Method for detecting abnormal signal, device, and readable storage medium
By measuring the RSSI values of multiple frequency points after the communication device disconnects from the access network and utilizing preset thresholds and machine learning models, the problem of detecting hidden wireless devices is solved, achieving efficient and accurate detection of covert devices and protecting user privacy.
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- FIBOCOM WIRELESS
- Filing Date
- 2025-06-17
- Publication Date
- 2026-07-23
AI Technical Summary
Existing technologies struggle to efficiently, accurately, and economically detect hidden wireless devices, such as hidden cameras and eavesdropping devices, especially when these devices have their infrared capabilities disabled. Traditional devices are bulky, expensive, and difficult to detect.
After the communication device disconnects from the access network device, the Received Signal Strength Indication (RSSI) on multiple supported frequency points is measured. The RSSI values are analyzed using preset threshold values and machine learning models to determine whether there are abnormal signals in the environment. The hidden device is then accurately located by measuring the maximum value and location of the RSSI value.
It achieves cost savings while efficiently and accurately detecting the presence of hidden devices in the environment, protecting user privacy and security, and requires no additional hardware.
Smart Images
Figure CN2025101394_23072026_PF_FP_ABST
Abstract
Description
Method, device and readable storage medium for detecting abnormal signal
[0001] The present application claims priority to the Chinese patent application No. 202510086521.1, filed on January 17, 2025, and entitled "Method, device and readable storage medium for detecting abnormal signal", the content of which is incorporated herein by reference in its entirety. TECHNICAL FIELD
[0002] The present application relates to the technical field of signal detection, and in particular to a method, device and readable storage medium for detecting abnormal signal. BACKGROUND
[0003] With the increasing popularity of wireless communication technology, various wireless devices are emerging, including a large number of hidden cameras, eavesdropping devices and positioning tracking devices. These devices are often small in size, strong in disguise, and difficult to detect, which poses a serious threat to people's privacy and security.
[0004] Hidden wireless devices (which can be referred to as concealed devices) are accompanied by a large number of radio signal emissions during use, such as hidden cameras and eavesdropping devices, which are accompanied by a large number of and long time radio signal emissions when uploading audio or image data. Currently, hidden cameras can be used to find concealed devices by emitting infrared light. Infrared rays are mainly used for camera shooting in low-light environments, and this method cannot find concealed devices if the hidden camera turns off this function. At the same time, this method cannot find hidden eavesdropping devices. Professional wireless detection devices are usually expensive, large in size and inconvenient to carry.
[0005] Therefore, how to save costs while achieving efficient and accurate detection of concealed devices needs to be explored. SUMMARY
[0006] The present application provides a method, device and readable storage medium for detecting abnormal signal.
[0007] In a first aspect, the present application provides a method for detecting abnormal signal, applied to a communication device, comprising: obtaining M frequency points supported by the communication device when the communication device is disconnected with an access network device. Measuring received signal strength indicator (RSSI) on the M frequency points respectively, obtaining N RSSI values, at least one RSSI value is measured on one frequency point. According to the N RSSI values, determining whether there is an abnormal signal in the environment, the RSSI value on the frequency point where the abnormal signal is located is greater than or equal to a preset threshold value. Wherein, M is a positive integer, N is an integer greater than or equal to M.
[0008] It can be understood that if the communication device determines that there is an abnormal signal in the environment, it means that there is a hidden wireless device in the environment; if the communication device determines that there is no abnormal signal in the environment, it means that there is no hidden wireless device in the environment.
[0009] For example, the communication device described above can be a terminal device with wireless transceiving function, such as a mobile phone, a notebook with a mobile communication module, a tablet, etc. In addition, the communication device also has the function of radio power measurement, that is, the ability to measure the RSSI of a signal.
[0010] For example, after the communication device in the embodiment of the application is disconnected with the access network device, the control module in the communication device can control the communication device to send or receive signals through an attention (AT) command.
[0011] In combination with the first aspect, in a possible implementation manner, the M frequency points supported by the communication device are acquired, including:
[0012] The frequency band list corresponding to at least one communication standard supported by the communication device is acquired; and the M frequency points are determined from the frequency band list corresponding to the at least one communication standard, wherein the frequency interval between adjacent two frequency points is a fixed value. For example, the frequency interval between adjacent two frequency points can be 200 kHz.
[0013] Generally, the communication device can support one or more communication standards. Under one communication standard, the communication device can support communication on multiple frequency bands, and one frequency band can include multiple frequency points, and there is a fixed frequency interval between adjacent frequency points. For example, the communication standard can include 4G or 5G or the next generation communication standard, such as 6G, etc.
[0014] In combination with the first aspect, in a possible implementation manner, the above-mentioned measuring the RSSI on the M frequency points respectively to obtain N RSSI values includes:
[0015] The RSSI of the signal received on each of the M frequency points is measured multiple times to obtain the maximum RSSI value of the signal received on each frequency point. According to the N RSSI values, it is determined whether there is an abnormal signal in the environment, including: according to the maximum RSSI value of the signal received on each frequency point, it is determined whether there is an abnormal signal.
