A remote data communication method and system for an electronic seal device

Abstract

The application relates to the technical field of remote data communication, in particular to a remote data communication method and system for an electronic seal device, which comprises the following steps: acquiring current signals, magnetic field electric signals and infrared electric signals of each local period in each communication section, judging seal states of the local periods, acquiring signal-to-noise ratios of uplink channels in the local periods, and transmission time delays and signal strengths at each moment; calculating first interference values, second interference values and misjudgment risk degrees of the local periods, and dividing priorities of all the local periods in each communication section; determining first risk values, second risk values and channel risk degrees of the local periods, and identifying low-risk periods; encrypting all signals and seal states, forming a sending queue according to the priorities, and transmitting to a remote monitoring terminal in the low-risk periods. The application ensures that the remote monitoring terminal can timely master the real state of transported goods, so as to accurately identify illegal opening of the electronic seal.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of remote data communication, in particular to a remote data communication method and system for an electronic seal device. BACKGROUND

[0002] With the development of Internet technology, electronic seals using RFID technology have gradually emerged. In the fields of modern logistics transportation and warehouse management, the electronic seals can effectively monitor the sealing state of goods, meeting the demand for real-time and accurate monitoring of the sealing state. The electronic seal device is usually used to monitor the safety of goods in the transportation process by detecting whether the seal is damaged through a sensor.

[0003] The existing electronic seal device has a single function and usually relies on a single sensor to monitor the sealing state. In a complex goods transportation environment, continuous transportation vibration and dust intrusion can easily cause the sensor to produce false alarms, causing interference to the real sealing state information. In addition, an open wireless channel is vulnerable to network attacks such as pseudo base station decoying and data tampering in remote or complex electromagnetic environments, resulting in malicious forgery or loss of critical state information, making it difficult to timely grasp the real state of the transported goods, increasing the risk of attackers forging normal state data of the sensor in the electronic seal device, and failing to accurately identify illegal opening of the electronic seal. SUMMARY

[0004] In order to solve the above technical problems, a remote data communication method and system for an electronic seal device are provided to solve the existing problems.

[0005] The technical problem of the present application is solved by providing a remote data communication method and system for an electronic seal device, comprising the following steps:

[0006] In a first aspect, the present application provides a remote data communication method for an electronic seal device, comprising the following steps:

[0007] Obtain the current signal, the magnetic field electric signal and the infrared electric signal of each local period in each communication section, and determine the sealing state of each local period, obtain the signal-to-noise ratio of the uplink channel in each local period, and the transmission delay and signal strength at each time;

[0008] Analyze the trend change of the magnetic field electric signal and the infrared electric signal, and calculate the first interference value of each local period;

[0009] The second interference value of each local time period is calculated through the periodic characteristics of the current signal change, the abnormal fluctuation of the infrared electric signal, and the synchronization of the abnormal change time between the magnetic field electric signal and the infrared electric signal. The misjudgment risk degree of each local time period is obtained in combination with the first interference value. Each communication section is prioritized in combination with the sealing state of each local time period;

[0010] The first risk value of each local time period is determined by analyzing the fluctuation of the transmission delay and the attenuation of the signal-to-noise ratio in each local time period. The channel risk degree of each local time period is obtained in combination with the extreme change range of the signal strength and the trend difference between the transmission delay and the signal strength in each local time period. The low-risk time period of the next communication section is identified.

[0011] All signals and sealing states of each local time period are encrypted. The sending queue is formed according to the priority. The encrypted data is transmitted to the remote monitoring terminal in the low-risk time period of the next communication section according to the order of the sending queue.

[0012] Preferably, the sealing state of each local time period is determined, including: if each local time period meets any determination condition, the sealing state is abnormal, and the local time period is recorded as an opening time period; otherwise, the sealing state is normal, and the local time period is recorded as a non-opening time period. The determination condition is that all signal strengths in the magnetic field electric signal are 0, or all signal strengths in the infrared electric signal are 0, or all non-0 in the current signal.

[0013] Preferably, the first interference value of each local time period is calculated, including:

[0014] The trend of the magnetic field electric signal and the infrared electric signal is decomposed and the trend strength is calculated, respectively recorded as the first trend degree and the second trend degree.

[0015] The first interference value is the sum of the first trend degree and the second trend degree.

[0016] Preferably, the second interference value of each local time period is calculated, including:

[0017] The autocorrelation coefficients of the current signal of multiple preset lag orders are obtained, and the mean of all autocorrelation coefficients is calculated as the autocorrelation strength of each local time period.

[0018] The signal strength of all time points in the infrared electric signal is detected for abnormality to obtain abnormal time points. The dispersion degree of the signal strength of all abnormal time points is calculated and recorded as the abnormal fluctuation degree.

[0019] The time points with signal strength of 0 in the magnetic field electric signal are counted and recorded as significant time points. The correlation degree between all significant time points and all abnormal time points in each local time period is calculated as the time synchronization degree of each local time period.

