CN107534706B - Mobile terminal anti-theft method and mobile terminal - Google Patents
Mobile terminal anti-theft method and mobile terminal Download PDFInfo
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Abstract
The embodiment of the invention provides a mobile terminal anti-theft method and a mobile terminal, comprising the following steps: monitoring a target sensor, wherein the target sensor comprises an acceleration sensor or a gravity sensor; when the output signal of the target sensor is detected, judging whether the waveform of the output signal is abnormal or not; and if the waveform of the output signal is determined to be abnormal, alarming according to a preset alarming strategy. The identification precision of the abnormal behavior of the mobile terminal can be improved.
Description
Technical Field
The embodiment of the invention relates to the field of terminal security, in particular to a mobile terminal anti-theft method and a mobile terminal.
Background
With the development of electronic technology, mobile terminals such as mobile phones have become an integral part of modern life. Along with the increasing intellectualization of mobile terminals, the life of people becomes more convenient, and people are enabled to rely on mobile phones more and more. At present, mobile phones are related to all aspects of people's life, and related personal information is increasing, such as various phone numbers, important materials, social account numbers and passwords, payment accounts and passwords, bound bank card information, photos, videos and the like, and relates to a large amount of security information and personal privacy. Therefore, once the mobile phone recording the information is lost, the user is greatly affected and even serious economic loss is caused.
However, the phenomenon of mobile phone theft in the current society is very serious, especially in places with high traffic, such as buses, subways, shopping malls, and the like, the mobile phone theft incidents often occur, and the number of mobile phone theft still rises year by year.
Therefore, in order to prevent the mobile phone from being stolen, in a prior art, whether the behavior of the mobile terminal is abnormal is determined by using an acceleration sensor or a gravity sensor built in the mobile phone, and the abnormal behavior is mainly determined by monitoring the variation of the three-dimensional coordinate of the sensor within a preset time and comparing the variation with a preset variation threshold, for example, taking the acceleration sensor as an example, a thief usually acts very slowly when stealing the mobile phone, so that the variation of the three-dimensional coordinate of the acceleration sensor within the preset time is smaller than that during normal use when the mobile phone is stolen, and therefore, when the variation of the three-dimensional coordinate of the acceleration sensor within the preset time is detected to be smaller than the preset variation threshold, the behavior is determined to be abnormal, and when the behavior is determined to be abnormal, the user of the mobile phone is notified by an.
However, in the prior art, the behavior of the terminal is usually judged through a single threshold of the sensor, and it is not easy to distinguish the user of the terminal from a thief, so that the accuracy of identifying the behavior of the terminal is low, and a false alarm is easily generated.
Disclosure of Invention
The embodiment of the invention provides a mobile terminal anti-theft method and a mobile terminal, which are used for improving the identification precision of abnormal behaviors of the mobile terminal.
In a first aspect, an anti-theft method for a mobile terminal is provided, the method comprising:
monitoring a target sensor, wherein the target sensor comprises an acceleration sensor or a gravity sensor;
when the output signal of the target sensor is detected, judging whether the waveform of the output signal is abnormal or not;
and if the waveform of the output signal is determined to be abnormal, alarming according to a preset alarming strategy.
With reference to the first aspect, in a first possible implementation manner, the determining whether the waveform of the output signal is abnormal includes:
respectively comparing the waveform of the output signal with a preset abnormal waveform and a preset normal waveform;
if the waveform of the output signal is matched with the normal waveform, determining that the waveform of the output signal is normal, and monitoring the target sensor again;
and if the waveform of the output signal is matched with the abnormal waveform, determining that the waveform of the output signal is abnormal.
With reference to the first possible implementation manner of the first aspect, in a second possible implementation manner, after determining that the waveform of the output signal is normal, the method further includes:
and learning the waveform of the output signal according to a preset learning algorithm so as to update the normal waveform.
With reference to the first possible implementation manner of the first aspect, in a third possible implementation manner, after determining that the waveform of the output signal is abnormal, the method further includes:
and learning the waveform of the output signal according to a preset learning algorithm so as to update the abnormal waveform.
With reference to the first aspect or any one of the foregoing possible implementations, in a fourth possible implementation, before the monitoring the target sensor, the method further includes:
acquiring positioning information of the mobile terminal;
judging whether the mobile terminal is located in a preset designated area or not according to the positioning information;
and if the mobile terminal is positioned in the designated area, monitoring the target sensor.
With reference to the first aspect or any one of the foregoing possible implementations, in a fifth possible implementation, before the monitoring the target sensor, the method further includes:
judging whether the mobile terminal is in a packet mode or not by using a light sensor and/or a distance sensor of the mobile terminal;
and if the mobile terminal is not in the packet mode, monitoring the target sensor.