[0016] In combination with the first aspect, in a possible implementation manner, the above-mentioned according to the maximum RSSI value of the signal received on each frequency point, it is determined whether there is an abnormal signal, including:
[0017] The maximum RSSI value of the received signal on each frequency point is compared with the aforementioned preset threshold. If the maximum RSSI value of the received signal on any of the M frequency points is greater than or equal to the preset threshold, it is determined that an abnormal signal exists in the environment, i.e., a hidden wireless device exists in the environment. Conversely, if the maximum RSSI value of the received signal on all M frequency points is less than the preset threshold, it is determined that no abnormal signal exists in the environment, i.e., no hidden wireless device exists in the environment.
[0018] For example, the aforementioned preset threshold value may be preset in the communication device.
[0019] In conjunction with the first aspect, in one possible implementation, the determination of whether an anomalous signal exists in the environment based on N RSSI values includes:
[0020] The N RSSI values and their corresponding frequency points are input into a trained machine learning model for processing. The output of this model includes the probability of an anomalous signal at each of the M frequency points. Based on the machine learning model's output, it is determined whether an anomalous signal exists in the environment.
[0021] For example, when the probability of an abnormal signal on any of the M frequency points is greater than or equal to a threshold, such as 0.8, it is determined that an abnormal signal exists in the environment, that is, a hidden wireless device exists in the environment. Conversely, when the probability of an abnormal signal on all M frequency points is less than the threshold, it is determined that no abnormal signal exists in the environment, that is, no hidden wireless device exists in the environment.
[0022] For example, the machine learning model described above may include models such as decision trees, random forests, or neural networks.
[0023] In conjunction with the first aspect, in one possible implementation, the above method also includes:
[0024] If an abnormal signal is present in the environment, determine the target frequency point where the abnormal signal is located; measure the RSSI at the target frequency point at multiple locations to obtain the RSSI values corresponding to multiple locations, with each location corresponding to at least one RSSI value; based on the RSSI values corresponding to these multiple locations, determine the location closest to the concealed device, which is the device that sent the abnormal signal, and the location closest to the concealed device has the largest RSSI value.
[0025] In conjunction with the first aspect, in one possible implementation, before acquiring the M frequency points supported by the communication device, the method further includes: in response to a user's operation or receiving an attention (AT) command, disconnecting the connection with the access network device, and controlling the communication device to send or receive signals via the AT command.
[0026] For example, a user's actions may include: removing the subscriber identity module (SIM) card from the communication device, or switching the communication device to airplane mode.
[0027] Secondly, embodiments of this application provide a communication device, which includes:
[0028] The acquisition module is used to acquire M frequency points supported by the communication device when the communication device is disconnected from the access network device, where M is a positive integer; the measurement module is used to measure the RSSI on the M frequency points respectively to obtain N RSSI values, where N is an integer greater than or equal to M; the determination module is used to determine whether there is an abnormal signal in the environment based on the N RSSI values, where the RSSI value on the frequency point where the abnormal signal is located is greater than or equal to a preset threshold value.
[0029] In conjunction with the second aspect, in one possible implementation, the aforementioned acquisition module is specifically used to: acquire a list of frequency bands corresponding to at least one communication standard supported by the communication device; and determine M frequency points from the list of frequency bands corresponding to at least one communication standard, wherein the frequency interval between two adjacent frequency points is a fixed value.
[0030] In conjunction with the second aspect, in one possible implementation, the aforementioned measurement module is specifically used to: perform multiple measurements at each of the M frequency points to obtain the maximum RSSI value of the received signal at each frequency point. The aforementioned determination module is specifically used to: determine whether an abnormal signal exists based on the maximum RSSI value of the received signal at each frequency point.
[0031] In conjunction with the second aspect, in one possible implementation, the aforementioned determining module is further specifically used to: compare the maximum RSSI value of the signal received at each frequency point with the preset threshold value; when there is a frequency point among the aforementioned M frequencies where the maximum RSSI value of the signal received is greater than or equal to the preset threshold, it is determined that there is an abnormal signal in the environment.
[0032] In conjunction with the second aspect, in one possible implementation, the aforementioned determining module is specifically used to: input the N RSSI values and the frequency points corresponding to the N RSSI values into a trained machine learning model for processing, obtain the output result of the machine learning model, the output result including the probability of an abnormal signal existing at each of the M frequency points; and determine whether an abnormal signal exists in the environment based on the output result of the machine learning model.
