provenance of computing device 202 may meet expectations (i.e., the computing device has not been tampered with). When the specified criteria is that the difference between the indication and a previously obtained indication meets or exceeds a threshold value and / or if the analysis of the indication provides information that the change in the electric field distribution indicates a tampering attempt (e.g., based on data provided by model 212), the provenance may not meet expectations.

[0082] In some examples, method 300 includes causing a sensor (eg, sensor 204) to perform a measurement of an electrical parameter at block 302. For example, as described below, measurement module 208 may be caused to obtain a measurement under various circumstances.

[0083] In some examples, the sensor may be caused to perform at least one of the following measurements: repeatedly; at the request of the authentication entity; and in response to satisfying a specified condition. In some examples, the specified condition may refer to a change in the computing device state, such as due to a power outage event or a restart. In some examples, the specified condition may refer to a determination that the computing device was moved to a different location and / or a different entity now owns the computing device.

[0084] In some examples, causing the sensor to perform a measurement at a specified sensitivity can be based on at least one of: a purpose of the sensor; a state of the computing device and a position of the sensor relative to the computing device. In some examples, the sensitivity of the measurement can depend on any of the above-mentioned factors.

[0085] In some examples, receiving an indication (e.g., block 102 of method 300) includes receiving an indication of an electrical parameter measured at a plurality of locations associated with at least the portion of the computing device. For example, the electrical parameter may be measured at a plurality of locations relative to the computing device. In some examples, where the sensor includes an array of capacitors, each capacitor may be associated with a different location and may provide a measurement at its particular location. In some examples, the measurement of the electrical parameter at each location may be performed by moving the sensor to a different location in order to perform a measurement at that location (e.g., if the sensor includes a single capacitor or other electrical component capable of detecting a change in an electric field).

[0086] In some examples, determining whether the indication indicates an expected electric field distribution associated with a specified hardware configuration of the computing device may include using a model (eg, an “electric field distribution model”) to determine whether indications of electrical parameters measured at multiple locations indicate an expected electric field distribution.

[0087] In some examples, the model is based on previously obtained indications of electrical parameters measured at multiple locations (e.g., "experimental data"). For example, the model can be constructed using data from previous measurements of electrical parameters at multiple locations. In some examples, the model is based on previously obtained indications of electrical parameters measured at specified locations.

[0088] In some examples, the model is based on information (e.g., "theoretical knowledge") about how hardware components of the computing device affect the expected electric field distribution. For example, the information may relate to how the hardware components may interfere with or otherwise affect the electric field around the hardware components. In another example, the information may relate to the expected electric field generated by the hardware components during operation (e.g., when powered on).

[0089] In some examples, any way in which hardware components affect the expected electric field distribution can be modeled (e.g., using previously obtained indications and / or information). Thus, the model can be based on at least one of: experimental data and theoretical knowledge about how hardware components contribute to or otherwise affect the electric field.

[0090] In some examples, method 300 includes causing a notification to be issued in response to determining that the indication is inconsistent with an expected electric field distribution at block 304. For example, the indication may be inconsistent with an expected electric field distribution if specified criteria are not met and / or if a difference between the indication and a previously obtained indication meets or exceeds a threshold.

[0091] In some examples, causing the notification to be issued may cause a particular action to be taken. For example, any one or a combination of the following example actions may be taken. One example action may be to send a notification to a verification entity. Another example action may be to limit the functionality of the computing device until the verification entity allows the functionality of the computing device to be increased. Another example action may be to limit the functionality of the computing device until it is determined that the indication indicates that the computing device is functioning as expected.

[0092] Figure 4 is a schematic diagram of an example device 400 for implementing or at least partially facilitating certain methods described herein (e.g., methods 100, 300). In some examples, device 400 includes a computing device and / or is considered an example of a computing device such as computing device 202. In some examples, device 400 can be used to determine certain information about the computing device that is different / separate from device 400 itself.