With reference to the first aspect or any one of the foregoing possible implementation manners of the first aspect, in a sixth possible implementation manner, the alarming according to a preset alarm policy includes:
sending an alarm sound according to a preset volume, and displaying a password input interface for releasing the alarm on a screen of the mobile terminal;
if the alarm release password input from the password input interface is received within the preset time, stopping sending the alarm sound;
and if the alarm release password is not received within the preset time, increasing the volume of the alarm sound to the maximum value.
In a second aspect, a mobile terminal, the mobile terminal comprising:
the monitoring unit is used for monitoring a target sensor, and the target sensor comprises an acceleration sensor or a gravity sensor;
an identification unit configured to determine whether a waveform of an output signal of the target sensor is abnormal when the output signal is detected;
and the processing unit is used for reporting according to a preset alarm strategy when the waveform of the output signal is determined to be abnormal.
With reference to the second aspect, in a first possible implementation manner, the identification unit is specifically configured to:
respectively comparing the waveform of the output signal with a preset abnormal waveform and a preset normal waveform;
if the waveform of the output signal is matched with the normal waveform, determining that the waveform of the output signal is normal, and monitoring the target sensor again;
and if the waveform of the output signal is matched with the abnormal waveform, determining that the waveform of the output signal is abnormal.
With reference to the first possible implementation manner of the second aspect, in a second possible implementation manner, the processing unit includes: a learning unit to: and after the waveform of the output signal is determined to be normal, learning the waveform of the output signal according to a preset learning algorithm so as to update the normal waveform.
With reference to the first possible implementation manner of the second aspect, in a third possible implementation manner, the processing unit includes: a learning unit to: and after determining that the waveform of the output signal is abnormal, learning the waveform of the output signal according to a preset learning algorithm to update the abnormal waveform.
With reference to the second aspect or any one of the foregoing possible implementation manners of the second aspect, in a fourth possible implementation manner, the mobile terminal further includes:
the positioning unit is used for acquiring positioning information of the mobile terminal before the target sensor is monitored;
the judging unit is used for judging whether the mobile terminal is positioned in a preset designated area or not according to the positioning information;
the monitoring unit is used for monitoring the target sensor when the mobile terminal is located in the designated area.
With reference to the second aspect or any one of the foregoing possible implementation manners of the second aspect, in a fifth possible implementation manner, the mobile terminal further includes:
the sensing unit is used for judging whether the mobile terminal is in a packet mode or not by utilizing a light sensor and/or a distance sensor of the mobile terminal before monitoring the target sensor;
the monitoring unit is used for monitoring the target sensor when the mobile terminal is not in the packet mode.
With reference to the second aspect or any one of the foregoing possible implementation manners of the second aspect, in a sixth possible implementation manner, the processing unit includes: an alarm unit for:
sending an alarm sound according to a preset volume, and displaying a password input interface for releasing the alarm on a screen of the mobile terminal;
if the alarm release password input from the password input interface is received within the preset time, stopping sending the alarm sound;
and if the alarm release password is not received within the preset time, increasing the volume of the alarm sound to the maximum value.
In a third aspect, a mobile terminal is provided, where the mobile terminal includes: the processor, the memory, the interface, the processor, the memory and the interface are connected through a bus; the interface is configured to interact with other network elements, the memory is configured to store a computer program, the processor is configured to execute the computer program, and the processor executes the computer program to:
monitoring a target sensor, wherein the target sensor comprises an acceleration sensor or a gravity sensor;
when the output signal of the target sensor is detected, judging whether the waveform of the output signal is abnormal or not;
and if the waveform of the output signal is determined to be abnormal, reporting according to a preset alarm strategy.
With reference to the third aspect, in a first possible implementation manner, the processor executes the computer program to specifically:
respectively comparing the waveform of the output signal with a preset abnormal waveform and a preset normal waveform;
if the waveform of the output signal is matched with the normal waveform, determining that the waveform of the output signal is normal, and monitoring the target sensor again;
and if the waveform of the output signal is matched with the abnormal waveform, determining that the waveform of the output signal is abnormal.
With reference to the second possible implementation manner of the third aspect, in a second possible implementation manner, the processor executes the computer program to:
and after the waveform of the output signal is determined to be normal, learning the waveform of the output signal according to a preset learning algorithm so as to update the normal waveform.
With reference to the second possible implementation manner of the third aspect, in a third possible implementation manner, the processor executes the computer program to:
and after determining that the waveform of the output signal is abnormal, learning the waveform of the output signal according to a preset learning algorithm to update the abnormal waveform.
