CN116909161B

CN116909161B - Smart home control method and system based on wearable equipment

Info

Publication number: CN116909161B
Application number: CN202311161121.XA
Authority: CN
Inventors: 戴新财; 郏莉莉
Original assignee: Nanchang Institute of Technology
Current assignee: Nanchang Institute of Technology
Priority date: 2023-09-11
Filing date: 2023-09-11
Publication date: 2023-12-12
Anticipated expiration: 2043-09-11
Also published as: CN116909161A

Abstract

The invention provides an intelligent home control method and system based on wearable equipment, wherein the method comprises the steps of pre-accessing home equipment into a home gateway, and pre-associating the wearable equipment of a user with the home gateway; carrying out identity authentication on the home gateway, the wearable equipment and the home equipment, and determining that the user is an authenticated user or a non-authenticated user based on an identity authentication result; if the user is an authenticated user, determining a user behavior state according to the operation data, determining a behavior recognition result based on the user behavior state, and determining the user as a normal user or an abnormal user based on the behavior recognition result; if the user is a non-authenticated user and/or the user is an abnormal user, a blank user is constructed according to the user behavior state, and blank behaviors and blank data are added in the operation data.

Description

Smart home control method and system based on wearable equipment

Technical Field

The invention belongs to the technical field of household control, and particularly relates to an intelligent household control method and system based on wearable equipment.

Background

The intelligent home uses the home as a platform, integrates facilities related to home life by utilizing a comprehensive wiring technology, a network communication technology, a security technology, an automatic control technology and an audio-video technology, builds an efficient management system of home facilities and family schedule matters, improves the safety, convenience, comfort and artistry of the home, and realizes an environment-friendly and energy-saving living environment.

The existing household equipment can be controlled through wearable equipment worn by a user, such as an intelligent watch, and the household equipment respectively has unique energy consumption characteristics, flow characteristics and corresponding equipment behavior characteristics, so that illegal personnel can access a household gateway or a household control system through a network interface or other equipment interfaces, further, operation data and behavior data of the household equipment are obtained, privacy leakage of the user is caused, and if the user is worse, whether the user is at home or is in a single house in a certain time period or not can be judged through the behavior data of the household equipment, and the safety of the user is indirectly influenced.

Disclosure of Invention

In order to solve the technical problems, the invention provides an intelligent home control method and system based on wearable equipment, which are used for solving the technical problems in the prior art.

In a first aspect, the present application provides the following technical solutions, and a smart home control method based on a wearable device, where the method includes:

the method comprises the steps that home equipment is accessed into a home gateway in advance, and wearable equipment of a user is associated with the home gateway in advance;

carrying out identity authentication on the home gateway, the wearable equipment and the home equipment to obtain an identity authentication result, and determining that the user is an authenticated user or a non-authenticated user based on the identity authentication result;

if the user is an authenticated user, control instruction data of the wearable device is obtained, operation data of corresponding household equipment is obtained based on the control instruction data, a user behavior state is determined according to the operation data, a behavior recognition result is determined based on the user behavior state, and the user is determined to be a normal user or an abnormal user based on the behavior recognition result;

if the user is a non-authentication user and/or the user is an abnormal user, constructing a blank user according to the user behavior state and adding blank behaviors and blank data into the running data.

Compared with the prior art, the application has the beneficial effects that: firstly, home equipment is accessed into a home gateway in advance, and wearable equipment of a user is associated with the home gateway in advance; then, carrying out identity authentication on the home gateway, the wearable equipment and the home equipment to obtain an identity authentication result, and determining that the user is an authenticated user or a non-authenticated user based on the identity authentication result; if the user is an authenticated user, control instruction data of the wearable device is obtained, operation data of corresponding household equipment is obtained based on the control instruction data, a user behavior state is determined according to the operation data, a behavior recognition result is determined based on the user behavior state, and the user is determined to be a normal user or an abnormal user based on the behavior recognition result; if the user is a non-authentication user and/or the user is an abnormal user, a blank user is constructed according to the user behavior state, and blank behavior and blank data are added in the operation data.

Preferably, the step of authenticating the home gateway, the wearable device and the home device to obtain an authentication result, and determining that the user is an authenticated user or a non-authenticated user based on the authentication result includes:

controlling the wearable device to generate a first authentication character with X bitsAnd acquiring a first device identifier +.>With the first authentication key->And a second device identification of said home gateway +.>With a second authentication keyAnd based on said first authentication character +.>Said first device identification->Said first authentication key->Said second device identity +.>And said second authentication key->Calculate the first authentication information +.>And second authentication information->：

；

In the method, in the process of the invention,representing SM4 encryption algorithm,/->Representing a bit exclusive OR operation, ">Indicating the joining operation->Representing a first authentication key->Before->Byte->Representing a second authentication key->Before->A number of bytes;

the first authentication informationAnd the second authentication information->The third authentication information is calculated based on the first authentication message added to the first authentication message of the home gateway>：

；

In the method, in the process of the invention,representing first intermediate information- >Is->Byte->Representing first intermediate information->Before->Byte->Representing SM4 decryption algorithm;

the first authentication informationThe second authentication message added to the home equipment controls the home gateway to generate a second authentication character of X bits +.>Based on the second authentication message and the second authentication character +.>Calculate fourth authentication information +.>：

；

In the method, in the process of the invention,representing second intermediate information->Is->Byte->Representing second intermediate information->Before->A number of bytes;

controlling the household equipment to generate a third authentication character with X bitsBased on the third authentication character +.>Calculate fifth authentication information->：

；

The fifth authentication informationAdding the fifth authentication information into a first authentication message of the home gateway, and enabling the fifth authentication information to be ++>In a third authentication message added to the wearable device, calculating sixth authentication information +_based on the third authentication message>And seventh authentication information->：

；

；/>；

In the method, in the process of the invention,representing third intermediate information->Is->Byte->Representing third intermediate information->Before->Byte->Representing fourth intermediate information->Is->Byte->Representing fourth intermediate information->Before->A number of bytes;

Based on the third authentication informationSaid fourth authentication information->Said sixth authentication information->Said seventh authentication information->And determining an identity authentication result, and determining that the user is an authenticated user or a non-authenticated user based on the identity authentication result.