[0020] The second disturbance value is the product of autocorrelation strength, abnormal volatility, and time synchronization.

[0021] Preferably, the risk of misjudgment is the normalized result of the product of the first interference value and the second interference value.

[0022] Preferably, the prioritization of all local time periods within each communication segment includes: designating all open time periods within each communication segment as a high-priority group and all closed time periods as a secondary-priority group; arranging all open time periods within the high-priority group in ascending order of time, and arranging all closed time periods within the secondary-priority group in descending order of misjudgment risk; and arranging all open time periods and all closed time periods in the order of high-priority group first and secondary-priority group last, and assigning priorities accordingly.

[0023] Preferably, determining the first risk value for each local time period includes:

[0024] Obtain the peaks and troughs of the transmission delay of the uplink channel at all times within each local time period; calculate the difference between the peak value of each peak and the trough value of its adjacent peak, and record it as the delay deviation; take the dispersion of the delay deviation of all peaks within each local time period as the delay fluctuation of each local time period.

[0025] Negative mapping is applied to the difference in signal-to-noise ratio between each local time period and the previous local time period of the uplink channel;

[0026] The first risk value is the product of the time delay volatility and the result of the negative mapping.

[0027] Preferably, obtaining the channel risk level for each local time period includes:

[0028] Calculate the range of signal strength of the uplink channel at all times within each local time period; calculate the distance between the transmission delay and signal strength of the uplink channel at all times within each local time period; and use the product of the range and the distance as the second risk value for each local time period.

[0029] The channel risk level is the normalized result of the product of the first risk value and the second risk value.

[0030] Preferably, identifying the low-risk period of the next communication segment includes: obtaining the segmentation threshold of the channel risk level for all local time periods within each communication segment; and designating the local time periods within the next communication segment where the channel risk level is less than the segmentation threshold as low-risk time periods.

[0031] Secondly, embodiments of this application also provide a remote data communication system for an electronic signature device, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of the remote data communication method for an electronic signature device described above.

[0032] This application has at least the following beneficial effects:

[0033] This application analyzes the attenuation trends of magnetic field and infrared electrical signals, and calculates the first interference value for each local time period. Its advantage lies in considering the changing trends of the magnetic field and infrared electrical signals, reflecting the obstruction and interference of dust in the transportation environment on the sensor, and assessing the risk of signal blocking and shielding caused by transportation environment interference to the magnetic field or infrared electrical signals. Calculating the second interference value for each local time period has the advantage of considering the periodicity of the current signal and the abnormal fluctuations of the infrared electrical signal, as well as the abnormal synchronization between the magnetic field and infrared electrical signals, reflecting the impact of transportation vibrations on the sensor. The study investigates the impact of sensor interference, obtaining the risk of misjudgment for each local time period. Its beneficial effect lies in comprehensively assessing the impact of transportation environment interference on the electronic sealing device during transport by comprehensively evaluating signals collected from multiple sensors, reflecting the possibility of misjudgment of the sealing status, and avoiding false alarms from a single sensor. It also determines the first risk value for each local time period, which is beneficial because it considers channel transmission delay jitter and signal-to-noise ratio attenuation, reflecting channel quality degradation and assessing the risk of the channel being subjected to active network attacks. Finally, it obtains the channel risk level for each local time period, which is beneficial because it considers signal strength fluctuations and... The disruption of the correlation between transmission delay and signal strength reflects the risk level of spoofing attacks by fake base stations. Combined with the first risk value, this comprehensively illustrates the risk level of data tampering and spoofing attacks during remote data communication, demonstrating the security of the transmission channel. Prioritizing all local time periods within each communication segment has the advantage of identifying the true opening status and prioritizing all local time periods based on the risk of misjudgment. Encrypting all signals and sealing statuses within each local time period and forming a transmission queue based on the priority ensures that subsequent sealing status anomalies are prioritized. Prioritizing the transmission of information from electronic seals that are in normal condition but pose a high risk of misinterpretation ensures that the true critical status information of the electronic seal device is transmitted preferentially within available channel resources. Identifying low-risk periods in the next communication segment and transmitting encrypted data to the remote monitoring terminal in the order of the transmission queue during these periods offers several advantages. Transmitting data during low-risk periods avoids the risk of critical information being intercepted or tampered with during transmission, reduces the risk of data exposure on insecure channels, and ensures that the remote monitoring terminal can promptly grasp the true status of the transported goods to accurately identify unauthorized opening of the electronic seal. Attached Figure Description

[0034] The following description, in conjunction with the accompanying drawings, provides a more detailed explanation of a remote data communication method for an electronic signature device according to this application.