[0093] Device 400 includes sensor 402 to measure characteristics of an electric field distribution (e.g., an electrical parameter associated with the electric field distribution) affected by hardware components of a computing device (e.g., of device 400 itself or of a different / separate computing device). In some examples, sensor 402 may include a sensor (e.g., embedded, combined, or otherwise integrated with a processing circuit module (e.g., a circuit module of a computing device) and / or a package of device 400. Figure 2 In some examples, sensor 402 may include a module capable of measuring an electrical parameter or otherwise sending an indication of the electrical parameter to another module (e.g., Figure 2 Components of the measurement module 208 or the determination module 210).

[0094] In some examples, sensor 402 can be sensitive to changes in the electric field distribution (e.g., due to hardware components of the computing device). For example, the size, location, and / or type of the hardware components can affect the electric field distribution. Changes to the hardware components (e.g., due to tampering with the hardware components) can affect the electric field distribution, which can be detected by sensor 402.

[0095] In use of device 400, sensor 402 sends an indication of the characteristic to a verification entity. Sending the indication to the verification entity may allow the verification entity to determine whether the electric field distribution has changed by comparison with a previously determined electric field distribution associated with the computing device. Thus, if a change has occurred, the verification entity may determine whether the computing device has been tampered with. In some examples, sensor 402 may send the indication to a device such as Figure 2 In some examples, the device 400 may include a measurement module 208 and / or a determination module 210 in and / or send an indication via them. Figure 2 The measurement module 208 referenced in , and the measurement module 208 can receive an indication of a characteristic from the sensor 402 and send the indication of the characteristic (eg, an indication of a measurement of an electrical parameter) to a verification entity (eg, the determination module 210).

[0096] Figure 5 1 is a schematic diagram of an example device 500 for implementing or at least partially facilitating certain methods (e.g., methods 100, 300) described herein. Device 500 includes a processing circuit module 502, which may include a computing device such as computing device 202. Device 500 may include certain modules or devices, or communicate with them, such as in conjunction with Figure 2 Those described.

[0097] In this example, the device 500 includes Figure 4 In this example, the sensor 402 is not part of the processing circuit module 502, but in other examples, the sensor 402 may form part of the processing circuit module 502.

[0098] In some examples, sensor 402 includes a capacitor array (such as a combination of Figure 2 ), used to measure the characteristics of the electric field distribution at different locations of the device 500.

[0099] In some examples, the capacitor array includes a plurality of capacitors distributed across the device 500. The indication of the characteristic may indicate a capacitance value associated with the capacitor at each different location. For example, each capacitor may have a certain associated capacitance value that depends on the electric field distribution associated with the computing device (and / or due to the electric field generated by the capacitor itself). The indication of the characteristic (i.e., the capacitance value of each of the plurality of capacitors) may be used to determine (e.g., with reference to a model) whether the computing device has been altered (e.g., tampered with).

[0100] In some examples, some of the capacitors of the capacitor array may be uniformly distributed on device 500 (e.g., at least a portion of device 500 may include a plurality of uniformly distributed capacitors distributed according to a regular pattern, as described above). In some examples, some of the capacitors of the capacitor array may be non-uniformly distributed on device 500 (e.g., at least a portion of device 500 may include a plurality of non-uniformly distributed capacitors distributed according to an irregular pattern, as described above).

[0101] In some examples, device 500 also includes conductive element 504. Conductive element 504 can modify the electric field distribution to create a characteristic electric field distribution associated with processing circuit module 502 (e.g., computing device) of device 500. For example, conductive element 504 can be formed in a manner that modifies the electric field distribution in a manner that is related to the identity of device 500. Therefore, each device 500 including a computing device can be manufactured to have its own characteristic electric field distribution, so that each device 500 can be distinguished from other devices 500 even if each device 500 includes the same components.

[0102] In some examples, conductive element 504 can be included with device 500 in a manner that facilitates electric field measurement. For example, conductive element 504 can enhance or otherwise alter the electric field distribution in an easily detectable manner. In some examples, it may be difficult for an entity such as an unauthorized manufacturer to replicate the same electric field distribution with a damaged or unauthorized component / device 500.