Preferably, the third authentication informationSaid fourth authentication information->Said sixth authentication information->Said seventh authentication information->The step of determining an identity authentication result, and determining whether the user is an authenticated user or a non-authenticated user based on the identity authentication result comprises:

judging the third authentication informationBefore->One byte and said second authentication key->Before->Whether or not the bytes are equal, if said third authentication information +.>Before->One byte and said second authentication key->Before->The bytes are equal, and the wearable device passes the authentication of the home gateway;

judging the fourth authentication informationBefore->One byte and the first authentication key->Before->Whether the bytes are equal, if said fourth authentication information +.>Before->One byte and the first authentication key->Before->The bytes are equal, and the wearable device passes the authentication of the household device;

Judging the sixth authentication informationSaid seventh authentication information->Whether or not to correspond to said first authentication character->Whether or not the first authentication information is equal, if the second authentication information is +.>Said seventh authentication information->And the first authentication character +.>If the two types of the wearable devices are equal, the home gateway and the home device pass through the authentication of the wearable devices;

if the wearable device passes the authentication of the home gateway, the authentication of the wearable device passes the authentication of the home device, and the authentication of the home gateway and the authentication of the wearable device pass the authentication of the home device, the user is an authenticated user, and if the wearable device fails the authentication of the home gateway and/or the authentication of the wearable device fails the authentication of the home device and/or the authentication of the home gateway and the authentication of the wearable device fails, the user is a non-authenticated user.

Preferably, the step of determining a user behavior state according to the operation data, determining a behavior recognition result based on the user behavior state, and determining that the user is a normal user or an abnormal user based on the behavior recognition result includes:

acquiring energy consumption data of the household equipment in a first preset time period Carrying out gray scale normalization processing on the energy consumption data to obtain an energy consumption gray value +.>：

；

In the method, in the process of the invention,、/>respectively historical maximum energy consumption data and historical minimum energy consumption data of the household equipment, < >>The gray value is not normalized;

based on the energy consumption gray valueDetermining an equipment energy consumption grid chart by taking the type of the household equipment as an abscissa and the first preset time period as an ordinate;

calculating the presence of the household equipment based on the equipment energy consumption grid graphEnergy consumption behavior at the moment +.>：

；

In the method, in the process of the invention,is a time factor->Is->Personal home appliance in->Energy consumption behavior at time, < >>Is->Personal home appliance in->Energy consumption data at a moment;

and determining the behavior change trend of the household equipment based on the energy consumption behavior quantity, determining a behavior recognition result based on the behavior change trend, and determining the user as a normal user or an abnormal user based on the behavior recognition result.

Preferably, the step of determining the behavior change trend of the home device based on the energy consumption behavior amount, determining a behavior recognition result based on the behavior change trend, and determining that the user is a normal user or an abnormal user based on the behavior recognition result includes:

Determining the change trend of the energy consumption behavior in a second preset time period, and judging whether the change trend is unchanged or tends to be stable;

if the change trend is unchanged or the change trend is stable, the behavior of the user is not changed, and the user is a normal user;

if the change trend is changed or the change trend is unstable, the behavior of the user is changed, a change time point is recorded, and the user is an abnormal user;

and acquiring a historical abnormal sample, inputting the historical abnormal sample into a preset convolutional neural network model for training, and inputting the change time point and the corresponding equipment energy consumption grid diagram into the trained preset convolutional neural network model to obtain the specific abnormal condition of the user behavior.

Preferably, the step of constructing a blank user according to the user behavior state and adding blank behavior and blank data in the running data includes:

determining a wearable device based on the user behavior stateCorresponding household device behavior->：

；

In the method, in the process of the invention,indicate->Personal home appliance->Indicate->Device behavior corresponding to individual household devices, +. >Indicate->The time when the device behavior corresponding to the individual home devices occurs;

based on the home device behaviorConstruction of blank user +.>And determining the user behavior of the blank user +.>：

；

In the method, in the process of the invention,indicate the ∈th of blank user>Individual behavior, ->Indicate the ∈th of blank user>The time of occurrence of the individual actions;

based on the home device behaviorDetermining a first probability of user behavior occurring at the corresponding moment +.>And a second probability of simultaneous occurrence of the two user actions +.>According to the first probability->Said second probability +.>Determining a mapping function between the behavior and the occurrence time of a blank user +.>：

；

In the method, in the process of the invention,for the current time pairUser home scene of the application->Behavior representing blank users before the current time, +.>The symmetry analysis result of the historical behavior of the user is obtained;

based on the mapping functionDetermining a blank behavior of said blank user +.>And add blank behavior +.>Blank data.

Preferably, the mapping function is based onDetermining a blank behavior of said blank user +.>And add blank behavior +.>The step of blank data includes:

based on the mapping function Determining a blank behavior of said blank user +.>：

；

In the method, in the process of the invention,is the ∈th of blank user>Mapping function corresponding to individual behavior, +.>Is a safety protection force;

for the blank behaviorPerforming symmetry test and extracting said blank behavior +.>Corresponding device behavior flow data;

capturing original behavior traffic of the home equipment, constructing blank equipment based on IP addresses of the home equipment, the home gateway and the wearable equipment, and establishing a blank data packet based on the original behavior traffic and the blank equipment;

adding blank behavior to the operation dataAnd the blank data package and the blank behavior +.>And adding the corresponding equipment behavior flow data into the operation data as blank data.