[0035] Figure 1 A flowchart illustrating the steps of a remote data communication method for an electronic signature device provided in this application embodiment;

[0036] Figure 2 A flowchart illustrating the steps of the method for obtaining the misjudgment risk level for each local time period provided in the embodiments of this application;

[0037] Figure 3 A flowchart illustrating the steps of the method for obtaining the channel risk level for each local time period provided in the embodiments of this application. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description, in conjunction with the accompanying drawings and embodiments, provides a remote data communication method and system for electronic signature devices. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0039] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0040] Please see Figure 1 The diagram illustrates a flowchart of a remote data communication method for an electronic signature device according to an embodiment of this application. The method includes the following steps:

[0041] Step 1: Obtain the current signal, magnetic field signal, and infrared signal for each local time period within each communication segment, determine the sealing status for each local time period, obtain the signal-to-noise ratio of the uplink channel for each local time period, and the transmission delay and signal strength at each moment.

[0042] An electronic seal is a specialized integrated circuit (ASIC) with a dedicated packaging structure and an embedded digital IC chip, making it one of the most widely used IC card chips. It integrates RFID (Radio Frequency Identification) technology, electronic serial number (ID) anti-counterfeiting ICs, and a ring-shaped multiple-use mechanical structure to create a high-security, low-cost, and automatically identifiable digital electronic lock. It can be applied to various devices, fundamentally solving the problems of pure mechanical seals being easily counterfeited, forged, illegally replaced, difficult to automatically identify, and prone to lead contamination; it also solves the problems of ordinary mechanical seals being easily opened illegally and unable to be authenticated after resealing. By using electronic seals as digital or physical sealing devices in logistics, transportation, or important document management, it ensures that items are not tampered with or illegally opened during transit.

[0043] Based on the above analysis, in this embodiment, the electronic signature device includes a main control module, an air pump switch detection module, a magnetic sensor module, an infrared grating detection module, a power supply module, and a communication module, specifically:

[0044] The main control module is connected to the air pump switch detection module, magnetic attraction detection module, infrared grating detection module, power supply module, data analysis module and communication module. It is used to receive signals collected by different detection modules and analyze and process them to determine the sealing status. At the same time, it sends the collected signals and sealing status information to the remote monitoring terminal through the communication module.

[0045] Air pump switch detection module: Used to detect the on / off state of the air pump. Specifically, it determines whether the air pump is on or off by detecting the change in current in the air pump circuit. When the air pump is on, there is current flowing through the air pump circuit, and the air pump switch detection module will transmit the detected current signal to the main control module. Conversely, when there is no current flowing through the air pump circuit, the air pump switch detection module will transmit the current signal 0 to the main control module.

[0046] Magnetic attraction detection module: includes a magnetic attraction sensor and a magnetic attraction block. The magnetic attraction sensor is installed on the main body of the sealing device, and the magnetic attraction block is installed at the corresponding position of the monitored door. When the monitored door is closed, the magnetic attraction detection module detects the magnetic field signal, converts it into an electrical signal, and transmits it to the main control module. When the monitored door is opened, the magnetic attraction sensor separates from the magnetic attraction block, the magnetic field signal disappears, and the corresponding electrical signal 0 is sent to indicate that the monitored door is open.

[0047] Infrared grating detection module: This module includes an infrared transmitter and an infrared receiver, which are installed on opposite sides of the monitored door. When the door is closed, the infrared light emitted by the transmitter is successfully received by the receiver, which converts the received light signal into an electrical signal and transmits it to the main control module. Conversely, when the door is open, the receiver is blocked by an object and cannot receive the infrared light, sending a corresponding electrical signal of 0 to indicate that the door is open.

[0048] Power module: Responsible for providing power to the entire electronic signature device. It uses a rechargeable battery to facilitate the use and maintenance of the device.

[0049] Communication module: Uses 5G communication to enable communication between the main control module and the remote monitoring terminal;

[0050] The main control module analyzes all received electrical signals to determine the sealing status. The specific determination process is as follows: when the air pump switch detection module detects the air pump is off, and both the magnetic attraction detection module and the infrared grating detection module detect the monitoring door is closed, the sealing status is determined to be normal. When the air pump switch detection module detects the air pump is on, or the magnetic attraction detection module detects the monitoring door is open, or the infrared grating detection module detects the monitoring door is open, the sealing status is determined to be abnormal. Based on the sealing status determination result, the main control module sends the collected signals and sealing status information to the remote monitoring terminal via the communication module. When the sealing status is normal, normal status information is sent; when the sealing status is abnormal, abnormal status information is sent, along with details such as the time of the abnormality and the specific type of abnormality, such as the air pump being on or the monitoring door being opened.

[0051] It should be noted that the air pump switch detection module, magnetic attraction detection module, and infrared grating detection module collect signals at a frequency of 30Hz. As for other implementation methods, the implementer can set the frequency according to the actual situation.