[0103] In some examples, the characteristic electric field distribution may be determined at a trusted point in the manufacture of device 500, or at another appropriate time. The characteristic electric field distribution may be used as a trusted reference point, which may be communicated, for example, to a repository (e.g., model 212) that may be accessed for future measurements to determine whether device 500 has been tampered with or cannot be trusted for some reason.

[0104] In some examples, conductive element 504 includes a plurality of conductive particles. The plurality of conductive particles can be introduced into a PCA and / or a package (eg, housing) of device 500 (eg, by a trusted entity during manufacture of device 500).

[0105] In some examples, conductive element 504 may be included in device 500 in a non-deterministic process to create a physically unclonable function for a characteristic electric field distribution. If conductive element 504 is included using a non-deterministic process, the characteristic electric field distribution may be difficult to replicate. In the case where the conductive element includes a plurality of conductive particles, these particles may be included in device 500 in a non-deterministic manner (e.g., they may be randomly incorporated into device 500 or otherwise combined with device 500).

[0106] Figure 6 6 is a schematic diagram of an example device 600 for implementing or at least partially facilitating certain methods (eg, methods 100, 300) described herein. The device 600 includes a processing circuit module 602. The processing circuit module 602 may include, for example, a combination of Figure 2 In this example, the device 600 is a device that is connected to the Figure 4 Device 600 may be used to control the operation of device 400 and / or receive measurements from device 400. In some examples, device 600 may be combined or otherwise integrated with device 400.

[0107] The processing circuit module 602 includes a processing module 604 for determining whether to receive a signal from a sensor (eg, a sensor for measuring an electric field associated with a specified hardware configuration of a computing device (eg, computing device 202). Figure 2 When it is determined that a measurement is to be obtained, processing module 604 may cause sensor 204 to obtain the measurement. The measurement (or an indication thereof) provided / sent by sensor 204 may be processed by device 600 itself or by another device (e.g., including Figure 2 The determination module 210 receives the electric field information so as to allow a determination to be made as to whether the electric field distribution associated with the specified hardware configuration of the computing device is as expected.

[0108] In some examples, the processing module 604 includes at least one dedicated processor (eg, an application specific integrated circuit (ASIC) and / or a field programmable gate array (FPGA), etc.) for implementing the functions of the processing module 604 described above.

[0109] In some examples, processing module 604 includes at least one processor for executing instructions that cause the at least one processor to implement the functions of processing module 604 described above. In such examples, the instructions may be stored in a machine-readable medium (not shown) accessible to at least one processor. In some examples, device 600 includes a machine-readable medium. In some examples, the machine-readable medium may be separate from device 600 (e.g., at least one processor of processing module 604 may be provided to communicate with the machine-readable medium to access the instructions stored therein).

[0110] In some examples, processing module 602 includes Figure 2 The measurement module 208.

[0111] In some examples, the processing circuit module 602 also includes another module, such as Figure 2 Any one or a combination of the determination module 210, the model 212 and the response module 214.

[0112] Figure 7A machine-readable medium 700 (eg, a tangible machine-readable medium) is schematically illustrated storing instructions 702 that, when executed by at least one processor 704, cause the at least one processor 704 to perform certain example methods described herein (eg, methods 100 or 300).

[0113] Instructions 702 include instructions 706 that cause at least one processor 704 to obtain an indication of an electrical parameter associated with a component (e.g., a "hardware component") for detecting a hardware state of a computing device. In some examples, instructions 706 may cause at least one processor 704 to provide the same or similar functionality as block 102 of method 100.

[0114] In some examples, the hardware state may refer to a hardware configuration of the computing device. In some examples, the hardware state may refer to the number, size, location, and / or type of components used in the computing device. In some examples, the indication may indicate an expected electric field distribution associated with a specified hardware configuration of the computing device.

[0115] Instructions 702 also include instructions 708 that cause at least one processor 704 to determine whether the indication satisfies a specified condition regarding an electrical parameter estimated for the component. The estimated electrical parameter may be based on an electric field distribution model of the computing device (e.g., model 212), and the specified condition may indicate that the hardware state of the computing device is as expected. If the component (or even any other part of the computing device) has not been tampered with or otherwise deemed to be not compromised or unauthorized, the hardware state may be as expected. In some examples, instructions 708 may cause at least one processor 704 to provide the same or similar functionality as block 104 of method 100.

