Anti-prying method and system for intelligent door lock

Abstract

The invention relates to the technical field of big data and smart home, in particular to an anti-prying method and system for an intelligent door lock, and the method comprises the following steps: S1, collecting door lock interaction data during interaction operation of the intelligent door lock in each set time period every day through a memory installed in the intelligent door lock; s2, based on the data collected in the S1, door lock interaction data are analyzed through big data, and a daily unlocking behavior database is established; s3, collecting real-time interaction data of the intelligent door lock, and comparing the real-time interaction data with the daily unlocking behavior database to obtain safety parameters; s4, remote abnormal access behaviors of the intelligent door lock are monitored in real time, and abnormal access parameters are obtained; s5, according to the safety parameters and the abnormal access parameters, safety early warning parameters are calculated, an early warning prompting mode is determined according to the safety early warning parameters, the safety and reliability of the intelligent door lock are improved, and safer and more convenient intelligent home experience is provided for a user.

Description

Technical Field

[0001] The present invention relates to the field of big data and smart home technologies, and in particular to an anti-pry method and system for a smart door lock. Background Art

[0002] With the rapid development of smart home technology, smart door locks, as the first line of defense for home security, are gaining more and more attention from users for their safety and reliability. However, traditional smart door lock anti-theft methods have many shortcomings and are difficult to effectively deal with increasingly complex unlocking methods and abnormal access behaviors. When collecting door lock interaction data, traditional smart door locks often only focus on simple unlocking records and failure times, and lack in-depth analysis and mining of data. This method cannot fully reflect the characteristics of users' unlocking behavior, resulting in insufficient accuracy in judging abnormal unlocking behavior. Traditional methods lack real-time performance and cannot timely analyze and warn the real-time interactive data of door locks. When monitoring abnormal access behavior, traditional smart door locks usually only rely on simple rule matching, such as checking access time and access device ID. However, this monitoring method is easily exploited by hackers to bypass security detection by forging access time and device ID. Traditional methods lack comprehensive coverage of abnormal access types, resulting in some potential security threats not being discovered in time. Traditional smart door locks also have shortcomings in early warning prompts. When abnormal unlocking or abnormal access behavior is detected, traditional methods can often only issue simple alarm sounds or light prompts, and cannot provide detailed early warning information and corresponding countermeasures. This not only increases the user's sense of panic, but also reduces the security protection effect of smart door locks.

[0003] Therefore, a method and system for preventing prying of an intelligent door lock are proposed. Summary of the invention

[0004] The present invention aims to solve the problem that traditional smart door locks lack in-depth analysis and mining of data when collecting door lock interaction data, and there is a problem of being unable to timely analyze the real-time interaction data of door locks. When monitoring abnormal access behavior, traditional smart door locks usually only rely on simple rule matching, and there is a problem of abnormal monitoring risk. Traditional methods can often only send out simple alarm sounds or light prompts, and cannot provide detailed warning information and corresponding response measures, resulting in poor user experience.

[0005] The technical solution adopted by the present invention to solve its technical problem is:

[0006] A method for preventing prying of a smart door lock, characterized in that it comprises the following steps:

[0007] S1: Collecting door lock interaction data when there is interactive operation of the smart door lock in each set time period every day through a memory installed in the smart door lock;

[0008] S2: Based on the data collected in S1, use big data to analyze the door lock interaction data and establish a daily unlocking behavior database;

[0009] S3: Collect the real-time interaction data of the smart door lock, compare the real-time interaction data with the daily unlocking behavior database, and obtain security parameters;

[0010] S4: Real-time monitoring of abnormal remote access behavior of smart door locks and obtaining abnormal access parameters;

[0011] S5: Calculate the security warning parameters according to the security parameters and the abnormal access parameters, and determine the warning prompt method according to the security warning parameters.

[0012] S6: Detect the external force value of the door lock through the pressure sensor installed in the smart door lock, compare the detected external force value with the preset anti-pry external force threshold; and generate an anti-pry warning based on the comparison result.

[0013] Furthermore, S1 specifically includes:

[0014] S11: Configuring a memory and a 5G communication module in the smart door lock, and connecting the memory to the cloud storage server through a network communication protocol;

[0015] S12: Collect door lock interaction data, which includes the owner's unlocking time, unlocking method, number of successful unlocking, and number of failed unlocking.