In a second aspect, the present invention provides the following technical solutions, a smart home control system based on a wearable device, where the system includes:

the association module is used for pre-accessing the home equipment into the home gateway and pre-associating the wearable equipment of the user with the home gateway;

the authentication module is used for carrying out identity authentication on the home gateway, the wearable equipment and the home equipment to obtain an identity authentication result, and determining that the user is an authenticated user or a non-authenticated user based on the identity authentication result;

The behavior determination module is used for acquiring control instruction data of the wearable equipment if the user is an authenticated user, acquiring operation data of corresponding household equipment based on the control instruction data, determining a user behavior state according to the operation data, determining a behavior recognition result based on the user behavior state, and determining that the user is a normal user or an abnormal user based on the behavior recognition result;

and the data interference module is used for constructing a blank user according to the user behavior state and adding blank behaviors and blank data into the running data if the user is a non-authentication user and/or the user is an abnormal user.

In a third aspect, the present invention provides a computer, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the processor implements the smart home control method based on the wearable device when executing the computer program.

In a fourth aspect, the present invention provides a storage medium, where a computer program is stored, and when the computer program is executed by a processor, the method for controlling smart home based on wearable devices is implemented.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a flowchart of a smart home control method based on a wearable device according to a first embodiment of the present invention;

fig. 2 is a detailed flowchart of step S2 in the smart home control method based on the wearable device according to the first embodiment of the present invention;

fig. 3 is a detailed flowchart of step S26 in the smart home control method based on the wearable device according to the first embodiment of the present invention;

fig. 4 is a detailed flowchart of step S3 in the smart home control method based on the wearable device according to the first embodiment of the present invention;

fig. 5 is a detailed flowchart of step S34 in the smart home control method based on the wearable device according to the first embodiment of the present invention;

fig. 6 is a detailed flowchart of step S4 in the smart home control method based on the wearable device according to the first embodiment of the present invention;

Fig. 7 is a detailed flowchart of step S44 in the smart home control method based on the wearable device according to the first embodiment of the present invention;

fig. 8 is a block diagram of a smart home control system based on a wearable device according to a second embodiment of the present invention;

fig. 9 is a block diagram of a hardware structure of a computer according to another embodiment of the present invention.

Embodiments of the present invention will be further described below with reference to the accompanying drawings.

Detailed Description

In order that the invention may be readily understood, a more complete description of the invention will be rendered by reference to the appended drawings. Several embodiments of the invention are presented in the figures. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.

Example 1

As shown in fig. 1, in a first embodiment of the present application, the present application provides a smart home control method based on a wearable device, where the method includes:

s1, pre-accessing home equipment into a home gateway, and pre-associating wearable equipment of a user with the home gateway;

specifically, in a general home system, the home system is composed of a user control terminal, a home gateway and specific home equipment, in the application, the user control terminal is specifically wearable equipment worn by a user, in the actual home control process, the user sends a control instruction to the home gateway through the wearable equipment, and the home gateway controls the corresponding home equipment to operate according to the issued control instruction, so that the home equipment needs to be accessed into the home gateway in advance before the home control is realized, the wearable equipment of the user and the home gateway are associated in advance, and in the step, the wearable equipment does not perform an identity authentication process, so that the home equipment cannot be specifically controlled.

S2, carrying out identity authentication on the home gateway, the wearable equipment and the home equipment to obtain an identity authentication result, and determining that the user is an authenticated user or a non-authenticated user based on the identity authentication result;

Specifically, before home control is achieved, identity authentication needs to be performed on the home gateway, the wearable device and the home device, firstly, identity authentication is performed on the home gateway and the home device by the identity of the wearable device, meanwhile, identity authentication is performed on the home gateway and the home device by the user's wearable device, specific control can be performed on specific home device only after the home gateway, the wearable device and the home device are authenticated, and after the user is determined to be an authenticated user, and when the user is determined to be a non-authenticated user, it is determined that the user does not have the right of controlling the home device, and therefore specific operation cannot be performed on specific home device.

As shown in fig. 2, the step S2 includes:

s21, controlling the wearable device to generate a first authentication character with X bitsAnd acquiring a first device identifier +.>With the first authentication key->And a second device identification of said home gateway +.>With a second authentication key->And based on said first authentication character +.>Said first device identification->Said first authentication key- >Said second device identity +.>And said second authentication key->Calculate the first authentication information +.>And second authentication information->：

；

specifically, the first authentication characterIn particular a 64-bit random number, and the first device identification of the household device +.>With the first authentication key->And a second device identification of said home gateway +.>With a second authentication key->Can be obtained specifically according to specific home equipment addresses and factory information.

S22, the first authentication informationAnd the second authentication information->The third authentication information is calculated based on the first authentication message added to the first authentication message of the home gateway>：

；

In the method, in the process of the invention,representing first intermediate information->Is->Byte->Representing first intermediate information->Before->Byte->Representing SM4 decryption algorithm;

specifically, the first authentication information is calculatedAnd the second authentication information->Thereafter, the wearable device will add the first authentication information +.>And the second authentication information->The first authentication message is specifically a CoAP message, the payload of the first authentication message is 256 bits, and the first authentication message is added with the first authentication information +. >And the second authentication information->Then the first authentication message is sent to the home gateway, and the home gateway calculates corresponding third authentication information according to the first authentication message>。

S23, the first authentication informationThe second authentication message added to the home equipment controls the home gateway to generate a second authentication character of X bits +.>Based on the second authentication message and the second authentication character +.>Calculate fourth authentication information +.>：

；

in particular, the second authentication character thereinAlso a 64-bit random number, the home gateway will add the first authentication information +.>The second authentication message is also a CoAP message, and after the second authentication message is received, the home equipment receives the second authentication message, and then the second authentication message and the second authentication character->Calculating fourth authentication information。

S24, controlling the household equipment to generate a third authentication character with X bitsBased on the third authentication characterCalculate fifth authentication information->：

；

Specifically, the third authentication characterAlso a 64-bit random number.