[0116] Instructions 702 also include instructions 710 that cause at least one processor 704 to cause a notification to be issued if the indication does not satisfy a specified condition. In some examples, instructions 710 may cause at least one processor 704 to provide a notification related to Figure 2 The response module 214 has the same or similar functions.

[0117] Certain modules of the devices described herein may be combined with certain modules of other devices described herein. Figure 2 , Figure 4 , Figure 5 and Figure 6 Any module or device described in any figure can be combined with Figure 2 , Figure 4 , Figure 5 and Figure 6Any module or device described in any figure may be combined or replaced with them. In addition, some modules or devices described herein may at least partially provide the same or similar functions as some methods described herein (eg, methods 100, 300), and vice versa.

[0118] Examples in the present disclosure may be provided as methods, systems, or as a combination of machine-readable instructions and processing circuit modules. Such machine-readable instructions may be included on a non-transitory machine (e.g., computer) readable storage medium (including but not limited to disk storage devices, CD-ROMs, optical storage devices, etc.) having computer-readable program code therein or thereon.

[0119] The present disclosure is described with reference to the flowcharts and block diagrams of the methods, devices and systems according to the examples of the present disclosure. Although the flowcharts described above show a specific execution order, the execution order may be different from that depicted. The blocks described in conjunction with a flowchart may be combined with the blocks of another flowchart. It should be understood that each block in the flowchart and / or block diagram and the combination of blocks in the flowchart and / or block diagram may be implemented by machine-readable instructions.

[0120] Machine-readable instructions may be executed, for example, by a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to implement the functions described in the specification and the figure. In particular, a processor or a processing circuit module or its module may execute machine-readable instructions. Therefore, the functional modules or devices (e.g., measurement module 208, determination module 210, model 212, response module 214, communication module 406, and / or processing module 604) and devices of the system 200, device 400, 500, 600 may be implemented by a processor that executes machine-readable instructions stored in a memory or a processor that operates according to instructions embedded in a logic circuit module. The term "processor" should be broadly interpreted as including a CPU, a processing unit, an ASIC, a logic unit, or a programmable gate array, etc. These methods and functional modules may all be executed by a single processor, or divided between several processors.

[0121] Such machine-readable instructions may also be stored in a computer-readable storage device capable of directing a computer or other programmable data processing device to operate in a specific mode.

[0122] Such machine-readable instructions may also be loaded onto a computer or other programmable data processing device to cause the computer or other programmable data processing device to perform a series of operations to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device implement the functions specified by (one or more) blocks in the flowchart and / or block diagram.

[0123] Furthermore, the teachings herein may be implemented in the form of a computer program product, which is stored in a storage medium and includes a plurality of instructions for causing a computer device to implement the method set forth in the examples of the present disclosure.

[0124] Although the methods, apparatus, and related aspects have been described with reference to certain examples, various modifications, changes, omissions, and substitutions may be made without departing from the scope of the present disclosure. Therefore, the methods, apparatus, and related aspects are intended to be limited by the scope of the appended claims and their equivalents. It should be noted that the above examples illustrate rather than limit what is described herein, and many embodiments may be devised without departing from the scope of the appended claims. Features described in conjunction with one example may be combined with features of another example.

[0125] The word "comprising" does not exclude the presence of other elements than those listed in the claims, "a" or "an" does not exclude a plurality, and a single processor or other unit may fulfill the functions of several units recited in the claims.

[0126] Features from any dependent claim may be combined with features from any independent claim or from other dependent claims.

Claims

1. A method comprising: causing a sensor to perform a measurement of an electrical parameter associated with at least a portion of a computing device, wherein the sensor comprises a capacitor array for measuring a characteristic of an electric field distribution at different locations of the computing device, and at least one capacitor in the capacitor array is configured to be moved to a different location to measure the characteristic of the electric field distribution at the location; receiving an indication of the electrical parameter; as well as A processing circuit module is used to determine whether the indication indicates an expected electric field distribution associated with a specified hardware configuration of the computing device, wherein the specified hardware configuration refers to the number, type and / or distribution of electronic hardware components used in the computing device.