[0033] In conjunction with the second aspect, in one possible implementation, the determining module is further configured to determine the target frequency point where the abnormal signal is located when an abnormal signal exists in the environment. The measuring module is further configured to measure the RSSI at the target frequency point at multiple locations, obtaining RSSI values corresponding to multiple locations, with one location corresponding to at least one RSSI value. The determining module is further configured to determine the location closest to the concealed device, which is the device transmitting the abnormal signal, based on the RSSI values corresponding to the multiple locations, and the location closest to the concealed device has the largest RSSI value.
[0034] In conjunction with the second aspect, in one possible implementation, the aforementioned communication device further includes a response module for disconnecting from the access network device in response to a user's operation or receiving an AT command.
[0035] Thirdly, embodiments of this application provide a communication device, which includes a processor, a memory, and a communication interface. The processor is connected to the memory and the communication interface, wherein the communication interface is used to provide data communication functions, the memory is used to store computer programs, and the processor is used to call the computer programs so that the communication device executes the method for detecting abnormal signals provided in the first aspect or any possible implementation of the first aspect, and can also achieve the beneficial effects of the method for detecting abnormal signals provided in the first aspect.
[0036] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program. When the computer program is run on a terminal device, it causes the communication device to execute the method for detecting abnormal signals provided by the first aspect or any feasible implementation of the first aspect, thereby achieving the beneficial effects of the method for detecting abnormal signals provided by the first aspect.
[0037] Details of one or more embodiments of this application are set forth in the following drawings and description. Other features, objects, and advantages of this application will become apparent from the specification, drawings, and claims. Attached Figure Description
[0038] To better describe and illustrate the embodiments and / or examples of this application disclosed herein, reference may be made to one or more accompanying drawings. The appendices or examples used to describe the drawings should not be considered as limiting the scope of any of this application, the embodiments and / or examples currently described, or the best mode of this application as currently understood.
[0039] Figure 1 is a schematic diagram of an application scenario provided according to one or more embodiments of this application;
[0040] Figure 2 is a schematic flowchart of a method for detecting abnormal signals according to one or more embodiments of this application;
[0041] Figure 3 is a schematic diagram of RSSI measurement results at multiple frequency points according to one or more embodiments of this application;
[0042] Figure 4 is a schematic diagram of a communication device provided according to one or more embodiments of this application;
[0043] Figure 5 is a schematic diagram of another structure of a communication device provided according to one or more embodiments of this application. Detailed Implementation
[0044] In the description of this application, terms such as "first" and "second" are used to distinguish different objects, not to describe a specific order. Furthermore, unless otherwise stated, " / " means "or," for example, A / B can mean A or B. "And / or" in this document describes a relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone. Additionally, "at least one" refers to one or more, and "multiple" refers to two or more. "One or more of the following" or similar expressions refer to any combination of these items, including any combination of single or multiple items. For example, at least one of a, b, or c can represent: a, b, c; a and b; a and c; b and c; or a and b and c. Where a, b, and c can be single or multiple.
[0045] The terms “comprising” and “having”, and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the steps or units listed, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus.
[0046] In this application, the words "exemplary" or "for example" are used to indicate that something is an example, illustration, or illustration. Any embodiment or design described as "exemplary," "for example," or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or designs. Rather, the use of the words "exemplary," "for example," or "for example" is intended to present the relevant concepts in a specific manner.
[0047] In this application, “when…”, “if” and “if” all refer to the device making a corresponding action under certain objective circumstances, and are not time-limited, nor do they require the device to make a judgment when it is implemented, nor do they mean that there are other limitations.
[0048] In this application, determining information D based on information C includes both determining information D based on information C itself and determining information D based on information C and other information. Furthermore, the use of information C to determine information D can also include indirect determination, such as when information D is determined based on information E, and information E is determined based on information C.
[0049] The technical solution provided in this application can be applied to the detection of concealed devices in scenarios such as hotels, offices, and airplanes. With the development of technology, various concealed devices are emerging, such as eavesdropping devices and hidden cameras. The existence of these concealed devices seriously infringes on personal privacy and may endanger social and even national security. By detecting abnormal signals in the environment, the presence of concealed devices can be determined. Please refer to Figure 1, which is a schematic diagram of an application scenario provided according to one or more embodiments of this application. As shown in Figure 1, the concealed device 100 can transmit data to the terminal device 102 or the access network device 104 via radio waves. These radio waves can be detected by other communication devices in the environment, such as the terminal device 106 in the figure. In addition to receiving radio waves from the concealed device 100, the terminal device 106 can also receive radio waves from other devices, such as those from televisions, routers, base stations, etc. The terminal device 106 can detect and analyze the received radio waves to discover abnormal signals, thereby further detecting the concealed device emitting the abnormal signals.
[0050] It is understood that the covert device in this application can be a hidden wireless device, referring to a device that uses radio waves to transmit information / data.
[0051] Terminal equipment, also known as user equipment (UE), mobile station (MS), or mobile terminal (MT), refers to devices that provide voice and / or data connectivity to users. Examples include handheld devices and in-vehicle devices with wireless connectivity. Currently, some examples of terminal equipment include: mobile phones, tablets, laptops, PDAs, mobile internet devices (MIDs), wearable devices, virtual reality (VR) devices, augmented reality (AR) devices, wireless terminals in industrial control, self-driving, remote medical surgery, smart grids, transportation safety, smart cities, and smart homes.