S25, the fifth authentication information Adding the fifth authentication information into a first authentication message of the home gateway, and enabling the fifth authentication information to be ++>In a third authentication message added to the wearable device, calculating sixth authentication information +_based on the third authentication message>And seventh authentication information->：

；

；/>；

specifically, in generating the fifth authentication informationAfter that, the home device will add fifth authentication information +.>In the first authentication message sent to the home gateway, the first authentication message can determine the corresponding message of the message, the message identifier of the message is the same as the message verifiable message received by the home device from the home gateway, and when the home gateway receives the third authentication message, the home gateway can send fifth authentication information->In a third authentication message sent to the wearable device, then sixth authentication information can be calculated according to the third authentication message>And seventh authentication information->。

S26, based on the third authentication informationSaid fourth authentication information- >Said sixth authentication information->Said seventh authentication information->Determining an identity authentication result, and determining that the user is an authenticated user or a non-authenticated user based on the identity authentication result;

as shown in fig. 3, the step S26 includes:

s261, judging the third authentication informationBefore->One byte and said second authentication key->Before->Whether or not the bytes are equal, if said third authentication information +.>Before->One byte and said second authentication key->Before->The bytes are equal, and the wearable device passes the authentication of the home gateway;

specifically, after the wearable device passes the authentication of the home gateway, the home gateway creates a session related to the wearable device, such as the third authentication informationBefore->One byte and said second authentication key->Before->The bytes are not equal, the wearable device cannot pass the authentication of the home gateway.

S262, judging the fourth authentication informationBefore->One byte and the first authentication key->Before->Whether the bytes are equal, if said fourth authentication information +.>Before->One byte and the first authentication key->Before->The bytes are equal, and the wearable device passes the authentication of the household device;

Specifically, after the wearable device passes the authentication of the home device, the home device creates a session related to the wearable device, such as the fourth authentication informationBefore->One byte and the first authentication key->Before->If the bytes are not equal, the wearable device cannot pass through the household deviceAnd (5) authentication.

S263, judging the sixth authentication informationSaid seventh authentication information->Whether to match the first authentication characterWhether or not the first authentication information is equal, if the second authentication information is +.>Said seventh authentication information->And the first authentication character +.>If the two types of the wearable devices are equal, the home gateway and the home device pass through the authentication of the wearable devices;

specifically, the sixth authentication informationSaid seventh authentication information->Whether to match the first authentication characterEqual, because the corresponding home gateway and home device can then decrypt the information sent by the wearable device.

S264, if the wearable device passes the authentication of the home gateway, the authentication of the wearable device passes the authentication of the home device, the authentication of the home gateway and the authentication of the wearable device pass the authentication of the home device, the user is an authenticated user, and if the wearable device fails the authentication of the home gateway and/or the authentication of the wearable device fails the authentication of the home device and/or the authentication of the home gateway and the authentication of the wearable device do not pass the authentication of the home device, the user is a non-authenticated user.

S3, if the user is an authenticated user, acquiring control instruction data of the wearable device, acquiring operation data of corresponding household equipment based on the control instruction data, determining a user behavior state according to the operation data, determining a behavior recognition result based on the user behavior state, and determining that the user is a normal user or an abnormal user based on the behavior recognition result;

specifically, after the user is the authenticated user, the corresponding control instruction data, namely the control instruction, can be issued through the wearable device, the corresponding household equipment is controlled to operate through the corresponding control instruction, the operation data of the corresponding household equipment is obtained, then the behavior state of the user can be determined according to the operation data, and the user can be judged to be a normal user or an abnormal user based on the behavior state.

As shown in fig. 4, the step S3 includes:

s31, acquiring energy consumption data of the household equipment in a first preset time periodCarrying out gray scale normalization processing on the energy consumption data to obtain an energy consumption gray value +.>：

；

In the method, in the process of the invention,、/>respectively the homeHistorical maximum energy consumption data and historical minimum energy consumption data of living equipment, and +. >The gray value is not normalized;

specifically, after the energy consumption data is obtained, denoising processing is needed for the energy consumption data so as to facilitate the subsequent processing process, and after the specific energy consumption gray level is obtained, the energy consumption of the household equipment is judged according to the color of the energy consumption gray level value, the darker the color is, the larger the energy consumption of the household equipment is, and the lighter the color is, the smaller the energy consumption of the household equipment is.

S32, based on the energy consumption gray valueDetermining an equipment energy consumption grid chart by taking the type of the household equipment as an abscissa and the first preset time period as an ordinate;

specifically, the first preset time period can be positioned for one hour, each five minutes is used as a scale, and the equipment energy consumption grid diagram representing the energy consumption of the household equipment can be obtained by combining the types of the household equipment.

S33, calculating the presence of the household equipment based on the equipment energy consumption grid chartEnergy consumption behavior at the moment +.>：

；

the time factor can be determined according to different household devices, the value range of the time factor is 0-1, and the energy consumption behavior can represent the variation degree of energy consumption in a period of time.

S34, determining a behavior change trend of the household equipment based on the energy consumption behavior quantity, determining a behavior recognition result based on the behavior change trend, and determining that the user is a normal user or an abnormal user based on the behavior recognition result;

as shown in fig. 5, the step S34 includes:

s341, determining a change trend of the energy consumption behavior in a second preset time period, and judging whether the change trend is unchanged or tends to be stable;

specifically, in a period of time, the energy consumption behavior is in an increasing relationship, which indicates that the change trend is increasing, the energy consumption behavior is in a decreasing relationship, which indicates that the change trend is decreasing, and when the absolute value of the difference between the energy consumption behaviors at two adjacent moments is greater than a preset threshold, the change trend is unstable, and when the absolute value of the difference between the energy consumption behaviors at two adjacent moments is not greater than the preset threshold, the change trend is stable.