[0052] However, since the main control module analyzes and judges the sealing status information of the signal, the electronic sealing device may misjudge the sealing status information due to interference from the transportation environment. Secondly, it may also be subject to network attacks during communication transmission, resulting in inaccurate judgment of the sealing status. Therefore, it is necessary to ensure the security of data transmission.

[0053] Based on the above analysis, the electrical signal received by the main control module from the magnetic attraction detection module is denoted as the magnetic field electrical signal; the electrical signal received by the main control module from the infrared grating detection module is denoted as the infrared electrical signal.

[0054] Therefore, multiple moments are treated as a communication segment, and the current signal, magnetic field signal, and infrared signal of each local time period within each communication segment are acquired.

[0055] In this embodiment, the duration of the communication segment is 5 minutes, and the duration of the local time segment is 5 seconds. As for other implementation methods, the implementer can set them according to the actual situation.

[0056] Therefore, when the sealing status is normal during a certain local period, the air pump switch should be detected to be off and the monitoring door should be closed. The current signal during this local period should be 0, while the magnetic field signal and infrared signal should not be 0. Conversely, when the air pump is detected to be on, that is, when the current signal is not 0, or the magnetic field signal or infrared signal is 0, it indicates that the sealing status is abnormal.

[0057] Secondly, a gateway radio frequency unit and UDP-based probe packets are deployed on the communication module to obtain the transmission delay of the uplink channel between the main control module and the remote monitoring terminal at all times in each local time period with a sampling frequency of 30Hz. The signal strength of the uplink channel at all times in each local time period is obtained through the signal acquisition device of the remote monitoring terminal, and the signal-to-noise ratio of the uplink channel in each local time period is calculated.

[0058] It should be noted that the electronic signature device sends UDP probe packets through the uplink channel. The signal acquisition unit directly measures the reference signal received power RSRP and the total received signal power RSSI, thereby calculating the signal-to-noise ratio (SNR) in real time. The average of all SNR values ​​in each local time period is taken as the SNR of the uplink channel in each local time period.

[0059] The collected data is timestamped using a GPS clock and then normalized. In this embodiment, the maximum-minimum normalization method is used. The maximum-minimum normalization method is a well-known technique and will not be described in detail here. As other implementation methods, implementers may use other methods of the prior art, such as Z-Score standardization. This embodiment does not impose any special restrictions on this.

[0060] Therefore, the sealing status of each local time period is determined by the current signal, magnetic field signal, and infrared signal during each local time period, specifically as follows:

[0061] If any of the judgment conditions is met in each local time period, the seal status is abnormal and the local time period is recorded as the door opening time period. Conversely, if the seal status is normal, it is recorded as the non-door opening time period. The judgment conditions are: all signal strengths in the magnetic field signal are 0, or all signal strengths in the infrared signal are 0, or all current signals are non-zero.

[0062] Thus, the current signal, magnetic field signal, and infrared signal of each local time period within each communication segment are obtained, as well as the transmission delay and signal strength of the uplink channel at each moment within each local time period, and the signal-to-noise ratio of the uplink channel at each local time period.

[0063] Step 2: Analyze the trend changes of the magnetic field signal and the infrared signal, and calculate the first interference value for each local time period; through the periodic characteristics of the current signal change, the abnormal fluctuations of the infrared signal, and the synchronicity of the abnormal changes between the magnetic field signal and the infrared signal, calculate the second interference value for each local time period, and combine it with the first interference value to obtain the misjudgment risk level for each local time period.

[0064] Electronic sealing devices are susceptible to interference from complex transportation environments during transit, leading to false alarms. Specifically, the gas switch detection module determines the sealing status by detecting changes in gas pressure, the magnetic attraction detection module uses a Hall effect sensor to detect displacement based on the attenuation of the magnetic field strength to determine the opening / closing status of the monitoring door, and the infrared grating detection module detects the on / off state of the light beam to determine the opening / closing status of the monitoring door. During transportation, unavoidable dust and vibrations are encountered. For example, high-intensity vibrations may cause micro-leakage in the gas path. Even if the gas pump is not turned on, airflow may occur in the gas path, causing the sensor to detect a current signal, resulting in false alarms. Furthermore, dust may adhere to the magnetic attraction sensor. The formation of a magnetic shielding layer weakens or eliminates the magnetic field signal, causing it to be misjudged as open even when the monitoring door is closed. High-intensity vibration may also cause the distance between the magnetic sensor and the magnet to increase instantaneously, causing the magnetic field signal to drop to zero momentarily, resulting in false alarms. Dust may also block the transmission path of infrared light, weakening or eliminating the infrared electrical signal, causing it to be misjudged as open even when the monitoring door is closed. Vibration can also cause micro-displacement at the transmitter and receiver of the infrared grating, resulting in high-frequency fluctuations in the infrared photoelectric signal, making it impossible to accurately distinguish between illegal opening of electronic seals and false alarms caused by environmental interference.