[0052] The following is a brief introduction to the relevant terms used in this application.
[0053] 1. Received Signal Strength Indicator (RSSI)
[0054] RSSI (Signal Strength Index) is a metric used in wireless communication to measure signal strength, typically expressed in dBm (decibels per milliwatt). RSSI measurements are usually performed by the receiver's network interface card (NIC) and provided to the upper layer via the PMD_RSSI.indicate interface. In wireless communication networks, the RSSI value is used to measure signal strength.
[0055] RSSI is a relative measurement value. After receiving a signal, a communication device can calculate the RSSI based on the signal's power. RSSI values are usually negative; the larger the value (i.e., the closer to 0), the stronger the signal. The formula for calculating RSSI is: Among them, P 接收 This indicates the power of the signal received by the communication device.
[0056] II. Communication Standards
[0057] A communication standard refers to the set of signal transmission methods, protocols, and standards in a communication system. Different communication standards are suitable for different application scenarios and needs. The communication standards in this application may include second-generation (2G), third-generation (3G), fourth-generation (4G), or fifth-generation (5G) mobile communication standards. Under different communication standards, communication devices can communicate on different frequency bands. Under one communication standard, a communication device supports one or more frequency bands, and a frequency band includes multiple frequency points.
[0058] For example, 5G frequency bands may include bands such as n1, n3, n28, n41, n77, n78, and n79. Taking band n1 as an example, the uplink communication frequency range is 1920MHz-1980MHz, and the downlink communication frequency range is 211MHz-2170MHz. Based on fixed frequency intervals, the frequency band can be divided into multiple frequency points.
[0059] In this application, unless otherwise specified, the same or similar parts between various embodiments or implementations can be referred to each other. In the various embodiments of this application, and in the various implementation methods / methods / implementations within each embodiment, unless otherwise specified or logically conflicting, the terminology and / or descriptions between different embodiments and between the various implementation methods / methods / implementations within each embodiment are consistent and can be mutually referenced. The technical features in different embodiments and the various implementation methods / methods / implementations within each embodiment can be combined according to their inherent logical relationships to form new embodiments, implementation methods, methods, or implementation approaches. The embodiments described below do not constitute a limitation on the scope of protection of this application.
[0060] In one possible implementation, the communication device in this application can be a terminal device with mobile communication capabilities. For example, the communication device in this application can be the terminal device 106 in FIG1.
[0061] Referring to Figure 2, which is a flowchart illustrating a method for detecting abnormal signals according to one or more embodiments of this application, it should be understood that although the steps in the flowchart of Figure 2 are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the figure may include multiple sub-steps or multiple stages, which are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.
[0062] As shown in Figure 2, the method for detecting abnormal signals includes, but is not limited to, the following steps:
[0063] S200: The communication equipment disconnects from the access network equipment and controls the transmission or reception of signals via AT commands.
[0064] In one possible implementation, the user can remove the SIM card from the communication device or set the communication device to airplane mode. In response to the user's operation, the communication device can enter a non-signaling mode, meaning it disconnects from the access network device and controls the transmission or reception of signals via AT commands. In other words, in this embodiment, after the communication device disconnects from the access network device, all subsequent actions / steps of the communication device are controlled by commands.
[0065] In another possible implementation, the communication device sends an AT command to the mobile communication module. Upon receiving the AT command, the mobile communication module disconnects from the access network device. The communication device controls the mobile communication module to send or receive signals via AT commands.
[0066] S202, When the communication device disconnects from the access network device, obtain the M frequency points supported by the communication device. M is a positive integer.
[0067] In one possible implementation, after the communication device disconnects from the access network device, the communication device can acquire M frequency points it supports. These M frequency points can be frequency points included in all frequency bands supported by the communication device, or they can be frequency points included in some frequency bands supported by the communication device; this application embodiment is not limited. For example, the communication device supports one or more communication standards, which may include one or more of 2G, 3G, 4G, or 5G. Under one communication standard, the communication device supports one or more frequency bands. A frequency band may include one or more frequency points, and the frequency interval between two adjacent frequency points is a fixed value, such as 200kHz. The aforementioned M frequency points may be frequency points under a certain communication standard, or the M frequency points may be frequency points under all communication standards supported by the communication device. This application embodiment is not limited.
[0068] It is understandable that when manufacturers produce communication equipment, they will pre-configure the communication standards supported by the communication equipment and the corresponding frequency band list, and store them in the communication equipment.