With reference to the third aspect or any one of the foregoing possible implementations, in a fourth possible implementation, the processor executes the computer program to:
before monitoring the target sensor, acquiring positioning information of the mobile terminal;
judging whether the mobile terminal is located in a preset designated area or not according to the positioning information;
and if the mobile terminal is positioned in the designated area, monitoring the target sensor.
With reference to the third aspect or any one of the foregoing possible implementations, in a fifth possible implementation, the processor executes the computer program to:
before monitoring the target sensor, judging whether the mobile terminal is in a packet mode by using a light sensor and/or a distance sensor of the mobile terminal;
and if the mobile terminal is not in the packet mode, monitoring the target sensor.
With reference to the third aspect or any one of the foregoing possible implementation manners of the third aspect, in a sixth possible implementation manner, the processor executes the computer program to execute the alarming according to a preset alarming policy, so as to:
sending an alarm sound according to a preset volume, and displaying a password input interface for releasing the alarm on a screen of the mobile terminal;
if the alarm release password input from the password input interface is received within the preset time, stopping sending the alarm sound;
and if the alarm release password is not received within the preset time, increasing the volume of the alarm sound to the maximum value.
The embodiment of the invention provides a mobile terminal anti-theft method and a mobile terminal, wherein a target sensor is monitored, and the target sensor comprises an acceleration sensor or a gravity sensor; when the output signal of the target sensor is detected, judging whether the waveform of the output signal is abnormal according to a preset normal waveform or an abnormal waveform, and if the waveform of the output signal is determined to be abnormal, alarming according to a preset alarm strategy. Compared with the method for identifying by adopting a single sensor threshold in the prior art, the method can improve the identification precision of the abnormal behavior of the mobile terminal, and in addition, after the waveform of the output signal is determined to be normal or abnormal, the waveform of the output signal is learned according to a preset learning algorithm, and the normal waveform or the abnormal waveform is updated, so the identification precision of the abnormal behavior of the mobile terminal can be further improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive labor.
Fig. 1 is a schematic flow chart of an anti-theft method for a mobile terminal according to the present invention;
FIG. 2 is a schematic diagram of normal and abnormal waveforms provided by the present invention;
FIG. 3 is a flow chart illustrating another anti-theft method for a mobile terminal according to the present invention;
fig. 4 is a schematic flow chart illustrating an alarm according to a preset alarm policy in another anti-theft method for a mobile terminal according to the present invention;
FIG. 5 is a flow chart illustrating an anti-theft method for a mobile terminal according to another embodiment of the present invention;
fig. 6 is a schematic structural diagram of a mobile terminal according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of a processing unit in another mobile terminal according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of a processing unit in another mobile terminal according to an embodiment of the present invention;
fig. 9 is a schematic structural diagram of another mobile terminal according to an embodiment of the present invention;
fig. 10 is a schematic structural diagram of another mobile terminal according to an embodiment of the present invention;
fig. 11 is a schematic structural diagram of another mobile terminal according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the invention provides an anti-theft method for a mobile terminal, which comprises the following steps as shown in figure 1:
And 102, judging whether the waveform of the output signal is abnormal or not when the output signal of the target sensor is detected.
And 103, if the waveform of the output signal is abnormal, alarming according to a preset alarm strategy.
The embodiment of the invention provides a mobile terminal anti-theft method, which comprises the steps of monitoring a target sensor, wherein the target sensor comprises an acceleration sensor or a gravity sensor; when the output signal of the target sensor is detected, judging whether the waveform of the output signal is abnormal according to a preset normal waveform or an abnormal waveform, and if the waveform of the output signal is determined to be abnormal, alarming according to a preset alarm strategy. Compared with the prior art that whether the mobile terminal is abnormal or not is judged by judging whether the single value of the variation of the three-dimensional coordinates of the sensor exceeds the threshold value or not within the preset time, the method provided by the embodiment of the invention is used for comparing the waveform output by the sensor in the whole motion process of the mobile terminal with the preset normal or abnormal waveform to identify whether the mobile terminal is abnormal or not, so that the problem that misjudgment is easy to occur in the prior art is avoided, and the identification precision of the abnormal behavior of the mobile terminal can be improved.
In order to enable those skilled in the art to more clearly understand the technical solution provided by the embodiment of the present invention, the following describes in detail the anti-theft method of the mobile terminal provided by the embodiment of the present invention through a specific embodiment, as shown in fig. 3, the method includes:
The positioning information may be geographical location information, such as longitude and latitude, obtained by a positioning module of the mobile terminal, and the positioning module may support one or more of the following satellite positioning systems: the Global Positioning System (GPS), the BeiDou Navigation satellite System (BDS), the Global Navigation satellite System (GLONASS), and the Galileo satellite Navigation System (Galileo satellite Navigation System).