S342, if the change trend is unchanged or the change trend is stable, the behavior of the user is not changed, and the user is a normal user;

specifically, by dividing the second preset time period into two identical time periods, whether the user is normal can be judged by whether the change trend in the two time periods changes and whether the change trend tends to be stable, for example, when the change trend of the user in the first time period is rising, the change trend in the second time period is also rising, the user is indicated to be a normal user, when the change trend of the user in the first time period is rising or falling, and the change trend in the second time period is stable, the user is indicated to be a normal user.

S343, if the change trend is changed or the change trend is unstable, the behavior of the user is changed, a change time point is recorded, and the user is an abnormal user;

specifically, when the change trend of the user in the first time period is rising, and the change trend in the second time period is falling, the user is indicated to be an abnormal user, and when the change trend of the user in the first time period is rising or falling, the change trend in the second time period is unstable, the user is indicated to be an abnormal user.

S344, acquiring a historical abnormal sample, inputting the historical abnormal sample into a preset convolutional neural network model for training, and inputting the change time point and a corresponding equipment energy consumption grid diagram into the trained preset convolutional neural network model to obtain a specific abnormal condition of user behavior;

the preset convolutional neural network model is a VGGNeT model, after a historical abnormal sample is analyzed through the model, the purpose of training the model can be achieved through training a loss function, then a change time point and an equipment energy consumption grid diagram corresponding to an abnormal user are input into the trained model, and specific abnormal conditions of user behaviors, such as abnormal conditions of a specific equipment at a certain time point or at a certain time, can be obtained.

S4, if the user is a non-authentication user and/or the user is an abnormal user, constructing a blank user according to the user behavior state and adding blank behaviors and blank data into the operation data;

specifically, when the user is determined to be an unauthorized user and/or an abnormal user, the representative user may be an illegal user, so that in order to further improve the protection of privacy, blank behaviors and blank data are added into daily operation data of the home equipment, if the illegal user obtains the operation data of the home equipment, it cannot be determined which data are real behaviors and which data are blank behaviors, and therefore, the illegal user cannot obtain behavior characteristics of the user according to the operation data.

As shown in fig. 6, the step S4 includes:

s41, determining the wearable device based on the user behavior stateCorresponding household device behavior->：

；

In the method, in the process of the invention,indicate->Personal home appliance->Indicate->Device behavior corresponding to individual household devices, +.>Indicate->The time when the device behavior corresponding to the individual home devices occurs;

s42, based on the household equipment behaviorsConstruction of blank user +.>And determining the user behavior of the blank user +. >：

；

specifically, the virtual behavior of the user behavior of the blank user can be added into the real behavior of the user to achieve the confusion effect.

S43, based on the household equipment behaviorsDetermining a first probability of user behavior occurring at the corresponding moment +.>And a second probability of simultaneous occurrence of the two user actions +.>According to the first probability->Said second probability +.>Determining a mapping function between the behavior and the occurrence time of a blank user +.>：

；

In the method, in the process of the invention,for the user home scene corresponding to the current time, < +.>Behavior representing blank users before the current time, +.>The symmetry analysis result of the historical behavior of the user is obtained;

specifically, by considering a plurality of factors to construct a mapping function, a real user can be simulated, the situation that the difference between real behavior data and blank behaviors is too large is avoided, meanwhile, the logic integrity of the behaviors of the blank user can be improved, the first probability can be obtained by analyzing the behavior data of the user in a period of time and determining corresponding sample data, the probability that a certain behavior occurs at a certain moment can be calculated through the sample data, the second probability can be specifically expressed as the sequential probability of the behaviors, namely, the behaviors of certain household equipment can be linked, namely, the behaviors can follow the behavior of the other household equipment after the behavior occurs, and therefore, the probability that the two behaviors occur concomitantly, namely, the second probability can be obtained through the association between the behaviors of the user.

S44, based on the mapping functionDetermining a blank behavior of said blank user +.>And add blank behavior +.>Blank data;

as shown in fig. 7, the step S44 includes:

s441, based on the mapping functionDetermining a blank behavior of said blank user +.>：

；

in particular, whereinAs the mapping function in the above steps, which reflects the mapping relation between the behavior and the occurrence time of the blank user, the security protection is +.>The purpose of joining is to balance the relationship between privacy protection and resource occupation, and the security protection is +.>The size of the system can be changed according to specific household equipment, and when the security protection force is increased +.>When the security protection capability is improved, namely the number of blank behaviors is increased but the corresponding resource occupation is also increased, when the security protection force is reduced +.>When the privacy preserving capability is reduced, the number of blank actions is reduced and the corresponding resource occupation is also reduced.

S442, for the blank behaviorPerforming symmetry test and extracting said blank behavior +. >Corresponding device behavior flow data;

specifically, in order to ensure that a certain logic relationship exists between blank behaviors, the blank behaviors are influenced by not only the current behavior but also the previous behavior, so that the consistency and the logic property of the blank behaviors can be ensured by the symmetry test.

S443, capturing original behavior traffic of the home equipment, constructing blank equipment based on IP addresses of the home equipment, the home gateway and the wearable equipment, and establishing a blank data packet based on the original behavior traffic and the blank equipment;

specifically, each device behavior has corresponding behavior flow, so that illegal users can be confused by constructing blank devices, and home devices are confused, so that an attacker cannot judge whether the obtained device behavior is the real behavior of the real home devices or the blank behavior.