[0069] In one possible implementation, the communication device can use commands to look up a locally stored list of communication standards and their corresponding frequency bands. One of these frequency band lists includes one or more frequency bands. For example, the communication device can send command 1 to the mobile communication module to obtain one or more communication standards supported by the device. Then, the communication device can send command 2 to the mobile communication module, which includes a specific communication standard and is used to obtain the frequency band list corresponding to that standard. The communication device can send multiple commands 2 to the mobile communication module to obtain frequency band lists corresponding to various communication standards. The frequency band lists supported by the communication device are not entirely the same under different communication standards. For example, under the 5G communication standard, the frequency bands supported by the communication device mainly include: n1, n3, n28, n41, n77, n78, and n79.
[0070] After obtaining a list of frequency bands corresponding to one or more communication standards, a communication device can determine M frequency points from this list. The frequency interval between any two adjacent frequency points is a fixed value. For example, the communication device can divide the frequency bands included in the list of frequency bands corresponding to one or more communication standards into multiple frequency points according to a fixed frequency interval, resulting in a total of M frequency points.
[0071] S204 measures the RSSI at M frequency points to obtain N RSSI values. N is an integer greater than or equal to M.
[0072] In one possible implementation, the communication device can measure the RSSI values at the aforementioned M frequency points respectively. For example, the communication device can measure once at a frequency point to obtain M RSSI values. Alternatively, the communication device can measure multiple times at a frequency point to obtain N RSSI values, where N is greater than or equal to M. It is understood that to reduce power consumption, the communication device will not continuously scan the signals at the frequency points. In other words, the communication device can intermittently scan the signals at the frequency points according to a pre-set scanning period. Since the period of the signal transmitted by the covert device is unknown and not synchronized with the scanning period of the communication device beforehand, if the communication device measures only once at a certain frequency point, it may not measure an RSSI value. In other words, even if an abnormal signal exists, the communication device may not be able to scan for the abnormal signal at all times. Therefore, the communication device in this embodiment intermittently measures multiple times at a frequency point to increase the probability of measuring an RSSI value, thereby increasing the probability of detecting abnormal signals and improving the accuracy of covert device detection.
[0073] When a communication device takes multiple measurements on a frequency point, the RSSI values measured at different time points may be different. Therefore, the communication device in this application embodiment can save the maximum RSSI value on that frequency point for subsequent analysis.
[0074] S206, based on the N RSSI values measured at M frequency points, determine whether there are abnormal signals in the environment.
[0075] In one possible implementation, the communication device compares N RSSI values with a preset threshold. When any of these N RSSI values is greater than or equal to the preset threshold, the communication device determines that an abnormal signal exists in the environment, i.e., a hidden device exists. When all N RSSI values are less than the preset threshold, the communication device determines that no abnormal signal exists in the environment, i.e., no hidden device exists. It can be understood that when multiple RSSI values are greater than or equal to the preset threshold, it indicates the presence of multiple abnormal signals in the environment, but these multiple abnormal signals may belong to the same hidden device. The preset threshold can be pre-set in the communication device.
[0076] In one possible implementation, after step S206 above, the method of this embodiment may further include: the communication device plotting and outputting a measurement result graph based on the M frequency points and the RSSI values measured at these M frequency points. The horizontal axis of the measurement result graph represents the frequency point / frequency, and the vertical axis represents the RSSI value.
[0077] In one possible implementation, if the communication device measures multiple times at each of the M frequency points to obtain the maximum RSSI value of the received signal at each frequency point, the communication device can compare the maximum RSSI value of the received signal at each frequency point with a preset threshold. If the maximum RSSI value of the received signal at any of the M frequency points is greater than or equal to the preset threshold, it is determined that an abnormal signal exists in the environment, i.e., a hidden device exists in the environment. If the maximum RSSI value of the received signal at all of the M frequency points is less than the preset threshold, it is determined that no abnormal signal exists in the environment, i.e., no hidden device exists in the environment. This embodiment compares the maximum RSSI value measured at each frequency point with the preset threshold, which can improve the accuracy of detection.
[0078] In one possible implementation, embodiments of this application can also utilize a machine learning model to analyze whether abnormal signals or covert devices exist in the environment. This machine learning model can be pre-trained. The data used during training can include: multiple pre-set frequency points, and RSSI values of various signals (including signals emitted by covert devices, signals emitted by uncovered devices, and / or environmental noise) collected on these frequency points. In other words, during the training phase of the machine learning model, the RSSI value and the frequency point from which the RSSI value is measured can be used as input, with a label of 0 or 1 as the output. The label for the frequency point containing abnormal signals (such as signals emitted by covert devices) is 1, and the label for the frequency points containing other signals (such as signals emitted by uncovered devices like mobile phones and base stations, environmental noise, etc.) is 0. After the machine learning model is trained, N RSSI values collected by the communication device and the frequency points corresponding to these N RSSI values can be input into the machine learning model for processing to obtain the output result. This output result includes the probability that an abnormal signal exists on each of the M frequency points. In other words, this output result includes the probability that each frequency point is labeled "1". Communication devices can determine the presence of abnormal signals in the environment based on the output of a machine learning model. For example, if the probability of an abnormal signal at a certain frequency point in the machine learning model's output is greater than a threshold, such as 0.8, then an abnormal signal is determined to exist in the environment, meaning a hidden device exists. If the probability of an abnormal signal at all M frequency points in the machine learning model's output is less than the threshold, then no abnormal signal is determined to exist in the environment, meaning no hidden device exists.