The preset designated area may be, for example, an area of a home, a unit, or the like set in advance by the user. If the mobile terminal leaves the designated area, step 203 is executed, otherwise, steps 201 to 202 are executed again. That is, when the mobile terminal determines that the mobile terminal is located in a relatively safe area such as a home or a unit according to the positioning information, the alarm function may be turned off, and when it determines that the mobile terminal leaves the designated area according to the positioning information, the alarm function may be turned on to perform the subsequent processes.
And 203, monitoring a target sensor, wherein the target sensor comprises an acceleration sensor or a gravity sensor.
The acceleration sensor may be a linear acceleration sensor, an angular acceleration sensor, or a linear acceleration sensor or an angular acceleration sensor.
And 204, comparing the waveform of the output signal of the target sensor with a preset abnormal waveform and a preset normal waveform when the waveform of the output signal of the target sensor is detected.
The waveform of the output signal may be a distribution curve of acceleration values of the sensor synthesized from acceleration values of the sensor output acquired within a certain time T. If the acceleration sensor is a linear acceleration sensor, the acceleration value of the acceleration sensor is a triaxial acceleration value, and if the acceleration sensor is an angular acceleration sensor, the acceleration value of the acceleration sensor is an angular acceleration value.
For example, the action of using the mobile terminal by the user in a normal situation is different from the action of stealing the mobile terminal, taking a mobile phone placed in a pocket as an example, when the mobile phone is used normally, the action amplitude of taking the mobile phone out of the pocket by the user is large, so the wave crest of the waveform obtained according to the acceleration of an acceleration sensor (or a gravity sensor) in the mobile phone is large, and when a thief steals, the action amplitude of taking the mobile phone out of the pocket is small, and at the moment, the wave crest of the waveform obtained according to the acceleration of the acceleration sensor (or the gravity sensor) in the mobile phone is small. I.e., the peak of the normal waveform is larger and the peak of the abnormal waveform is smaller, the normal waveform and the abnormal waveform may be as shown in fig. 2, for example.
Further, in normal use, after the user takes out the mobile phone from the pocket, the mobile phone is usually turned over so that the screen of the mobile phone is right opposite to the user, and when the thief takes out the mobile phone from the pocket, the mobile phone is not used, so that the action of turning over the mobile phone is usually not performed, and therefore, preferably, the angular acceleration value of an angular acceleration sensor (such as a gyroscope) in the mobile phone can be further monitored, so that the identification is performed by combining a waveform generated by the angular acceleration value of the angular acceleration sensor in the mobile phone.
Therefore, a function model of an abnormal waveform when the mobile terminal is stolen and a function model of a normal waveform when the mobile terminal is normally used by a user can be preset in the mobile terminal, wherein if the mobile terminal comprises a plurality of sensors, the function model of the abnormal waveform and the function model of the normal waveform corresponding to each sensor can be preset.
When the mobile terminal fits a distribution curve of the acceleration value of the sensor according to the acceleration value output by the sensor acquired within a certain time T to obtain the waveform of the output signal, the normal waveform and the abnormal waveform within the time T can be respectively obtained according to the function model of the normal waveform and the function model of the abnormal waveform to be used as the preset normal waveform and the preset abnormal waveform, and then the waveform of the output signal is respectively compared with the normal waveform and the abnormal waveform to judge whether the waveform of the output signal is normal or abnormal or other irrelevant waveforms. Therefore, steps 205 to 206, 207 to 208, and 209 in the subsequent steps can be executed alternatively. The comparison method comprises the following steps: dynamic Time Warping (DTW) algorithm, Hidden Markov Model (HMM) algorithm, etc.
In addition, taking a mobile phone as an example, when the mobile phone is used normally, the screen is usually lighted after a user takes the mobile phone out of a pocket, and when a thief steals the mobile phone, the screen is not lighted after taking the mobile phone out of the pocket, so that after the waveforms of the output signals are compared according to the method, whether the screen is lighted or not can be continuously monitored, and the identification precision is further improved.
and step 206, learning the waveform of the output signal according to a preset learning algorithm to update the normal waveform.
Specifically, the waveform of the output signal is learned according to a preset learning algorithm to update the function model of the normal waveform, so that the normal waveform is closer to the real normal waveform, the recognition accuracy is higher and higher, and the misjudgment is less and less. Wherein, the learning method includes but is not limited to: llc (loglog counting) iterative self-learning algorithm, neural network, Support Vector Machine (SVM), clustering algorithm, or deep learning (deep learning) algorithm.
And step 207, if the waveform of the output signal is matched with the abnormal waveform, determining that the waveform of the output signal is abnormal, and alarming according to a preset alarm strategy. As shown in fig. 4, may include:
For example, the preset time may be set to 5 seconds, and if an alarm cancellation password is input from the password input interface within the preset time, it is determined that the alarm is false, the alarm is cancelled, and the alarm sound is stopped. If the alarm cancellation password is not input from the password input interface within the time, or the password is input incorrectly, the volume of the alarm sound is increased to the maximum value.