[0016] S13: The 5G communication module is used to regularly transmit the collected door lock interaction data to the cloud storage server; and integrate, filter and denoise the data.

[0017] Furthermore, S2 specifically includes:

[0018] S21: The cloud storage server is used for the user to preset the daily unlocking time range, three daily unlocking mode trends and the daily unlocking failure number threshold;

[0019] S22: Establish a daily unlocking behavior database according to the daily unlocking time range, three daily unlocking mode orientation values ​​and daily unlocking failure number thresholds set in S21.

[0020] Furthermore, S3 specifically includes:

[0021] S31: Obtain the real-time unlocking time of the door lock, and compare the real-time unlocking time with the daily unlocking time range. If the real-time unlocking time is within the daily unlocking time range, the first security parameter a1=0, otherwise a1=1;

[0022] S32: Get the real-time unlocking mode of the door lock, and compare the real-time unlocking mode with the daily unlocking mode trend. When the first unlocking mode is consistent with the first daily unlocking trend, the second security parameter a2=0, when the first unlocking mode is consistent with the second daily unlocking trend, the second security parameter a2=0.1, when the first unlocking mode is consistent with the third daily unlocking trend, the second security parameter a2=0.3. After the first unlocking fails, when the second unlocking mode is consistent with the first daily unlocking trend, the second security parameter a2=0, when the second unlocking mode is consistent with the second daily unlocking trend, the second security parameter a2=0.4, when the second unlocking mode is consistent with the third daily unlocking trend, the second security parameter a2=0 .6, after the second unlocking failure, when the third unlocking method is consistent with the first daily unlocking trend, the second security parameter a2=0.2, when the third unlocking method is consistent with the second daily unlocking trend, the second security parameter a2=0.6, when the third unlocking method is consistent with the third daily unlocking trend, the second security parameter a2=0.8, after the third unlocking failure, when the third unlocking method is consistent with the first daily unlocking trend, the second security parameter a2=0.4, when the third unlocking method is consistent with the second daily unlocking trend, the second security parameter a2=0.8, when the third unlocking method is consistent with the third daily unlocking trend, the second security parameter a2=1, after the third unlocking failure, the second security parameter a2=1;

[0023] S33: Obtain the real-time unlocking failure count of the door lock, and compare the real-time unlocking failure count with the daily unlocking failure count threshold. When the real-time unlocking failure count is within the daily unlocking failure count threshold, the third security parameter a3=0, otherwise a3=1.

[0024] S34: Unlocking methods include fingerprint unlocking, face recognition unlocking and password unlocking.

[0025] Furthermore, S4 specifically includes:

[0026] S41: Obtaining remote access log data of the smart door lock in real time, including remote access time, remote access device ID, remote access type and remote access result;

[0027] S42: Acquire abnormal access parameters by comparing remote access time, remote access device ID, remote access type, remote access result and preset abnormal access time threshold range, homeowner's device ID, abnormal access type range and access failure times.

[0028] Furthermore, S42 specifically includes:

[0029] S421: Obtain remote access time, compare the remote access time with a preset normal access time threshold range, and when the remote access time is within the preset abnormal access time threshold range, the first abnormal access parameter b1=0.5, otherwise b1=0;

[0030] S422: Obtain the remote access device ID, and compare the remote access device ID with the homeowner's device ID to see if they are consistent. When the remote access device ID is consistent with the homeowner's device ID, the second abnormal access parameter b2=0, otherwise b2=1;

[0031] S423: Obtain the remote access type, compare the remote access type with the abnormal access type range, if the remote access type is within the abnormal access type range, the third abnormal access parameter b3=1, otherwise b3=0;

[0032] S424: Get the remote access result. When the remote access is successful, the fourth abnormal access parameter b4=0. When the number of remote access failures is one, the fourth abnormal access parameter b4=0.2. When the number of remote access failures is two or three, the fourth abnormal access parameter b4=0.5. When the number of remote access failures is greater than three, the fourth abnormal access parameter b4=1.