[0079] To improve accuracy, the abnormal signal can be further analyzed by combining it with a preset threshold value. When the probability of an abnormal signal at a certain frequency point in the output of the machine learning model is greater than the threshold, the RSSI value measured at that frequency point is obtained, and the RSSI value is compared with the preset threshold value. If the RSSI value is greater than or equal to the preset threshold value, it is determined that there is an abnormal signal in the environment, that is, there is a hidden device in the environment.
[0080] The aforementioned machine learning models may include decision trees, random forests, or neural networks.
[0081] This application uses a machine learning model to analyze whether there are abnormal signals in the environment, which can quickly eliminate common interference signals and further improve the accuracy of detecting covert devices.
[0082] In one possible implementation, the communication device can also determine the presence of abnormal signals in the environment based on whether there are significant jumps in the measured RSSI values. For example, the average of the RSSI values measured at M frequency points is calculated, and then the average value is compared with the RSSI value at each frequency point. If the RSSI value at a certain frequency point is much larger than the average value (for example, the difference between the RSSI value at this frequency point and the average value is greater than a certain value), it indicates that a significant jump has occurred. Therefore, it can be determined that there are abnormal signals in the environment, i.e., the presence of concealed devices.
[0083] It's understandable that, although transmission and reception in mobile communication may occur on different frequencies, they can still be measured by receiving channels of different frequency bands or standards. Even if the frequency band measured by the communication equipment does not cover the actual frequency of the abnormal signal, the out-of-band noise RSSI of the abnormal signal can still be measured.
[0084] In one possible implementation, when the communication device determines that an abnormal signal / covert device exists in the environment, it can further locate the position of the covert device. For example, the method in this embodiment may further include steps S208 and S210.
[0085] S208, If an abnormal signal exists in the environment, measure the RSSI at the frequency point where the abnormal signal is located at multiple locations to obtain the RSSI values corresponding to multiple locations. Each location corresponds to at least one RSSI value.
[0086] In one possible implementation, if an abnormal signal exists in the environment, indicating the presence of a concealed device, the communication device can further determine the target frequency point where the abnormal signal is located. The user can move the communication device indoors, and the device can measure the RSSI at the target frequency point at multiple locations, obtaining the RSSI values corresponding to these multiple locations. It is understood that, to improve measurement accuracy, multiple measurements can be taken at a single location for the target frequency point, and the maximum RSSI value corresponding to each location can be saved.
[0087] S210, determine the location closest to the concealed device based on the RSSI values corresponding to multiple locations. The concealed device is the device that sends abnormal signals, and the location closest to the concealed device corresponds to the largest RSSI value.
[0088] In one possible implementation, the communication device can determine the location closest to the covert device based on the RSSI values corresponding to these multiple locations. The covert device is the one that sends the abnormal signal, and the location closest to the covert device has the highest RSSI value.
[0089] For example, in a test space (such as a room or a car), the SIM card of a communication device (such as a mobile phone) with two antennas is removed (i.e., switched to airplane mode). At this time, the communication device is disconnected from the access network device (such as a base station). The user can use AT commands to set the scanning frequency band of the communication device to 800MHz to 5.8GHz, and the scanning interval to 100 milliseconds. To reduce interference, the user can turn off other known communication devices in the test space (such as mobile phones, wireless routers, or Bluetooth headsets). Please refer to Figure 3, which is a schematic diagram of RSSI measurement results at multiple frequency points according to one or more embodiments of this application. As shown in Figure 3, the RSSI of the signals received by antenna 1 (i.e., Ant1) and antenna 2 (i.e., Ant2) both show a significant jump around 1.847GHz. Therefore, it can be determined that the signal with a measured RSSI of -50dBm is an abnormal signal, and the frequency point of the abnormal signal is 1.847GHz. Based on this information, the scanning frequency can be locked at 1.847 GHz. Then, continuous single-frequency scanning can be performed at different locations within the test space to determine the location with the highest RSSI. This location with the highest RSSI is the closest location to the concealed device.
[0090] This application utilizes existing communication equipment to measure RSSI on multiple supported frequency points and analyzes the measured RSSI to determine whether abnormal signals exist in the environment, thereby identifying the presence of hidden wireless devices. No additional hardware or software development is required, saving costs while efficiently and accurately detecting hidden wireless devices in the environment and protecting user privacy.
[0091] The methods of the embodiments of this application have been described in detail above, and the devices of the embodiments of this application are provided below.