S444, adding blank behaviors to the operation dataAnd the blank data packet and the blank behavior are combinedCorresponding equipment behavior flow data is added into the operation data as blank data;

specifically, by means of the blank data and the blank behaviors, an illegal user can not distinguish whether the data and the behaviors come from the real behaviors and the data generated by the corresponding household equipment controlled by the wearable equipment, so that privacy protection capability and safety of household control are improved.

The first advantage of this embodiment is: firstly, home equipment is accessed into a home gateway in advance, and wearable equipment of a user is associated with the home gateway in advance; then, carrying out identity authentication on the home gateway, the wearable equipment and the home equipment to obtain an identity authentication result, and determining that the user is an authenticated user or a non-authenticated user based on the identity authentication result; if the user is an authenticated user, control instruction data of the wearable device is obtained, operation data of corresponding household equipment is obtained based on the control instruction data, a user behavior state is determined according to the operation data, a behavior recognition result is determined based on the user behavior state, and the user is determined to be a normal user or an abnormal user based on the behavior recognition result; if the user is a non-authentication user and/or the user is an abnormal user, a blank user is constructed according to the user behavior state, and blank behavior and blank data are added in the operation data.

Example two

As shown in fig. 8, in a second embodiment of the present invention, there is provided a smart home control system based on a wearable device, the system including:

the association module 1 is used for pre-accessing home equipment into a home gateway and pre-associating the wearable equipment of the user with the home gateway;

the authentication module 2 is used for carrying out identity authentication on the home gateway, the wearable equipment and the home equipment to obtain an identity authentication result, and determining that the user is an authenticated user or a non-authenticated user based on the identity authentication result;

the behavior determining module 3 is configured to obtain control instruction data of the wearable device if the user is an authenticated user, obtain operation data of a corresponding home device based on the control instruction data, determine a user behavior state according to the operation data, determine a behavior recognition result based on the user behavior state, and determine that the user is a normal user or an abnormal user based on the behavior recognition result;

and the data interference module 4 is used for constructing a blank user according to the user behavior state and adding blank behaviors and blank data into the running data if the user is a non-authentication user and/or the user is an abnormal user.

Wherein the authentication module 2 comprises:

a first authentication sub-module for controlling the wearable device to generate a first authentication character with X bitsAnd acquiring a first device identifier +.>With the first authentication key->And a second device identification of said home gateway +.>With a second authentication key->And based on said first authentication character +.>Said first device identification->Said first authentication key->Said second device identity +.>And said second authentication key->Calculate the first authentication information +.>And second authentication information->：

；

a second authentication sub-module for authenticating the first authentication informationAnd the second authentication information->The third authentication information is calculated based on the first authentication message added to the first authentication message of the home gateway>：

；

a third authentication sub-module for comparing the first authentication information with the second authentication information The second authentication message added to the home equipment controls the home gateway to generate a second authentication character of X bits +.>Based on the second authentication message and the second authentication character +.>Calculate fourth authentication information +.>：

；

a fourth authentication sub-module for controlling the home device to generate a third authentication character with X bitsBased on the third authentication character +.>Calculate fifth authentication information->：

；

A fifth authentication sub-module for authenticating the fifth authentication informationAdding the fifth authentication information into a first authentication message of the home gateway, and enabling the fifth authentication information to be ++>In a third authentication message added to the wearable device, calculating sixth authentication information +_based on the third authentication message>And seventh authentication information->：

；

；/>；

In the method, in the process of the invention,representing third intermediate information->Is->Byte->Representing third intermediate information->Before->Byte->Representing fourth intermediate information->Is->Byte->Representing fourth intermediate information->Before->A number of bytes; />

A sixth authentication sub-module for based on the third authentication information Said fourth authentication information->Said sixth authentication information->Said seventh authentication information->And determining an identity authentication result, and determining that the user is an authenticated user or a non-authenticated user based on the identity authentication result.

The sixth authentication submodule includes:

a first judging unit for judging the third authentication informationBefore->One byte with the second authentication keyBefore->Whether or not the bytes are equal, if said third authentication information +.>Before->One byte and said second authentication key->Before->The bytes are equal, and the wearable device passes the authentication of the home gateway;

a second judging unit for judging the fourth authentication informationBefore->One byte with the first authentication keyBefore->Whether the bytes are equal, if said fourth authentication information +.>Before->One byte and the first authentication key->Before->The bytes are equal, and the wearable device passes the authentication of the household device;

a third judging unit for judging the sixth authentication informationSaid seventh authentication information->Whether or not to correspond to said first authentication character->Whether or not the first authentication information is equal, if the second authentication information is +.>Said seventh authentication information- >And the first authentication character +.>If the two types of the wearable devices are equal, the home gateway and the home device pass through the authentication of the wearable devices;

the fourth judging unit is configured to determine that the user is an authenticated user if the wearable device passes the authentication of the home gateway, the authentication of the wearable device passes the authentication of the home device, and the authentication of the home gateway and the authentication of the wearable device pass the authentication of the home device, and determine that the user is a non-authenticated user if the wearable device fails the authentication of the home gateway and/or the authentication of the wearable device fails the authentication of the home device and/or the authentication of the home gateway and the authentication of the wearable device do not pass the authentication of the home device.

The behavior determination module 3 includes:

an acquisition sub-module for acquiring energy consumption data of the home equipment in a first preset time periodCarrying out gray scale normalization processing on the energy consumption data to obtain an energy consumption gray value +.>：

；

a grid chart determining sub-module for determining a gray value based on the energy consumptionDetermining an equipment energy consumption grid chart by taking the type of the household equipment as an abscissa and the first preset time period as an ordinate;

The energy consumption behavior calculation operator module is used for calculating the condition that the household equipment is in the household based on the equipment energy consumption grid graphEnergy consumption behavior at the moment +.>：

；

and the identification sub-module is used for determining the behavior change trend of the household equipment based on the energy consumption behavior quantity, determining a behavior identification result based on the behavior change trend, and determining that the user is a normal user or an abnormal user based on the behavior identification result.