[0033] Furthermore, S5 specifically includes:

[0034] S51: Calculate the security warning parameters according to the acquired security parameters and abnormal access parameters:

[0035]

[0036] Wherein, S is a security warning parameter, ω1 is a comprehensive weight factor, ω1={0,1}, β1, β2 and β3 are security parameter weight factors, and β1+β2+β3=1, α1, α2, α3 and α4 are abnormal access parameter weight factors, and α1+α2+α3+α4=1, a1 is a first security parameter, a2 is a second security parameter, a3 is a third security parameter, b1 is a first abnormal access parameter, b2 is a second abnormal access parameter, b3 is a third abnormal access parameter, and b4 is a fourth abnormal access parameter;

[0037] S52: Determine the warning prompt mode according to the safety warning parameter and the preset safety warning threshold. When the safety warning parameter is within the first safety warning threshold, a first-level warning prompt is issued. When the safety warning parameter is within the second safety warning threshold, a second-level warning prompt is issued. When the safety warning parameter is within the third safety warning threshold, a third-level warning prompt is issued.

[0038] Furthermore, S52 specifically includes:

[0039] S521: The method of comparing the safety warning parameter calculated in S51 with the preset safety threshold is as follows:

[0040]

[0041] Among them, S is a safety warning parameter. When the output result is I, a first-level warning prompt signal is generated. When the output result is II, a second-level warning prompt signal is generated. When the output result is III, a third-level warning prompt signal is generated.

[0042] S522: When a first-level warning signal is obtained, a warning message is sent to the mobile terminal of the homeowner through the 5G communication module;

[0043] S523: When a second-level warning prompt signal is obtained, the image data outside the door is obtained through a camera installed outside the door, and then the image data outside the door and the warning prompt information are transmitted to the mobile terminal of the homeowner;

[0044] S524: When a third-level warning signal is obtained, an alarm prompt message is sent to the homeowner's mobile terminal through the 5G communication module and the smart door lock is controlled to directly sound an alarm.

[0045] Furthermore, S6 specifically includes:

[0046] S61: Install a pressure sensor in the smart door lock to obtain the external force value of the door lock;

[0047] S62: Compare the external force value data obtained in S61 with the preset anti-pry external force threshold; and control the smart door lock to sound an alarm when it is confirmed that the external force value data obtained is greater than the preset anti-pry external force threshold.

[0048] The present invention also provides an anti-pry system for a smart door lock, which is used to implement the anti-pry method for the smart door lock as described above, and is characterized in that it includes:

[0049] A data acquisition module, used to collect door lock interaction data when there is an interactive operation of the smart door lock in each set time period every day through a memory installed in the smart door lock;

[0050] A database establishment module is used to analyze the door lock interaction data using big data after receiving the door lock interaction data, and establish a daily unlocking behavior database;

[0051] The security parameter acquisition module is used to collect the real-time interaction data of the smart door lock; and to compare the collected real-time interaction data with the daily unlocking behavior database to obtain security parameters;

[0052] The abnormal access monitoring module is used to monitor the remote abnormal access behavior of the smart door lock in real time; and is used to obtain abnormal access parameters by comparing the remote abnormal access behavior of the smart door lock monitored in real time with the preset abnormal access behavior threshold;

[0053] A security warning module, used to calculate security warning parameters according to security parameters and abnormal access parameters; and to determine a warning prompt mode according to the security warning parameters;

[0054] The anti-pry warning module detects the external force applied to the door lock through the pressure sensor installed in the smart door lock, compares the detected external force value with the preset anti-pry external force threshold, and generates an anti-pry warning based on the comparison result.

[0055] Beneficial effects of the present invention:

[0056] 1. It can deeply mine the hidden information in the door lock interaction data, such as user unlocking habits and common unlocking methods, so as to establish a more accurate daily unlocking behavior database, improve the intelligence level of the system, and ensure the accuracy of the data.

[0057] 2. It can quickly respond to every interactive operation of the door lock, and timely compare the real-time interactive data with the daily unlocking behavior database, so as to effectively identify abnormal unlocking behavior, enhance the security of the system, and obtain potential security threat information at the first time.

[0058] 3. Remote abnormal access monitoring can comprehensively consider multiple factors, including access time, device ID, and access type, to more accurately identify abnormal access behavior. This multi-dimensional monitoring method effectively reduces the risk of abnormal monitoring and improves the security of the system.