[0065] Furthermore, the flowchart of the method for obtaining the misjudgment risk level for each local time period provided in the embodiments of this application is as follows: Figure 2 As shown.

[0066] Based on the above analysis, when significantly affected by environmental interference such as dust and transport vibration, the signal strength of both infrared and magnetic field signals will attenuate. Simultaneously, transport vibration will cause periodic fluctuations in the current signal, frequent momentary zeroing of the magnetic field signal strength, and significant high-frequency fluctuations in the infrared signal. Therefore, by analyzing the changing trends of the magnetic field and infrared signals, the first interference value is calculated as follows:

[0067] The magnetic field electrical signal is decomposed into trends, and the trend intensity is calculated and denoted as the first trend degree.

[0068] Perform trend decomposition on the infrared electrical signal and calculate the trend intensity, denoted as the second trend degree;

[0069] In this embodiment, the STL (Seasonal and Trend decomposition using Loess) trend decomposition algorithm is used for trend decomposition. The STL trend decomposition algorithm and the calculation of trend strength are well-known techniques and will not be elaborated upon here. The calculation process for trend strength is as follows: the magnetic field electrical signal and infrared electrical signal are decomposed into trend terms and residual terms using the STL trend decomposition algorithm. The formula for calculating trend strength is: ,in, As for trend strength, Let Variance be the variance of the residual term. The variances of the trend term and the residual term, To find the maximum value.

[0070] Calculate the sum of the first trend degree and the second trend degree, and use it as the first disturbance value for each local time period;

[0071] It should be noted that the greater the first or second trend degree, the more obvious the trend of the magnetic field signal or infrared signal, that is, the stronger the trend of the magnetic field signal, the greater the influence of the transportation environment on the magnetic field signal or infrared signal, the higher the risk of signal blocking and shielding, and the greater the obtained first interference value.

[0072] Secondly, the periodic changes of the current signal, the degree of instantaneous zeroing of the magnetic field signal, and the high-frequency fluctuations of the infrared signal are analyzed to calculate the second interference value, specifically:

[0073] The autocorrelation coefficients of the current signal at multiple preset lag orders are obtained, and the mean of all autocorrelation coefficients is calculated as the autocorrelation intensity of each local time period.

[0074] In this embodiment, the autocorrelation function is used to output the autocorrelation coefficient. The autocorrelation function is a well-known technique and will not be described in detail here. The lag order is set to all integers from 1 to 20. As for other implementation methods, the implementer can set it according to the actual situation.

[0075] It should be noted that the higher the autocorrelation strength, the stronger the periodicity of the current signal, and the more severe the micro-leakage and self-recovery of the air pump circuit caused by vibration in the cargo transportation environment.

[0076] The moment when the signal intensity in the statistical magnetic field electrical signal is 0 is denoted as a significant moment.

[0077] Anomaly detection is performed on the signal strength at all times in the infrared electrical signal to obtain the abnormal moments; the dispersion of the signal strength at all abnormal moments is calculated and denoted as the abnormal fluctuation degree.

[0078] In this embodiment, the Bernaola Galvan (BG) segmentation algorithm is used for anomaly detection. The BG segmentation algorithm is a well-known technique and will not be described in detail here. As other implementation methods, implementers can use other existing methods, such as Bayesian mutation detection algorithms, etc. This embodiment does not impose any special restrictions on this. Secondly, the degree of dispersion is measured by calculating the information entropy of the signal strength at all anomaly moments. The calculation of information entropy is a well-known technique and will not be described in detail here. As other implementation methods, implementers can use other existing methods, such as standard deviation, coefficient of variation, etc. This embodiment does not impose any special restrictions on this.

[0079] Calculate the correlation between all significant moments and all abnormal moments in each local time period, and use it as the time synchronization degree of each local time period;

[0080] In this embodiment, the correlation is calculated by measuring the Pearson correlation coefficient between all significant moments and all abnormal moments in each local time period. The calculation of the Pearson correlation coefficient is a well-known technique and will not be described in detail here. As other implementation methods, implementers may use other methods of the prior art, such as Spearman correlation coefficient, etc. This embodiment does not impose any special restrictions on this.

[0081] It should be noted that if the door is truly opened illegally, the magnetic field signal will be significant at all times after the monitoring door is opened, while the infrared signal will be zero. No abnormal moment can be detected, so the correlation is low and the time synchronization is small. However, real and severe transportation vibrations will affect multiple sensors simultaneously and cause them to produce anomalies near the same point in time. Therefore, the greater the time synchronization, the more likely there are synchronous abnormal changes in the infrared and magnetic field signals, and the higher the synchronous influence of transportation vibrations may be.

[0082] The product of autocorrelation strength, abnormal volatility, and time synchronization is used as the second disturbance value for each local time period.

[0083] It should be noted that the greater the abnormal fluctuation, the more severe the fluctuation of the infrared electrical signal and the greater the environmental interference; the greater the second interference value, the more severe the vibration interference in the detection module of the electronic seal device is to the transportation environment.