And 208, learning the waveform of the output signal according to a preset learning algorithm to update the abnormal waveform.
Similar to the steps 205 to 206, it can be understood that the waveform of the output signal is learned according to a preset learning algorithm to update the function model of the abnormal waveform, so that the abnormal waveform is closer to the real abnormal waveform, the recognition accuracy is higher and higher, and the misjudgment is less and less. Wherein, the learning method includes but is not limited to: LLC iterative self-learning algorithm, neural network, support vector machine, clustering algorithm, deep learning algorithm, etc.
and step 210, judging whether the mobile terminal is in a packet mode or not by using a light sensor and/or a distance sensor of the mobile terminal.
The bag mode is a mode in which the mobile terminal is placed in a light-tight space such as a pocket or a bag, and since the space is an irrelevant environment, whether the mobile terminal is in the bag mode can be sensed by a light sensor, or, since the space in the pocket or the bag is small, when the mobile terminal is placed in the space such as the pocket or the bag, particularly a trouser pocket, the mobile terminal is usually tightly attached to the inner wall of the pocket or the bag, and has a small distance from the inner wall of the pocket or the bag, and thus, whether the mobile terminal is in the bag mode can be determined by sensing the distance in combination with a distance sensor.
Step 210 may be executed after determining that the mobile terminal is located in the designated area in step 202, at this time, if the mobile terminal is not in the packet mode, step 203 is executed, otherwise, step 210 is continuously executed, as shown in fig. 5; alternatively, it may be executed simultaneously with step 201, and when step 202 determines that the mobile terminal is located in the designated area and step 210 determines that the mobile terminal is not in the packet mode, step 203 is executed again (not shown in the figure); alternatively, step 210 may be executed before step 201, and if it is determined that the mobile terminal is not in the packet mode, step 201 is executed, otherwise, step 210 is continuously executed (not shown in the figure).
In summary, the embodiment of the present invention provides an anti-theft method for a mobile terminal, which monitors a target sensor, where the target sensor includes an acceleration sensor or a gravity sensor; when the waveform of the output signal of the target sensor is detected, comparing the waveform of the output signal with a preset abnormal waveform and a preset normal waveform respectively; if the waveform of the output signal is matched with the normal waveform, determining that the waveform of the output signal is normal, and monitoring the target sensor again; and if the waveform of the output signal is matched with the abnormal waveform, determining that the waveform of the output signal is abnormal, and alarming according to a preset alarm strategy, compared with the method for identifying by adopting a single threshold of a sensor in the prior art, the method can improve the identification precision of the abnormal behavior of the mobile terminal. Meanwhile, whether the mobile terminal is in a safe designated area or not can be judged according to the positioning information of the mobile terminal, monitoring and follow-up processes of the target sensor can be executed after the mobile terminal leaves the designated area, the alarm function can be closed in unnecessary scenes, and the electric quantity is saved.
An embodiment of the present invention further provides a mobile terminal 10, as shown in fig. 6, where the mobile terminal includes:
the monitoring unit 101 is configured to monitor a target sensor, where the target sensor includes an acceleration sensor or a gravity sensor;
an identification unit 102 that, when detecting an output signal of the target sensor, determines whether a waveform of the output signal is abnormal;
and the processing unit 103 is used for reporting according to a preset alarm strategy when the waveform of the output signal is determined to be abnormal.
Optionally, the identifying unit 102 may be specifically configured to:
respectively comparing the waveform of the output signal with a preset abnormal waveform and a preset normal waveform;
if the waveform of the output signal is matched with the normal waveform, determining that the waveform of the output signal is normal, and monitoring the target sensor again;
and if the waveform of the output signal is matched with the abnormal waveform, determining that the waveform of the output signal is abnormal.
Optionally, as shown in fig. 7, the processing unit 103 includes: a learning unit 1031;
the learning unit 1031 is configured to: and after the waveform of the output signal is determined to be normal, learning the waveform of the output signal according to a preset learning algorithm so as to update the normal waveform.
The learning unit 1031 is further configured to: and after determining that the waveform of the output signal is abnormal, learning the waveform of the output signal according to a preset learning algorithm to update the abnormal waveform.
Optionally, as shown in fig. 8, the mobile terminal 10 further includes:
a positioning unit 104, configured to acquire positioning information of the mobile terminal before the target sensor is monitored;
a determining unit 105, configured to determine whether the mobile terminal is located in a preset designated area according to the positioning information;
the monitoring unit 101 is configured to perform the monitoring on the target sensor when the mobile terminal is located in the designated area.