The identification submodule comprises:

the first determining unit is used for determining the change trend of the energy consumption behavior in a second preset time period and judging whether the change trend is unchanged or tends to be stable;

the second determining unit is used for determining that the behavior of the user is unchanged and the user is a normal user if the change trend is unchanged or the change trend is stable;

a third determining unit, configured to change the behavior of the user and record a change time point if the change trend changes or the change trend is unstable, where the user is an abnormal user;

The anomaly determination unit is used for acquiring a historical anomaly sample, inputting the historical anomaly sample into a preset convolutional neural network model for training, and inputting the change time point and the corresponding equipment energy consumption grid diagram into the preset convolutional neural network model after training so as to obtain the specific anomaly condition of the user behavior.

The data interference module 4 includes:

a first behavior determination submodule for determining a wearable device based on the user behavior stateCorresponding household device behavior->：

；

a second behavior determination sub-module for determining a behavior of the household device based on the household deviceConstruction of blank user +.>And determining the user behavior of the blank user +.>：

；

a function determination submodule for determining the behavior of the household equipment based on the household equipmentDetermining a first probability of user behavior occurring at the corresponding moment +.>And a second probability of simultaneous occurrence of the two user actions +.>According to the first probability- >Said second probability +.>Determining a mapping function between the behavior and the occurrence time of a blank user +.>：

；

a behavior adding sub-module for adding a behavior based on the mapping functionDetermining a blank behavior of said blank user +.>And add blank behavior +.>Blank data.

The behavior adding submodule comprises:

a behavior determination unit for determining the behavior of the object based on the mapping functionDetermining a blank behavior of said blank user +.>：

；

a checking unit for checking the blank behaviorPerforming symmetry test and extracting said blank behavior +.>Corresponding device behavior flow data;

the data packet unit is used for capturing the original behavior flow of the home equipment, constructing blank equipment based on the IP addresses of the home equipment, the home gateway and the wearable equipment, and establishing a blank data packet based on the original behavior flow and the blank equipment;

An adding unit for adding blank behavior to the operation dataAnd the blank data package and the blank behavior +.>And adding the corresponding equipment behavior flow data into the operation data as blank data.

In other embodiments of the present application, a computer is provided in the embodiments of the present application, including a memory 102, a processor 101, and a computer program stored in the memory 102 and executable on the processor 101, where the processor 101 implements the smart home control method based on a wearable device described above when executing the computer program.

In particular, the processor 101 may include a Central Processing Unit (CPU), or an application specific integrated circuit (Application Specific Integrated Circuit, abbreviated as ASIC), or may be configured as one or more integrated circuits that implement embodiments of the present application.

Memory 102 may include, among other things, mass storage for data or instructions. By way of example, and not limitation, memory 102 may comprise a Hard Disk Drive (HDD), floppy Disk Drive, solid state Drive (Solid State Drive, SSD), flash memory, optical Disk, magneto-optical Disk, tape, or universal serial bus (Universal Serial Bus, USB) Drive, or a combination of two or more of the foregoing. Memory 102 may include removable or non-removable (or fixed) media, where appropriate. The memory 102 may be internal or external to the data processing apparatus, where appropriate. In a particular embodiment, the memory 102 is a Non-Volatile (Non-Volatile) memory. In a particular embodiment, the Memory 102 includes Read-Only Memory (ROM) and random access Memory (Random Access Memory, RAM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (Programmable Read-Only Memory, abbreviated PROM), an erasable PROM (Erasable Programmable Read-Only Memory, abbreviated EPROM), an electrically erasable PROM (Electrically Erasable Programmable Read-Only Memory, abbreviated EEPROM), an electrically rewritable ROM (Electrically Alterable Read-Only Memory, abbreviated EAROM), or a FLASH Memory (FLASH), or a combination of two or more of these. The RAM may be Static Random-Access Memory (SRAM) or dynamic Random-Access Memory (Dynamic Random Access Memory DRAM), where the DRAM may be a fast page mode dynamic Random-Access Memory (Fast Page Mode Dynamic Random Access Memory FPMDRAM), extended data output dynamic Random-Access Memory (Extended Date Out Dynamic Random Access Memory EDODRAM), synchronous dynamic Random-Access Memory (Synchronous Dynamic Random-Access Memory SDRAM), or the like, as appropriate.

Memory 102 may be used to store or cache various data files that need to be processed and/or communicated, as well as possible computer program instructions for execution by processor 101.

The processor 101 reads and executes the computer program instructions stored in the memory 102 to implement the smart home control method based on the wearable device.

In some of these embodiments, the computer may also include a communication interface 103 and a bus 100. As shown in fig. 9, the processor 101, the memory 102, and the communication interface 103 are connected to each other via the bus 100 and perform communication with each other.

The communication interface 103 is used to implement communications between modules, devices, units, and/or units in embodiments of the application. The communication interface 103 may also enable communication with other components such as: and the external equipment, the image/data acquisition equipment, the database, the external storage, the image/data processing workstation and the like are used for data communication.

Bus 100 includes hardware, software, or both, coupling components of a computer to each other. Bus 100 includes, but is not limited to, at least one of: data Bus (Data Bus), address Bus (Address Bus), control Bus (Control Bus), expansion Bus (Expansion Bus), local Bus (Local Bus). By way of example, and not limitation, bus 100 may include a graphics acceleration interface (Accelerated Graphics Port), abbreviated AGP, or other graphics Bus, an enhanced industry standard architecture (Extended Industry Standard Architecture, abbreviated EISA) Bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an industry standard architecture (Industry Standard Architecture, ISA) Bus, a wireless bandwidth (InfiniBand) interconnect, a Low Pin Count (LPC) Bus, a memory Bus, a micro channel architecture (Micro Channel Architecture, abbreviated MCa) Bus, a peripheral component interconnect (Peripheral Component Interconnect, abbreviated PCI) Bus, a PCI-Express (PCI-X) Bus, a serial advanced technology attachment (Serial Advanced Technology Attachment, abbreviated SATA) Bus, a video electronics standards association local (Video Electronics Standards Association Local Bus, abbreviated VLB) Bus, or other suitable Bus, or a combination of two or more of the foregoing. Bus 100 may include one or more buses, where appropriate. Although embodiments of the application have been described and illustrated with respect to a particular bus, the application contemplates any suitable bus or interconnect.