[0084] Furthermore, based on the first interference value and the second interference value, the risk of misjudgment is determined, specifically as follows:

[0085] The normalized result of the product of the first interference value and the second interference value is used as the misjudgment risk level for each local time period.

[0086] In this embodiment, the sigmoid function is used for normalization. The sigmoid function is a well-known technique and will not be described in detail here. As other implementation methods, implementers may use other methods of the prior art, such as the tanh function. This embodiment does not impose any special restrictions on this.

[0087] It should be noted that the higher the risk of misjudgment, the greater the impact of the transportation environment on the electronic sealing device during transportation, and the higher the possibility of misjudgment.

[0088] Thus, the risk level of misjudgment for each local time period is obtained.

[0089] Step 3: Analyze the fluctuations in transmission delay and the attenuation of signal-to-noise ratio within each local time period to determine the first risk value for each local time period. Combine the extreme range of signal strength variation within each local time period with the trend difference between transmission delay and signal strength to obtain the channel risk level for each local time period.

[0090] Furthermore, during the remote data communication process of the electronic signature device, the quality of the 5G transmission channel also needs to be considered. Due to the influence of network attacks that tamper with data and fake base station deception attacks, the channel quality will degrade. When the risk of tampering with the critical status data of the electronic signature device and the risk of successful fake base station deception attacks are higher, the correlation between channel quality and network attack risk will lead to aggravated transmission delay jitter in the 5G uplink channel. This is because attackers can cause unstable data transmission delays by tampering with data or interfering with the channel, resulting in a significant decrease in the signal-to-noise ratio. At the same time, the impact of fake base station co-channel interference attacks can cause transient link interruptions, weakening legitimate signals and causing a significant precipitous drop in the signal strength of the 5G uplink channel. In addition, the combined attack of data tampering and fake base station deception can cause distortion of the transmission channel estimation matrix, further aggravating the correlation fluctuation between uplink transmission delay and signal strength.

[0091] Furthermore, the flowchart of the method for obtaining the channel risk level for each local time period provided in the embodiments of this application is as follows: Figure 3 As shown.

[0092] Based on the above analysis, by analyzing the fluctuation of uplink channel transmission delay and the trend of signal-to-noise ratio changes, the first risk value is calculated as follows:

[0093] Obtain the peaks and troughs of the transmission delay of the uplink channel at all times within each local time period;

[0094] In this embodiment, the AMPD (Automatic Multiscale-based Peak Detection) algorithm is used to obtain peaks and troughs. The AMPD algorithm is a well-known technology and will not be described in detail here.

[0095] Calculate the difference between the peak value of each wave peak and the valley value of its adjacent wave trough, and denot it as the time delay deviation;

[0096] In this embodiment, the difference between the peak value of each wave peak and the trough value of the previous wave trough is calculated and denoted as the time delay deviation.

[0097] The degree of dispersion of the time delay deviation of all peaks within each local time period is taken as the time delay fluctuation of each local time period.

[0098] In this embodiment, the degree of dispersion is calculated by measuring the coefficient of variation of the time delay deviation of all peaks in each local time period. The calculation of the coefficient of variation is a well-known technique and will not be described in detail here. As other implementation methods, implementers may use other methods of the prior art, such as variance, etc. This embodiment does not impose any special restrictions on this.

[0099] The difference in signal-to-noise ratio between each local time period and the previous local time period of the uplink channel is denoted as the relative difference, and the relative difference is negatively mapped.

[0100] In this embodiment, the specific process of negative mapping is as follows: negative mapping is performed through an exponential function, assuming the relative difference is denoted as... ,but The result is used as the result of the negative mapping, where, For an exponential function with the natural constant as the base, the negative mapping process is used to make the result of the negative mapping greater than 0.

[0101] The product of the time delay volatility and the result of the negative mapping is used as the first risk value for each local time period;

[0102] It should be noted that the greater the latency fluctuation, the more severe the transmission latency jitter of the 5G uplink channel; the greater the negative mapping result, the more significant the signal-to-noise ratio deteriorates between two adjacent local time periods, and the channel environment is rapidly deteriorating; the greater the first risk value, the higher the risk that the uplink channel is under active network attack.

[0103] Secondly, the changes in uplink channel signal strength and the correlation between transmission delay and signal strength are analyzed to calculate the second risk value, specifically:

[0104] Calculate the range of signal strength of the uplink channel at all times within each local time period;

[0105] Calculate the distance between the transmission delay and signal strength of the uplink channel at all times within each local time period;

[0106] In this embodiment, the distance is measured by calculating the DTW distance between the transmission delay and signal strength of the uplink channel at all times in each local time period. The DTW distance is a well-known technique and will not be described in detail here.