[0059] 4. When the system detects abnormal unlocking or abnormal access behavior, it can not only sound an alarm, but also send detailed warning information to the user through the mobile terminal. This information includes a specific description of the abnormal behavior and the possible risk level, so as to help users better understand potential security threats and take corresponding protective measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings of the embodiments are briefly introduced below. The drawings described below only relate to some embodiments of the present invention, but are not intended to limit the present invention.

[0061] In the attached picture:

[0062] Figure 1 It is a schematic diagram of an anti-theft method and system for a smart door lock according to an embodiment of the present invention. DETAILED DESCRIPTION

[0063] The concept and technical effects of the present invention will be clearly and completely described below in conjunction with embodiments to fully understand the purpose, features and effects of the present invention.

[0064] It should be noted that the references to "one embodiment", "an embodiment", "an exemplary embodiment", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0065] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0066] See also Figure 1 ,

[0067] A method for preventing prying of a smart door lock, characterized in that it comprises the following steps:

[0068] S1: Collecting door lock interaction data when there is interactive operation of the smart door lock in each set time period every day through a memory installed in the smart door lock;

[0069] S2: Based on the data collected in S1, use big data to analyze the door lock interaction data and establish a daily unlocking behavior database;

[0070] S3: Collect the real-time interaction data of the smart door lock, compare the real-time interaction data with the daily unlocking behavior database, and obtain security parameters;

[0071] S4: Real-time monitoring of abnormal remote access behavior of smart door locks and obtaining abnormal access parameters;

[0072] S5: Calculate the security warning parameters according to the security parameters and the abnormal access parameters, and determine the warning prompt method according to the security warning parameters.

[0073] S6: Detect the external force value of the door lock through the pressure sensor installed in the smart door lock, compare the detected external force value with the preset anti-pry external force threshold; and generate an anti-pry warning based on the comparison result.

[0074] S1 specifically includes:

[0075] S11: Configuring a memory and a 5G communication module in the smart door lock. The memory is connected to a cloud storage server through a network communication protocol. The memory is a mobile hard disk.

[0076] S12: Collect door lock interaction data, which includes the owner's unlocking time, unlocking method, number of successful unlocking, and number of failed unlocking.

[0077] S13: The 5G communication module is used to regularly transmit the collected door lock interaction data to the cloud storage server; and integrate, filter and denoise the data.

[0078] Through the combination of the above steps, the memory is used to temporarily store the door lock interaction data to ensure the integrity and continuity of the door lock interaction; the 5G communication module provides a high-speed and stable network connection, so that the data can be transmitted to the cloud storage server in real time and efficiently. This configuration not only improves the speed and efficiency of data transmission, but also enhances the reliability and stability of the system.

[0079] S2 specifically includes:

[0080] S21: The cloud storage server is used for the user to preset the daily unlocking time range, three daily unlocking mode trends and the daily unlocking failure number threshold;

[0081] S22: Establish a daily unlocking behavior database according to the daily unlocking time range, three daily unlocking mode orientation values ​​and daily unlocking failure number thresholds set in S21.

[0082] Through the combination of the above steps, the foundation of the daily unlocking behavior database is built, which is also an important basis for the subsequent abnormal behavior identification. By analyzing the door lock interaction data, the system can accurately identify the user's daily unlocking time range, the three daily unlocking method trends, and the threshold of the number of daily unlocking failures. These parameters can reflect the user's unlocking habits and also reflect the usage status and safety of the door lock.

[0083] S3 specifically includes:

[0084] S31: Obtain the real-time unlocking time of the door lock, and compare the real-time unlocking time with the daily unlocking time range. If the real-time unlocking time is within the daily unlocking time range, the first security parameter a1=0, otherwise a1=1;