2. The method according to claim 1, wherein: Receiving the indication includes receiving indications of electrical parameters measured at a plurality of locations associated with at least the portion of the computing device.

3. The method according to claim 2, wherein: Determining whether the indication indicates an expected electric field distribution associated with a specified hardware configuration of the computing device includes using a model to determine whether the indications of the electrical parameters measured at the plurality of locations indicate an expected electric field distribution, wherein the model is based on at least one of: previously obtained indications of electrical parameters measured at the plurality of locations; and Information about how hardware components of the computing device affect the expected electric field distribution.

4. The method according to claim 1, wherein: Determining whether the indication indicates an expected electric field distribution associated with a specified hardware configuration of the computing device includes: comparing the indication of the electrical parameter to a previously obtained indication of the electrical parameter; and A determination is made as to whether any deviation between the indication and previously obtained indications indicates an unexpected modification of a hardware configuration of the computing device.

5. The method according to claim 1, wherein: Determining whether the indication indicates an expected electric field distribution associated with a specified hardware configuration of the computing device includes determining whether the indication satisfies specified criteria regarding the expected electric field distribution, such that: if the specified criteria are met, the provenance of the computing device meets expectations, and if the specified criteria are not met, the provenance of the computing device does not meet expectations.

6. The method of claim 5, comprising causing the sensor to perform measurements at a specified sensitivity based on at least one of: a purpose of the sensor; a state of the computing device and a position of the sensor relative to the computing device.

7. The method of claim 1, comprising causing issuance of a notification in response to determining that the indication is inconsistent with an expected electric field distribution.

8. The method according to claim 7, wherein: Causing issuance of the notification causes at least one of: sending the notification to the verification entity; limiting the functionality of the computing device until the verification entity allows the functionality of the computing device to be increased; limiting the functionality of the computing device until it is determined that the indication indicates that the computing device is operating as expected.

9. A device comprising: a sensor to measure a characteristic of an electric field distribution affected by a hardware configuration of a computing device, wherein the sensor is to send an indication of the characteristic to a verification entity to allow the verification entity to compare it with a previously determined electric field distribution associated with the computing device to determine whether the electric field distribution has changed, wherein the hardware configuration refers to the number, type and / or distribution of electronic hardware components used in the computing device; The sensor includes a capacitor array for measuring characteristics of electric field distribution at different locations of the computing device, and at least one capacitor in the capacitor array is configured to be moved to a different location to measure the characteristics of the electric field distribution at the location.

10. The device according to claim 9, wherein: The capacitor array includes a plurality of capacitors distributed across the computing device, and wherein the indication of the characteristic is used to indicate a capacitance value associated with the capacitor at each of the different locations.

11. The apparatus of claim 9, comprising a conductive element for modifying the electric field distribution to create a characteristic electric field distribution coupled to a processing circuit module of the computing device.

12. The device according to claim 11, wherein The conductive elements are included in the computing device in a non-deterministic process to create a physically unclonable function for the characteristic electric field distribution.

13. A tangible machine-readable medium storing instructions that, when executed by at least one processor, cause the at least one processor to: obtaining an indication of an electrical parameter associated with a component for detecting a hardware state of a computing device and measured by a sensor, wherein The hardware status refers to the number, size, location and / or type of components used in a computing device; determining, based on an electric field distribution model of the computing device, whether the indication satisfies a specified condition regarding an electrical parameter estimated for the component, wherein the specified condition indicates that a hardware state of the computing device is as expected; and if said indication does not satisfy said specified condition, causing the issuance of a notification; The sensor includes a capacitor array for measuring characteristics of electric field distribution at different locations of the computing device, and at least one capacitor in the capacitor array is configured to be moved to a different location to measure the characteristics of the electric field distribution at the location.

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