[0107] The product of the range and the distance is used as the second risk value for each local time period;

[0108] It should be noted that the larger the range, the greater the fluctuation of the signal strength in that local time period, which may be subject to interference or signal instability. The larger the distance, the more inconsistent the changes in transmission delay and signal strength, reflecting that the normal correlation between signal strength and transmission delay is more severely disrupted. The larger the second risk value, the greater the fluctuation of the signal strength and the more inconsistent the changes in transmission delay and signal strength, reflecting that the channel is subject to interference and that there is a higher risk of fake base station deception attacks.

[0109] Furthermore, based on the first risk value and the second risk value, the channel risk level is determined, specifically as follows:

[0110] The normalized result of the product of the first risk value and the second risk value is used as the channel risk level for each local time period;

[0111] In this embodiment, the sigmoid function is used for normalization. The sigmoid function is a well-known technique and will not be described in detail here. As other implementation methods, implementers may use other methods of the prior art, such as the tanh function. This embodiment does not impose any special restrictions on this.

[0112] It should be noted that the higher the channel risk level, the higher the risk of the electronic signature device being subjected to data tampering and fake base station deception attacks during remote data communication, the lower the channel security, and the increased risk of data transmission.

[0113] Thus, the channel risk level for each local time period is obtained.

[0114] Step 4: Prioritize all local time periods within each communication segment, identify low-risk time periods in the next communication segment based on channel risk level, encrypt all signals and sealing statuses in each local time period, form a transmission queue according to the priority, and transmit encrypted data to the remote monitoring terminal in the order of the transmission queue during the low-risk time period of the next communication segment.

[0115] Furthermore, based on the opening and closing status of monitored doors during all local time periods within the communication segment, and combined with the risk of misjudgment, priorities are assigned, specifically as follows:

[0116] All open periods within each communication segment are designated as the high priority group, and all non-open periods are designated as the low priority group.

[0117] All opening times within the high priority group are arranged in ascending order of time, and all non-opening times within the secondary priority group are arranged in descending order of risk of misjudgment. The high priority group is arranged first and the secondary priority group is arranged last. All opening times and all non-opening times are then assigned priority accordingly.

[0118] It should be noted that the earlier a local time period is listed, the higher its priority, and vice versa.

[0119] Furthermore, based on priority, the data transmitted by the electronic signature device in each local time period is encrypted and transmitted, specifically as follows:

[0120] The current signal, magnetic field signal, infrared signal, and seal status information of each local time period are encrypted to obtain the ciphertext;

[0121] In this embodiment, the AES encryption algorithm is used for encryption. The AES encryption algorithm is a well-known technology and will not be described in detail here. The specific encryption process is as follows: the current signal, magnetic field signal, infrared signal and seal status information are each divided into 128-bit (16-byte) blocks, and byte padding is performed using the PKCS#7 rule. An AES-256 key is configured, and an initial vector is generated using randomization. The plaintext blocks after byte padding are encrypted sequentially using CBC mode. The AES algorithm is called iteratively to output the ciphertext. The number of iterations is set to 10, and an HMAC verification process is added to prevent data tampering.

[0122] The ciphertext of all local time periods within each communication segment is sorted by priority to form a transmission queue;

[0123] Obtain the segmentation threshold for channel risk in all local time periods within each communication segment;

[0124] In this embodiment, the Otsu's method is used to obtain the segmentation threshold. Otsu's method is a well-known technique and will not be described in detail here. As other implementation methods, implementers may use other methods of the prior art, such as cross-validation. This embodiment does not impose any special restrictions on this.

[0125] Local time periods within the next communication segment where the channel risk level is less than the segmentation threshold are designated as low-risk periods, and vice versa.

[0126] During low-risk periods, encrypted messages are transmitted sequentially to the remote monitoring terminal according to the transmission queue.

[0127] It should be noted that since there are many ciphertexts waiting to be transmitted, they may not be transmitted in a low-risk period. Therefore, once a low-risk period appears in the next communication segment, the ciphertexts will be transmitted sequentially according to the sending queue. During high-risk periods, the ciphertexts will continue to wait and will not be sent until a low-risk period appears again.

[0128] The remote monitoring terminal verifies and decrypts the encrypted text transmitted by the main control module of the electronic signature device to further evaluate the status of the electronic signature.

[0129] Based on the same inventive concept as the above method, this application also provides a remote data communication system for an electronic signature device, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-described remote data communication methods for an electronic signature device.

[0130] It should be understood that, although Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0131] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0132] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application. Therefore, any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of this application, without departing from the content of the technical solution of this application, shall fall within the protection scope of the technical solution of this application.