[0085] S32: Get the real-time unlocking mode of the door lock, and compare the real-time unlocking mode with the daily unlocking mode trend. When the first unlocking mode is consistent with the first daily unlocking trend, the second security parameter a2=0, when the first unlocking mode is consistent with the second daily unlocking trend, the second security parameter a2=0.1, when the first unlocking mode is consistent with the third daily unlocking trend, the second security parameter a2=0.3. After the first unlocking fails, when the second unlocking mode is consistent with the first daily unlocking trend, the second security parameter a2=0, when the second unlocking mode is consistent with the second daily unlocking trend, the second security parameter a2=0.4, when the second unlocking mode is consistent with the third daily unlocking trend, the second security parameter a2=0 .6, after the second unlocking failure, when the third unlocking method is consistent with the first daily unlocking trend, the second security parameter a2=0.2, when the third unlocking method is consistent with the second daily unlocking trend, the second security parameter a2=0.6, when the third unlocking method is consistent with the third daily unlocking trend, the second security parameter a2=0.8, after the third unlocking failure, when the third unlocking method is consistent with the first daily unlocking trend, the second security parameter a2=0.4, when the third unlocking method is consistent with the second daily unlocking trend, the second security parameter a2=0.8, when the third unlocking method is consistent with the third daily unlocking trend, the second security parameter a2=1, after the third unlocking failure, the second security parameter a2=1;

[0086] S33: Obtain the real-time unlocking failure count of the door lock, and compare the real-time unlocking failure count with the daily unlocking failure count threshold. When the real-time unlocking failure count is within the daily unlocking failure count threshold, the third security parameter a3=0, otherwise a3=1.

[0087] S34: Unlocking methods include fingerprint unlocking, face recognition unlocking and password unlocking.

[0088] By combining the above steps, the real-time unlocking time, unlocking method and number of unlocking failures are compared with the parameters in the daily unlocking behavior database, and the unlocking behavior is evaluated from multiple dimensions. This multi-dimensional evaluation method improves the accuracy and reliability of system recognition, sets different security parameters for different unlocking methods and continuous unlocking failures, enables the system to more carefully reflect the user's unlocking behavior characteristics, and improves the real-time and security of the system.

[0089] S4 specifically includes:

[0090] S41: Obtaining remote access log data of the smart door lock in real time, including remote access time, remote access device ID, remote access type and remote access result;

[0091] S42: Acquire abnormal access parameters by comparing remote access time, remote access device ID, remote access type, remote access result and preset abnormal access time threshold range, homeowner's device ID, abnormal access type range and number of access failures, wherein the abnormal access type includes unlock access request, password change access request and user information access request.

[0092] Through the combination of the above steps, the remote access behavior of the smart door lock can be monitored in real time, and abnormal behavior can be identified by comparing data in multiple dimensions, thereby improving the accuracy and reliability of detection. The system's preset abnormal access parameters can be adjusted and optimized according to actual needs to adapt to the usage habits and security needs of different users.

[0093] S42 specifically includes:

[0094] S421: Obtain remote access time, compare the remote access time with a preset normal access time threshold range, and when the remote access time is within the preset abnormal access time threshold range, the first abnormal access parameter b1=0.5, otherwise b1=0;

[0095] S422: Obtain the remote access device ID, and compare the remote access device ID with the homeowner's device ID to see if they are consistent. When the remote access device ID is consistent with the homeowner's device ID, the second abnormal access parameter b2=0, otherwise b2=1;

[0096] S423: Obtain the remote access type, compare the remote access type with the abnormal access type range, if the remote access type is within the abnormal access type range, the third abnormal access parameter b3=1, otherwise b3=0;

[0097] S424: Get the remote access result. When the remote access is successful, the fourth abnormal access parameter b4=0. When the number of remote access failures is one, the fourth abnormal access parameter b4=0.2. When the number of remote access failures is two or three, the fourth abnormal access parameter b4=0.5. When the number of remote access failures is greater than three, the fourth abnormal access parameter b4=1.

[0098] S5 specifically includes:

[0099] S51: Calculate the security warning parameters according to the acquired security parameters and abnormal access parameters:

[0100]

[0101] Wherein, S is a security warning parameter, ω1 is a comprehensive weight factor, ω1={0,1}, β1, β2 and β3 are security parameter weight factors, and β1+β2+β3=1, α1, α2, α3 and α4 are abnormal access parameter weight factors, and α1+α2+α3+α4=1, a1 is a first security parameter, a2 is a second security parameter, a3 is a third security parameter, b1 is a first abnormal access parameter, b2 is a second abnormal access parameter, b3 is a third abnormal access parameter, and b4 is a fourth abnormal access parameter;

[0102] In this embodiment, when ω1=0, β1=0.3, β2=0.4, β3=0.3, a1=0, a2=0.8, a3=1, the safety warning parameter is calculated to be 0.62.