The computer can execute the intelligent home control method based on the wearable equipment based on the obtained intelligent home control system based on the wearable equipment, thereby realizing the home control based on the wearable equipment.

In still other embodiments of the present application, in combination with the smart home control method based on a wearable device, the embodiments of the present application provide a technical solution, a storage medium, where a computer program is stored on the storage medium, where the computer program is executed by a processor to implement the smart home control method based on a wearable device.

Those of skill in the art will appreciate that the logic and/or steps represented in the flow diagrams or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.

More specific examples (a non-exhaustive list) of the readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer readable medium may even be paper or other suitable medium on which the program is printed, as the program may be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory.

It is to be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.

The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.

Claims

1. An intelligent home control method based on wearable equipment, which is characterized by comprising the following steps:

if the user is a non-authentication user and/or the user is an abnormal user, constructing a blank user according to the user behavior state and adding blank behaviors and blank data into the operation data;

the step of constructing the blank user according to the user behavior state and adding the blank behavior and the blank data into the operation data comprises the following steps:

；

In the method, in the process of the invention,indicate the ∈th of blank user >Individual behavior, ->Indicate the ∈th of blank user>The time of occurrence of the individual actions;

；

based on the mapping functionDetermining a blank behavior of said blank user +.>And add blank behavior +.>Blank data;

said mapping function basedDetermining a blank behavior of said blank user +.>And at the number of operationsBlank behavior of blank user added thereto +.>The step of blank data includes:

based on the mapping functionDetermining a blank behavior of said blank user +.>：

；

for the blank behaviorPerforming symmetry test and extracting said blank behavior +. >Corresponding device behavior flow data;

2. The smart home control method based on a wearable device according to claim 1, wherein the step of authenticating the home gateway, the wearable device, and the home device to obtain an authentication result, and determining that the user is an authenticated user or a non-authenticated user based on the authentication result comprises:

controlling the wearable device to generate a first authentication character with X bitsAnd acquiring a first device identifier +.>With the first authentication key->And a second device identification of said home gateway +.>With a second authentication key->And based on said first authentication character +.>Said first device identification- >Said first authentication key->Said second device identity +.>And said second authentication key->Calculate the first authentication information +.>And second authentication information->：

；

In the method, in the process of the invention,representing first intermediate information->Is->Byte->Representing first intermediate information->Before->A number of bytes of the data are used,representing SM4 decryption algorithm;

；

controlling the household equipment to generate a third authentication character with X bitsBased on the third authentication character +. >Calculate fifth authentication information->：

；

；/>；

In the method, in the process of the invention,representing third intermediate information->Is->Byte->Representing third intermediate information->Before->A number of bytes of the data are used,representing fourth intermediate information->Is->Byte->Representing fourth intermediate information->Before->A number of bytes;

3. The smart home control method based on the wearable device according to claim 2, wherein the third authentication information is based onSaid fourth authentication information->Said sixth authentication information->The seventh authentication informationThe step of determining an identity authentication result, and determining whether the user is an authenticated user or a non-authenticated user based on the identity authentication result comprises:

4. The smart home control method based on a wearable device according to claim 1, wherein the step of determining a user behavior state according to the operation data, determining a behavior recognition result based on the user behavior state, and determining that the user is a normal user or an abnormal user based on the behavior recognition result comprises:

acquiring energy consumption data of the household equipment in a first preset time periodCarrying out gray scale normalization processing on the energy consumption data to obtain an energy consumption gray value +.>：

；

In the method, in the process of the invention,、/>respectively the home furnishingHistorical maximum energy consumption data and historical minimum energy consumption data of the device, +.>The gray value is not normalized;

；

In the method, in the process of the invention,is a time factor->Is->Personal home appliance in->Energy consumption behavior at time, < >>Is->Individual houseThe living equipment is->Energy consumption data at a moment;

5. The smart home control method based on a wearable device according to claim 4, wherein the step of determining a behavior change trend of the home device based on the energy consumption behavior amount, determining a behavior recognition result based on the behavior change trend, and determining the user as a normal user or an abnormal user based on the behavior recognition result comprises:

determining a change trend of the energy consumption behavior in a second preset time period, and judging whether the change trend is unchanged or whether the change trend is stable;

6. An intelligent home control system based on a wearable device, the system comprising:

the data interference module is used for constructing a blank user according to the user behavior state and adding blank behaviors and blank data into the operation data if the user is a non-authentication user and/or the user is an abnormal user;

The data interference module comprises:

；

a function determination submodule for determining the behavior of the household equipment based on the household equipmentDetermining a first probability of user behavior occurring at the corresponding moment +.>And a second probability of simultaneous occurrence of the two user actions +.>According to the first probability->The second probabilityDetermining a mapping function between the behavior and the occurrence time of a blank user +.>：

；

a behavior adding sub-module for adding a behavior based on the mapping function Determining a blank behavior of said blank user +.>And add blank behavior +.>Blank data;

the behavior adding submodule comprises:

；

7. A computer comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the wearable device-based smart home control method of any of claims 1 to 5 when the computer program is executed.

8. A storage medium having stored thereon a computer program which, when executed by a processor, implements the wearable device-based smart home control method of any of claims 1 to 5.