Optionally, as shown in fig. 9, the mobile terminal 10 further includes:
a sensing unit 106, configured to determine whether the mobile terminal is in a packet mode by using a light sensor and/or a distance sensor of the mobile terminal before the monitoring of the target sensor;
the monitoring unit 101 is configured to perform the monitoring of the target sensor when the mobile terminal is not in the packet mode.
Optionally, as shown in fig. 10, the processing unit 103 includes: an alarm unit 1032, the alarm unit 1032 being operable to:
sending an alarm sound according to a preset volume, and displaying a password input interface for releasing the alarm on a screen of the mobile terminal;
if the alarm release password input from the password input interface is received within the preset time, stopping sending the alarm sound;
and if the alarm release password is not received within the preset time, increasing the volume of the alarm sound to the maximum value.
The present embodiment is used to implement the above method embodiments, and the working process and the working principle of each unit in the present embodiment refer to the description in the above method embodiments, which are not described herein again.
The embodiment of the invention provides a mobile terminal, which monitors a target sensor, wherein the target sensor comprises an acceleration sensor or a gravity sensor; when the waveform of the output signal of the target sensor is detected, comparing the waveform of the output signal with a preset abnormal waveform and a preset normal waveform respectively; if the waveform of the output signal is matched with the normal waveform, determining that the waveform of the output signal is normal, and monitoring the target sensor again; and if the waveform of the output signal is matched with the abnormal waveform, determining that the waveform of the output signal is abnormal, and alarming according to a preset alarm strategy, compared with the method for identifying by adopting a single threshold of a sensor in the prior art, the method can improve the identification precision of the abnormal behavior of the mobile terminal. Meanwhile, whether the mobile terminal is in a safe designated area or not can be judged according to the positioning information of the mobile terminal, monitoring and follow-up processes of the target sensor can be executed after the mobile terminal leaves the designated area, the alarm function can be closed in unnecessary scenes, and the electric quantity is saved.
An embodiment of the present invention provides a mobile terminal 20, as shown in fig. 11, where the mobile terminal 20 includes: the processor 201, the memory 202, the interface 203, the processor 201, the memory 202 and the interface 203 are connected through a bus 204; the interface 203 is configured to interact with other network elements, the memory 202 is configured to store a computer program 2021, the processor 201 is configured to execute the computer program 2021, and the processor 201 executes the computer program 2021 to:
monitoring a target sensor, wherein the target sensor comprises an acceleration sensor or a gravity sensor;
when the output signal of the target sensor is detected, judging whether the waveform of the output signal is abnormal or not;
and if the waveform of the output signal is determined to be abnormal, reporting according to a preset alarm strategy.
Optionally, the processor executes the computer program to specifically:
respectively comparing the waveform of the output signal with a preset abnormal waveform and a preset normal waveform;
if the waveform of the output signal is matched with the normal waveform, determining that the waveform of the output signal is normal, and monitoring the target sensor again;
and if the waveform of the output signal is matched with the abnormal waveform, determining that the waveform of the output signal is abnormal.
Optionally, the processor 201 executes the computer program 2021 to:
and after the waveform of the output signal is determined to be normal, learning the waveform of the output signal according to a preset learning algorithm so as to update the normal waveform.
Optionally, the processor 201 executes the computer program 2021 to:
and after determining that the waveform of the output signal is abnormal, learning the waveform of the output signal according to a preset learning algorithm to update the abnormal waveform.
Optionally, the processor 201 executes the computer program 2021 to:
before monitoring the target sensor, acquiring positioning information of the mobile terminal;
judging whether the mobile terminal is located in a preset designated area or not according to the positioning information;
and if the mobile terminal is positioned in the designated area, monitoring the target sensor.
Optionally, the processor 201 executes the computer program 2021 to:
before monitoring the target sensor, judging whether the mobile terminal is in a packet mode by using a light sensor and/or a distance sensor of the mobile terminal;
and if the mobile terminal is not in the packet mode, monitoring the target sensor.
Optionally, the processor 201 executes the computer program 2021 to:
sending an alarm sound according to a preset volume, and displaying a password input interface for releasing the alarm on a screen of the mobile terminal;
if the alarm release password input from the password input interface is received within the preset time, stopping sending the alarm sound;
and if the alarm release password is not received within the preset time, increasing the volume of the alarm sound to the maximum value.
The present embodiment is used to implement the above method embodiments, and the working process and the working principle of each unit in the present embodiment refer to the description in the above method embodiments, which are not described herein again.