[0103] S52: Determine the warning prompt mode according to the safety warning parameter and the preset safety warning threshold. When the safety warning parameter is within the first safety warning threshold, a first-level warning prompt is issued. When the safety warning parameter is within the second safety warning threshold, a second-level warning prompt is issued. When the safety warning parameter is within the third safety warning threshold, a third-level warning prompt is issued.

[0104] Through the combination of the above steps, multiple security parameters and abnormal access parameters can be comprehensively considered to provide a more comprehensive security assessment. The weight factor and security warning threshold can be adjusted according to the actual situation to adapt to different security needs and scenarios. The security warning parameters can be calculated in real time and the warning prompt method can be determined to ensure timely response to security risks. Different levels of warning methods can improve the efficiency of warning and enhance the user experience.

[0105] S52 specifically includes:

[0106] S521: The method of comparing the safety warning parameter calculated in S51 with the preset safety threshold is as follows:

[0107]

[0108] Among them, S is a safety warning parameter. When the output result is I, a first-level warning prompt signal is generated. When the output result is II, a second-level warning prompt signal is generated. When the output result is III, a third-level warning prompt signal is generated.

[0109] S522: When a first-level warning signal is obtained, a warning message is sent to the mobile terminal of the homeowner through the 5G communication module;

[0110] S523: When a second-level warning prompt signal is obtained, the image data outside the door is obtained through a camera installed outside the door, and then the image data outside the door and the warning prompt information are transmitted to the mobile terminal of the homeowner;

[0111] S524: When a third-level warning signal is obtained, an alarm prompt message is sent to the homeowner's mobile terminal through the 5G communication module and the smart door lock is controlled to directly sound an alarm.

[0112] S6 specifically includes:

[0113] S61: Install a pressure sensor in the smart door lock to obtain the external force value of the door lock;

[0114] S62: Compare the external force value data obtained in S61 with the preset anti-pry external force threshold; and control the smart door lock to sound an alarm when it is confirmed that the external force value data obtained is greater than the preset anti-pry external force threshold.

[0115] The present invention also provides an anti-pry system for a smart door lock, which is used to implement the anti-pry method for the smart door lock as described above, and is characterized by comprising:

[0116] A data acquisition module, used to collect door lock interaction data when there is an interactive operation of the smart door lock in each set time period every day through a memory installed in the smart door lock;

[0117] A database establishment module is used to analyze the door lock interaction data using big data after receiving the door lock interaction data, and establish a daily unlocking behavior database;

[0118] The security parameter acquisition module is used to collect the real-time interaction data of the smart door lock; and to compare the collected real-time interaction data with the daily unlocking behavior database to obtain security parameters;

[0119] The abnormal access monitoring module is used to monitor the remote abnormal access behavior of the smart door lock in real time; and is used to obtain abnormal access parameters by comparing the remote abnormal access behavior of the smart door lock monitored in real time with the preset abnormal access behavior threshold;

[0120] The security warning module is used to calculate the security warning parameters according to the security parameters and the abnormal access parameters; and to determine the warning prompt mode according to the security warning parameters.

[0121] The anti-pry warning module detects the external force applied to the door lock through the pressure sensor installed in the smart door lock, compares the detected external force value with the preset anti-pry external force threshold, and generates an anti-pry warning based on the comparison result.

[0122] In summary, the present invention collects real-time interactive data of smart door locks and uses big data analysis technology to establish a daily unlocking behavior database, so as to fully reflect the unlocking behavior characteristics of users. This method also monitors the remote abnormal access behavior of smart door locks in real time, and obtains abnormal access parameters by comparing the real-time monitored data with the preset abnormal access behavior threshold. In terms of early warning prompts, the method calculates security warning parameters based on security parameters and abnormal access parameters, and determines the early warning prompt method based on the warning parameters, thereby providing more accurate and effective security protection.

[0123] The above embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, other embodiments obtained by technical users in this field without paying creative work all fall within the scope of protection of the present invention.