[0092] Please refer to Figure 4, which is a schematic diagram of a communication device provided according to one or more embodiments of this application. The communication device may include:
[0093] The acquisition module 400 is used to acquire M frequency points supported by the communication device when the communication device is disconnected from the access network device, where M is a positive integer;
[0094] Measurement module 402 is used to measure RSSI at M frequency points respectively and obtain N RSSI values, where N is an integer greater than or equal to M;
[0095] The determination module 404 is used to determine whether there is an abnormal signal in the environment based on N RSSI values, wherein the RSSI value at the frequency point where the abnormal signal is located is greater than or equal to a preset threshold value.
[0096] In one possible implementation, the acquisition module 400 is specifically used to: acquire a list of frequency bands corresponding to at least one communication standard supported by the communication device; and determine M frequency points from the list of frequency bands corresponding to at least one communication standard, wherein the frequency interval between two adjacent frequency points is a fixed value.
[0097] In one possible implementation, the measurement module 402 is specifically used to: perform multiple measurements at each of the M frequency points to obtain the maximum RSSI of the received signal at each frequency point. The determination module 404 is specifically used to: determine whether an abnormal signal exists based on the maximum RSSI of the received signal at each frequency point.
[0098] In one possible implementation, the determining module 404 is further specifically used to: compare the maximum RSSI of the signal received at each frequency point with the preset threshold value; when the maximum RSSI of the signal received at one of the M frequency points is greater than or equal to the preset threshold value, it is determined that there is an abnormal signal in the environment.
[0099] In one possible implementation, the determining module 404 is specifically used to: input the N RSSI values and the frequency points corresponding to the N RSSI values into a trained machine learning model for processing, obtain the output result of the machine learning model, the output result including the probability of an abnormal signal on each of the M frequency points; and determine whether an abnormal signal exists in the environment based on the output result of the machine learning model.
[0100] In one possible implementation, the determining module 404 is further configured to determine the target frequency point where the abnormal signal is located. The measuring module 402 is further configured to measure the RSSI at the target frequency point at multiple locations to obtain RSSI values corresponding to multiple locations, wherein one location corresponds to at least one RSSI value. The determining module 404 is further configured to determine the location closest to the concealed device, which is the device that sent the abnormal signal, based on the RSSI values corresponding to the multiple locations, and the location closest to the concealed device has the largest RSSI value.
[0101] In one possible implementation, the communication device further includes a response module 406. This response module 406 is used to disconnect from the access network device in response to a user's operation or upon receiving an AT command.
[0102] In specific implementation, the above-mentioned communication device can execute the steps or methods performed by the communication device in Figure 2 through the above-mentioned modules to achieve the functions implemented in the above-mentioned method embodiments. For details, please refer to the corresponding descriptions provided for each step in the method embodiments shown in Figure 2 above, which will not be repeated here.
[0103] In this embodiment, when the communication device disconnects from the access network device, the acquisition module 400 acquires M frequency points supported by the communication device; the measurement module 402 measures the RSSI on each of the M frequency points to obtain N RSSI values; and the determination module 404 determines whether there is an abnormal signal in the environment based on the N RSSI values, wherein the RSSI value on the frequency point where the abnormal signal is located is greater than or equal to a preset threshold. This method can efficiently and accurately detect the presence of hidden wireless devices in the environment while saving costs and protecting user privacy.
[0104] Each module in the aforementioned communication device can be implemented entirely or partially through software, hardware, or a combination thereof. Specifically, each module can be embedded in the processor of the communication device in hardware form or independent of it, or it can be stored in the memory of the communication device in software form, so that the processor can call and execute the operations corresponding to each module.
[0105] Please refer to Figure 5, which is a schematic diagram of another structure of a communication device provided according to one or more embodiments of this application. As shown in Figure 5, the communication device provided in this application includes: at least one communication bus 500, at least one processor 502, such as a CPU, a memory 504, a user interface 506, and at least one communication interface 508. The communication bus 500 is used to implement communication between these components. The user interface 506 may include a display screen, and the communication interface 508 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 504 may be a high-speed RAM memory or a non-volatile memory, such as at least one disk storage device. Optionally, the memory 504 may also be at least one storage device located remotely from the aforementioned processor 502. As shown in Figure 5, the memory 504, as a computer storage medium, may include an operating system, a network communication module, a user interface module, and a device control application.
[0106] In the terminal device shown in Figure 5, the communication interface 508 provides network communication functionality; while the user interface 506 is mainly used to provide an input interface for the user; in the communication device shown in Figure 5, the processor 502 can be used to load program instructions stored in the memory 504 and specifically perform the following operations:
[0107] When the communication device disconnects from the access network device, the following steps are taken: M frequency points supported by the communication device are obtained, where M is a positive integer; RSSI on each of the M frequency points is measured to obtain N RSSI values, where N is an integer greater than or equal to M; based on the N RSSI values, it is determined whether there are abnormal signals in the environment, and the RSSI value on the frequency point where the abnormal signal is located is greater than or equal to a preset threshold value.