The embodiment of the invention provides a mobile terminal, which monitors a target sensor, wherein the target sensor comprises an acceleration sensor or a gravity sensor; when the waveform of the output signal of the target sensor is detected, comparing the waveform of the output signal with a preset abnormal waveform and a preset normal waveform respectively; if the waveform of the output signal is matched with the normal waveform, determining that the waveform of the output signal is normal, and monitoring the target sensor again; and if the waveform of the output signal is matched with the abnormal waveform, determining that the waveform of the output signal is abnormal, and alarming according to a preset alarm strategy, compared with the method for identifying by adopting a single threshold of a sensor in the prior art, the method can improve the identification precision of the abnormal behavior of the mobile terminal. Meanwhile, whether the mobile terminal is in a safe designated area or not can be judged according to the positioning information of the mobile terminal, monitoring and follow-up processes of the target sensor can be executed after the mobile terminal leaves the designated area, the alarm function can be closed in unnecessary scenes, and the electric quantity is saved.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment. In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute some steps of the methods according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
It is obvious to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be performed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to perform all or part of the above described functions. For the specific working process of the device described above, reference may be made to the corresponding process in the foregoing method embodiment, which is not described herein again.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (18)
1. An anti-theft method for a mobile terminal, the method comprising:
monitoring a target sensor, wherein the target sensor comprises a linear acceleration sensor and an angular acceleration sensor;
when the output signal of the target sensor is detected, judging whether the waveform of the output signal is abnormal or not, and monitoring whether a screen is lightened or not;
if the waveform of the output signal is determined to be abnormal and the screen is not lightened, alarming according to a preset alarming strategy;
the judging whether the waveform of the output signal is abnormal includes:
respectively comparing the waveform of the output signal with a preset abnormal waveform and a preset normal waveform;
if the waveform of the output signal is matched with the normal waveform, determining that the waveform of the output signal is normal, and monitoring the target sensor again;
and if the waveform of the output signal is matched with the abnormal waveform, determining that the waveform of the output signal is abnormal.
2. The method of claim 1, after determining that the waveform of the output signal is normal, further comprising:
and learning the waveform of the output signal according to a preset learning algorithm so as to update the normal waveform.
3. The method of claim 1, after determining that the waveform of the output signal is abnormal, further comprising:
and learning the waveform of the output signal according to a preset learning algorithm so as to update the abnormal waveform.
4. The method of any one of claims 1-3, further comprising, prior to said monitoring the target sensor:
acquiring positioning information of the mobile terminal;
judging whether the mobile terminal is located in a preset designated area or not according to the positioning information;
and if the mobile terminal leaves the designated area, monitoring the target sensor.
5. The method of any one of claims 1-3, further comprising, prior to said monitoring the target sensor:
judging whether the mobile terminal is in a packet mode or not by using a light sensor and/or a distance sensor of the mobile terminal;
and if the mobile terminal is not in the packet mode, monitoring the target sensor.
6. The method according to any one of claims 1-3, wherein said alerting according to a preset alert policy comprises:
sending an alarm sound according to a preset volume, and displaying a password input interface for releasing the alarm on a screen of the mobile terminal;
if the alarm release password input from the password input interface is received within the preset time, stopping sending the alarm sound;
and if the alarm release password is not received within the preset time, increasing the volume of the alarm sound to the maximum value.
7. A mobile terminal, characterized in that the mobile terminal comprises:
the monitoring unit is used for monitoring a target sensor, and the target sensor comprises a linear acceleration sensor and an angular acceleration sensor;
an identification unit configured to determine whether a waveform of an output signal of the target sensor is abnormal when the output signal is detected;
the monitoring unit is also used for monitoring whether the screen is lightened;
the processing unit is used for alarming according to a preset alarm strategy when the waveform of the output signal is determined to be abnormal and the screen is not lightened;
the identification unit is specifically configured to:
respectively comparing the waveform of the output signal with a preset abnormal waveform and a preset normal waveform;
if the waveform of the output signal is matched with the normal waveform, determining that the waveform of the output signal is normal, and monitoring the target sensor again;
and if the waveform of the output signal is matched with the abnormal waveform, determining that the waveform of the output signal is abnormal.
8. The mobile terminal of claim 7, wherein the processing unit comprises: a learning unit to: and after the waveform of the output signal is determined to be normal, learning the waveform of the output signal according to a preset learning algorithm so as to update the normal waveform.
9. The mobile terminal of claim 7, wherein the processing unit comprises: a learning unit to: and after determining that the waveform of the output signal is abnormal, learning the waveform of the output signal according to a preset learning algorithm to update the abnormal waveform.
10. The mobile terminal according to any of claims 7-9, characterized in that the mobile terminal further comprises:
the positioning unit is used for acquiring positioning information of the mobile terminal before the target sensor is monitored;
the judging unit is used for judging whether the mobile terminal is positioned in a preset designated area or not according to the positioning information;
the monitoring unit is used for monitoring the target sensor when the mobile terminal leaves the designated area.