Claims

1. A method for preventing prying of a smart door lock, characterized in that: The following steps are involved: S1: Collecting door lock interaction data when there is interactive operation of the smart door lock in each set time period every day through a memory installed in the smart door lock; S2: Based on the data collected in S1, use big data to analyze the door lock interaction data and establish a daily unlocking behavior database; S3: Collect the real-time interaction data of the smart door lock, compare the real-time interaction data with the daily unlocking behavior database, and obtain security parameters; S4: Real-time monitoring of abnormal remote access behavior of smart door locks and obtaining abnormal access parameters; S5: Calculate security warning parameters according to security parameters and abnormal access parameters, and determine warning prompt mode according to the security warning parameters; S6: Detecting the external force value of the door lock through the pressure sensor installed in the smart door lock, and comparing the detected external force value with the preset anti-pry external force threshold; And generate anti-theft warning based on the comparison results.

2. The anti-pry method of a smart door lock according to claim 1, characterized in that: The S1 specifically includes: S11: Configuring a memory and a 5G communication module in the smart door lock, and connecting the memory to the cloud storage server through a network communication protocol; S12: Collect door lock interaction data, where the door lock interaction data includes the owner's unlocking time, unlocking method, number of successful unlockings, and number of failed unlockings. S13: The 5G communication module is used to regularly transmit the collected door lock interaction data to the cloud storage server; and integrate, filter and denoise the data.

3. The anti-pry method of a smart door lock according to claim 1, characterized in that: The S2 specifically includes: S21: The cloud storage server is used for the user to preset the daily unlocking time range, three daily unlocking mode trends and the daily unlocking failure number threshold; S22: Establish a daily unlocking behavior database according to the daily unlocking time range, three daily unlocking mode orientation values ​​and daily unlocking failure number thresholds set in S21.

4. The anti-pry method of a smart door lock according to claim 3, characterized in that: The S3 specifically includes: S31: Obtain the real-time unlocking time of the door lock, and compare the real-time unlocking time with the daily unlocking time range. If the real-time unlocking time is within the daily unlocking time range, the first security parameter a1=0, otherwise a1=1; S32: Get the real-time unlocking mode of the door lock, and compare the real-time unlocking mode with the daily unlocking mode trend. When the first unlocking mode is consistent with the first daily unlocking trend, the second security parameter a2=0, when the first unlocking mode is consistent with the second daily unlocking trend, the second security parameter a2=0.1, when the first unlocking mode is consistent with the third daily unlocking trend, the second security parameter a2=0.

3. After the first unlocking fails, when the second unlocking mode is consistent with the first daily unlocking trend, the second security parameter a2=0, when the second unlocking mode is consistent with the second daily unlocking trend, the second security parameter a2=0.4, when the second unlocking mode is consistent with the third daily unlocking trend, the second security parameter a2=0 .6, after the second unlocking failure, when the third unlocking method is consistent with the first daily unlocking trend, the second security parameter a2=0.2, when the third unlocking method is consistent with the second daily unlocking trend, the second security parameter a2=0.6, when the third unlocking method is consistent with the third daily unlocking trend, the second security parameter a2=0.8, after the third unlocking failure, when the third unlocking method is consistent with the first daily unlocking trend, the second security parameter a2=0.4, when the third unlocking method is consistent with the second daily unlocking trend, the second security parameter a2=0.8, when the third unlocking method is consistent with the third daily unlocking trend, the second security parameter a2=1, after the third unlocking failure, the second security parameter a2=1; S33: Obtain the real-time unlocking failure count of the door lock, and compare the real-time unlocking failure count with the daily unlocking failure count threshold. When the real-time unlocking failure count is within the daily unlocking failure count threshold, the third security parameter a3=0, otherwise a3=1; S34: The unlocking methods include fingerprint unlocking, face recognition unlocking and password unlocking.

5. The anti-pry method of a smart door lock according to claim 1, characterized in that: The S4 specifically includes: S41: Obtaining remote access log data of the smart door lock in real time, including remote access time, remote access device ID, remote access type and remote access result; S42: Acquire abnormal access parameters by comparing remote access time, remote access device ID, remote access type, remote access result and preset abnormal access time threshold range, homeowner's device ID, abnormal access type range and access failure times.