[0108] It is understood that the communication device described in the embodiments of this application can be used to execute the method of the embodiment shown in FIG2 above. The beneficial effects of using the same method will not be repeated here.
[0109] This application also provides a computer storage medium for storing a computer program. When the computer program is run on a terminal device, the communication device can execute the methods or steps of the embodiment shown in FIG2 above.
[0110] This application also provides a computer program product or computer program that includes computer instructions stored in a computer-readable storage medium. A processor of a communication device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, enabling the communication device to perform the method of the embodiment shown in FIG2 above, which will not be described again here.
[0111] As used in this application, the terms "component," "module," and "system," etc., are intended to refer to computer-related entities, which can be hardware, a hardware and software assembly, software, or software in execution. For example, a component can be, but is not limited to, a process running on a processor, a processor, an object, executable code, an executing thread, a program, and / or a computer. For illustration, an application running on a server and the server itself can both be components. One or more components may reside in a process and / or an executing thread, and components may be located within a single computer and / or distributed across two or more computers.
[0112] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.
[0113] In summary, the above are merely preferred embodiments of the technical solutions of this application and are not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.
Claims
1. A method for detecting abnormal signals, applied to a communication device, comprising: When the communication device disconnects from the access network device, the M frequency points supported by the communication device are obtained, where M is a positive integer; Measure the Received Signal Strength Indication (RSSI) at the M frequency points respectively to obtain N RSSI values, where N is an integer greater than or equal to M; Based on the N RSSI values, it is determined whether there is an abnormal signal in the environment, wherein the RSSI value at the frequency point where the abnormal signal is located is greater than or equal to a preset threshold value.
2. The method according to claim 1, characterized in that, The step of obtaining the M frequency points supported by the communication device includes: Obtain a list of frequency bands corresponding to at least one communication standard supported by the communication device; M frequency points are determined from the frequency band list corresponding to the at least one communication standard, wherein the frequency interval between two adjacent frequency points is a fixed value.
3. The method according to claim 1 or 2, characterized in that, The step of measuring the Received Signal Strength Indication (RSSI) at the M frequency points to obtain N RSSI values includes: Measure multiple times at each of the M frequency points to obtain the maximum RSSI value of the received signal at each frequency point; Based on the N RSSI values, determine whether there are abnormal signals in the environment, including: Based on the maximum RSSI value of the signal received at each frequency point, determine whether there is an abnormal signal.
4. The method according to claim 3, characterized in that, The step of determining whether there is an abnormal signal based on the maximum RSSI value of the signal received at each frequency point includes: The maximum RSSI value of the signal received at each frequency point is compared with the preset threshold value; When the maximum RSSI value of the signal received at one of the M frequency points is greater than or equal to a preset threshold, it is determined that there is an abnormal signal in the environment.
5. The method according to claim 1 or 2, characterized in that, The step of determining whether there are abnormal signals in the environment based on the N RSSI values includes: The N RSSI values and the frequency points corresponding to the N RSSI values are input into the trained machine learning model for processing to obtain the output results of the machine learning model. The output results include the probability that there is an abnormal signal at each of the M frequency points. Based on the output of the machine learning model, determine whether there are abnormal signals in the environment.
6. The method according to claim 1 or 2, characterized in that, The method further includes: When an abnormal signal is present in the environment, the target frequency point where the abnormal signal is located is determined; RSSI at the target frequency point is measured at multiple locations to obtain RSSI values corresponding to the multiple locations, where each location corresponds to at least one RSSI value; Based on the RSSI values corresponding to the multiple locations, the location closest to the concealed device is determined. The concealed device is the device that sends the abnormal signal, and the location closest to the concealed device has the largest RSSI value.
7. The method according to claim 1 or 2, characterized in that, Before obtaining the M frequency points supported by the communication device, the method further includes: In response to user actions or receiving a notification AT command, disconnect from the access network device.
8. A communication device, comprising: The acquisition module is used to acquire M frequency points supported by the communication device when the communication device is disconnected from the access network device, where M is a positive integer; The measurement module is used to measure the Received Signal Strength Indication (RSSI) at the M frequency points respectively, and obtain N RSSI values, where N is an integer greater than or equal to M; The determination module is used to determine whether there is an abnormal signal in the environment based on the N RSSI values, wherein the RSSI value at the frequency point where the abnormal signal is located is greater than or equal to a preset threshold value.
9. A communication device, comprising: Processor, memory, and communication interface; The processor is connected to a memory and a communication interface, wherein the communication interface is used to provide data communication functions, the memory is used to store computer programs, and the processor is used to invoke the computer programs to cause the communication device to perform the method as described in any one of claims 1-7.
10. A computer-readable storage medium storing a computer program, the computer program being loaded and executed by a processor to cause a communication device having the processor to perform the method as described in any one of claims 1-7.