11. The mobile terminal according to any of claims 7-9, characterized in that the mobile terminal further comprises:
the sensing unit is used for judging whether the mobile terminal is in a packet mode or not by utilizing a light sensor and/or a distance sensor of the mobile terminal before monitoring the target sensor;
the monitoring unit is used for monitoring the target sensor when the mobile terminal is not in the packet mode.
12. The mobile terminal according to any of claims 7-9, wherein the processing unit comprises: an alarm unit for:
sending an alarm sound according to a preset volume, and displaying a password input interface for releasing the alarm on a screen of the mobile terminal;
if the alarm release password input from the password input interface is received within the preset time, stopping sending the alarm sound;
and if the alarm release password is not received within the preset time, increasing the volume of the alarm sound to the maximum value.
13. A mobile terminal, characterized in that the mobile terminal comprises: the processor, the memory, the interface, the processor, the memory and the interface are connected through a bus; the interface is configured to interact with other network elements, the memory is configured to store a computer program, the processor is configured to execute the computer program, and the processor executes the computer program to:
monitoring a target sensor, wherein the target sensor comprises a linear acceleration sensor and an angular acceleration sensor;
when the output signal of the target sensor is detected, judging whether the waveform of the output signal is abnormal or not, and monitoring whether a screen is lightened or not;
if the waveform of the output signal is determined to be abnormal and the screen is not lightened, alarming according to a preset alarming strategy;
the processor executing the computer program is specifically configured to:
respectively comparing the waveform of the output signal with a preset abnormal waveform and a preset normal waveform;
if the waveform of the output signal is matched with the normal waveform, determining that the waveform of the output signal is normal, and monitoring the target sensor again;
and if the waveform of the output signal is matched with the abnormal waveform, determining that the waveform of the output signal is abnormal.
14. The mobile terminal of claim 13, wherein the processor executes the computer program to:
and after the waveform of the output signal is determined to be normal, learning the waveform of the output signal according to a preset learning algorithm so as to update the normal waveform.
15. The mobile terminal of claim 13, wherein the processor executes the computer program to:
and after determining that the waveform of the output signal is abnormal, learning the waveform of the output signal according to a preset learning algorithm to update the abnormal waveform.
16. The mobile terminal of any of claims 13-15, wherein the processor executes the computer program to:
before monitoring the target sensor, acquiring positioning information of the mobile terminal;
judging whether the mobile terminal is located in a preset designated area or not according to the positioning information;
and if the mobile terminal leaves the designated area, monitoring the target sensor.
17. The mobile terminal of any of claims 13-15, wherein the processor executes the computer program to:
before monitoring the target sensor, judging whether the mobile terminal is in a packet mode by using a light sensor and/or a distance sensor of the mobile terminal;
and if the mobile terminal is not in the packet mode, monitoring the target sensor.
18. The mobile terminal according to any of claims 13-15, wherein the processor executes the computer program to perform the alerting according to a preset alert policy for:
sending an alarm sound according to a preset volume, and displaying a password input interface for releasing the alarm on a screen of the mobile terminal;
if the alarm release password input from the password input interface is received within the preset time, stopping sending the alarm sound;
and if the alarm release password is not received within the preset time, increasing the volume of the alarm sound to the maximum value.
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/CN2015/077662 WO2016172845A1 (en) | 2015-04-28 | 2015-04-28 | Anti-theft method for mobile terminal and mobile terminal |
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| Publication Number | Publication Date |
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| CN107534706A CN107534706A (en) | 2018-01-02 |
| CN107534706B true CN107534706B (en) | 2020-04-21 |
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| CN201580079217.9A Active CN107534706B (en) | 2015-04-28 | 2015-04-28 | Mobile terminal anti-theft method and mobile terminal |
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| CN (1) | CN107534706B (en) |
| WO (1) | WO2016172845A1 (en) |
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| CN109885951A (en) * | 2019-02-28 | 2019-06-14 | 中科云创(厦门)科技有限公司 | Equipment fault diagnosis method and device |
| US11567847B2 (en) | 2020-02-04 | 2023-01-31 | International Business Machines Corporation | Identifying anomolous device usage based on usage patterns |
| CN113079176B (en) * | 2021-04-14 | 2022-04-05 | 西安交通大学 | High-speed network flow abnormity detection system suitable for mass data |
| CN115223316B (en) * | 2022-07-06 | 2024-02-09 | 华为技术有限公司 | Intelligent commodity anti-theft alarm detection method |
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| Publication number | Publication date |
|---|---|
| WO2016172845A1 (en) | 2016-11-03 |
| CN107534706A (en) | 2018-01-02 |
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