6. The anti-pry method of a smart door lock according to claim 5, characterized in that: The S42 specifically includes: S421: Obtain remote access time, compare the remote access time with a preset normal access time threshold range, and when the remote access time is within the preset abnormal access time threshold range, the first abnormal access parameter b1=0.5, otherwise b1=0; S422: Obtain the remote access device ID, and compare the remote access device ID with the homeowner's device ID to see if they are consistent. When the remote access device ID is consistent with the homeowner's device ID, the second abnormal access parameter b2=0, otherwise b2=1; S423: Obtain the remote access type, compare the remote access type with the abnormal access type range, if the remote access type is within the abnormal access type range, the third abnormal access parameter b3=1, otherwise b3=0; S424: Get the remote access result. When the remote access is successful, the fourth abnormal access parameter b4=0. When the number of remote access failures is one, the fourth abnormal access parameter b4=0.

2. When the number of remote access failures is two or three, the fourth abnormal access parameter b4=0.

5. When the number of remote access failures is greater than three, the fourth abnormal access parameter b4=1.

7. The anti-pry method of a smart door lock according to claim 1, characterized in that: The S5 specifically includes: S51: Calculate the security warning parameters according to the acquired security parameters and abnormal access parameters: Wherein, S is a security warning parameter, ω1 is a comprehensive weight factor, ω1={0,1}, β1, β2 and β3 are security parameter weight factors, and β1+β2+β3=1, α1, α2, α3 and α4 are abnormal access parameter weight factors, and α1+α2+α3+α4=1, a1 is a first security parameter, a2 is a second security parameter, a3 is a third security parameter, b1 is a first abnormal access parameter, b2 is a second abnormal access parameter, b3 is a third abnormal access parameter, and b4 is a fourth abnormal access parameter; S52: Determine the warning prompt mode according to the safety warning parameter and the preset safety warning threshold. When the safety warning parameter is within the first safety warning threshold, a first-level warning prompt is issued. When the safety warning parameter is within the second safety warning threshold, a second-level warning prompt is issued. When the safety warning parameter is within the third safety warning threshold, a third-level warning prompt is issued.

8. The anti-pry method of a smart door lock according to claim 7, characterized in that: The S52 specifically includes: S521: The method of comparing the safety warning parameter calculated in S51 with the preset safety threshold is as follows: Among them, S is a safety warning parameter. When the output result is I, a first-level warning prompt signal is generated. When the output result is II, a second-level warning prompt signal is generated. When the output result is III, a third-level warning prompt signal is generated. S522: When a first-level warning signal is obtained, a warning message is sent to the mobile terminal of the homeowner through the 5G communication module; S523: When a second-level warning prompt signal is obtained, the image data outside the door is obtained through a camera installed outside the door, and then the image data outside the door and the warning prompt information are transmitted to the mobile terminal of the homeowner; S524: When a third-level warning signal is obtained, an alarm prompt message is sent to the homeowner's mobile terminal through the 5G communication module and the smart door lock is controlled to directly sound an alarm.

9. The anti-pry method of a smart door lock according to claim 1, characterized in that: The S6 specifically includes: S61: Install a pressure sensor in the smart door lock to obtain the external force value of the door lock; S62: Compare the external force value data obtained in S61 with the preset anti-pry external force threshold; and control the smart door lock to sound an alarm when it is confirmed that the external force value data obtained is greater than the preset anti-pry external force threshold.

10. An anti-theft system for a smart door lock, used to implement the smart home control method according to any one of claims 1 to 9, characterized in that: include: A data acquisition module, used to collect door lock interaction data when there is an interactive operation of the smart door lock in each set time period every day through a memory installed in the smart door lock; A database establishment module is used to analyze the door lock interaction data using big data after receiving the door lock interaction data, and establish a daily unlocking behavior database; The security parameter acquisition module is used to collect the real-time interaction data of the smart door lock; and to compare the collected real-time interaction data with the daily unlocking behavior database to obtain security parameters; Abnormal access monitoring module, used to monitor remote abnormal access behavior of smart door locks in real time; And used to obtain abnormal access parameters by comparing the remote abnormal access behavior of the smart door lock monitored in real time with the preset abnormal access behavior threshold; A security warning module is used to calculate security warning parameters based on security parameters and abnormal access parameters; And used to determine the warning prompt mode according to the safety warning parameters; The anti-pry warning module detects the external force value of the door lock through the pressure sensor installed in the smart door lock, and compares the detected external force value with the preset anti-pry external force threshold; And generate anti-theft warning based on the comparison results.

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