Claims

1. A method for remote data communication for an electronic seal device, characterized by, The method comprises the following steps: Obtaining the current signal, the magnetic field electric signal and the infrared electric signal of each local period in each communication section, and judging the sealing state of each local period, obtaining the signal-to-noise ratio of the uplink channel in each local period, and the transmission delay and the signal strength at each time; Analyzing the trend change of the magnetic field electric signal and the infrared electric signal, and calculating the first interference value of each local period; Through the periodic characteristics of the change of the current signal, the abnormal fluctuation of the infrared electric signal, and the synchronization of the abnormal change time between the magnetic field electric signal and the infrared electric signal, the second interference value of each local period is calculated, the first interference value is combined to obtain the misjudgment risk degree of each local period, and the sealing state of each local period is combined to divide the priority of all local periods in each communication section; Analyzing the fluctuation change of the transmission delay in each local period, and the attenuation of the signal-to-noise ratio, determining the first risk value of each local period, combining the extreme change range of the signal strength in each local period, and the trend difference between the transmission delay and the signal strength, obtaining the channel risk degree of each local period, and identifying the low risk period of the next communication section; All signals and sealing states of each local period are encrypted, a sending queue is formed according to the priority, and the encrypted data is transmitted to the remote monitoring terminal in the low risk period of the next communication section in the order of the sending queue.

2. A method for remote data communication with an electronic seal device as claimed in claim 1, characterized in that, The judgment of the sealing state of each local period comprises: if any of the judgment conditions is met, the sealing state is abnormal, and the local period is recorded as the opening period; otherwise, the sealing state is normal, and the local period is recorded as the non-opening period, wherein the judgment conditions are that all signal strengths in the magnetic field electric signal are 0, or all signal strengths in the infrared electric signal are 0, or all non-0 in the current signal.

3. A method for remote data communication with an electronic seal device as claimed in claim 1, characterized in that, The calculation of the first interference value of each local period comprises: Trend decomposition and trend intensity calculation are performed on the magnetic field electric signal and the infrared electric signal respectively, and the first trend degree and the second trend degree are recorded respectively. The first interference value is the sum of the first trend degree and the second trend degree.

4. A method for remote data communication with an electronic seal device as claimed in claim 1, characterized in that, The calculation of the second interference value of each local period comprises: The autocorrelation coefficients of a plurality of preset lag orders of the current signal are obtained, and the mean value of all autocorrelation coefficients is calculated as the autocorrelation strength of each local period; Abnormal detection is performed on the signal strengths of all time points in the infrared electric signal to obtain abnormal time points; the dispersion degree of the signal strengths of all abnormal time points is calculated and recorded as the abnormal fluctuation degree; The time points with signal strength of 0 in the magnetic field electric signal are counted and recorded as significant time points; the correlation degree between all significant time points and all abnormal time points in each local period is calculated as the time synchronization degree of each local period; The second interference value is the product of the autocorrelation strength, the abnormal fluctuation degree and the time synchronization degree.

5. A method for remote data communication with an electronic seal device as claimed in claim 1, characterized in that, The misjudgment risk degree is the normalized result of the product of the first interference value and the second interference value.

6. A method for remote data communication with an electronic seal device as claimed in claim 2, characterized in that, The priority of all local time segments in each communication section is divided, including: all open-door time segments in each communication section are recorded as a high priority group, and all non-open-door time segments are recorded as a secondary priority group; all open-door time segments in the high priority group are arranged in ascending order of time sequence, all non-open-door time segments in the secondary priority group are arranged in descending order of misjudgment risk degree, all open-door time segments and all non-open-door time segments are arranged in the order of the high priority group first and the secondary priority group second, and priority is assigned in turn.

7. A method for remote data communication with an electronic seal device as claimed in claim 1, characterized in that, The first risk value of each local time segment is determined, including: The peak and valley of the transmission delay of the uplink channel at all times in each local time segment are obtained; the difference between the peak value of each peak and the valley value of its adjacent valley is calculated and recorded as a delay deviation; the dispersion degree of the delay deviation of all peaks in each local time segment is taken as the delay fluctuation degree of each local time segment; The difference in signal-to-noise ratio between each local time segment and the previous local time segment of the uplink channel is negatively mapped. The first risk value is the product of the delay fluctuation degree and the result of negative mapping.

8. A method for remote data communication with an electronic seal device as claimed in claim 1, characterized in that, The channel risk degree of each local time segment is obtained, including: The range of signal strength of the uplink channel at all times in each local time segment is calculated; the distance between the transmission delay and the signal strength of the uplink channel at all times in each local time segment is calculated; the product of the range and the distance is taken as the second risk value of each local time segment; The channel risk degree is the normalized result of the product of the first risk value and the second risk value.

9. A method for remote data communication with an electronic seal device as claimed in claim 1, characterized in that, The low-risk time segment of the next communication section is identified, including: obtaining the segmentation threshold of the channel risk degree of all local time segments in each communication section; the local time segment with a channel risk degree less than the segmentation threshold in the next communication section is taken as the low-risk time segment.

10. A remote data communication system for an electronic seal device, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, The processor executes the computer program to realize the steps of the remote data communication method for the electronic seal device in any one of claims 1-9.

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