Information security protection system for smart home

Abstract

This invention discloses an information security protection system for smart homes, relating to the field of smart home information security technology. It segments several pieces of private data from a user's personal information using a slicing unit, dividing them into several private data segments. Each private data segment corresponds to a real-time mapping value analyzed based on the user's personal characteristics. The real-time mapping value is composed of several element values ​​arranged according to a certain pattern, thus obtaining a mapping relationship containing the user's private data segments and the real-time mapping value. An uploading unit uploads the user's mapping relationship to a segment mapping table on the manufacturer's server. This ensures that the manufacturer's server can only store corresponding segmented private data, with each piece of data existing on the server in segments, preventing the acquisition of personal privacy even if data is leaked.

Description

Technical Field

[0001] This invention belongs to the field of smart home information security technology, specifically a smart home information security protection system. Background Technology

[0002] Patent CN104426726A discloses a smart home system that protects user privacy and information security. This invention provides a smart home system. The system includes a smart home network, the internet, and a dynamic domain name server. The smart home network includes network devices connected to the internet; a home server connected to the network devices for information interaction, receiving information from smart home terminals, and sending control signals to control the smart home terminals; several smart home terminals connected to the home server; and a dynamic domain name server connected to the internet for receiving dynamic IP addresses sent by network devices via the internet, binding the dynamic IP addresses to a fixed domain name of the smart home network, and performing domain name resolution. The provided smart home system can realize functions such as video monitoring, leisure and entertainment, intelligent control of home appliances, and home environment monitoring, and can achieve customer customization, combination, and association; it has no external operation service platform, ensuring information security.

[0003] However, regarding users' personal privacy data, how to effectively protect the right of manufacturers to access user privacy data, while preventing other personnel from obtaining the corresponding user privacy data from the manufacturer's servers, is a problem. Based on this, a solution is provided. Summary of the Invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art.

[0005] Therefore, this invention proposes an information security protection system for smart homes, comprising:

[0006] The slicing unit is used to segment several pieces of privacy data in the user's personal information, dividing them into several privacy data segments. Each privacy data segment corresponds to a real-time mapping value that is analyzed in real time based on the user's personal characteristics. The real-time mapping value is composed of several element values ​​arranged in a regular order, thus obtaining a mapping relationship that includes the user's privacy data segments and the real-time mapping value.

[0007] The user's mapping relationship is uploaded to the fragment mapping table on the manufacturer's server using the upload unit. The fragment mapping table includes past mapping values ​​and past privacy data segments. Past mapping values ​​are a series of combined values, generally consisting of at least one element value. Past privacy data segments are several segments that correspond to privacy data, which are used by verified users to read their personal privacy data.

[0008] Furthermore, the slicing unit is also used to process the facial information of personal information based on the real-time mapping value, retaining only the key element values ​​of the corresponding real-time mapping value, while covering or masking the rest, and retaining it as the corresponding calling feature in the slicing unit on the user end. The calling feature will retain the number of characters of the preceding and following data.

[0009] Furthermore, the user's personal information, consisting of several pieces of privacy data, is acquired by the data acquisition unit.

[0010] Furthermore, the data acquisition unit will transmit the privacy data in the personal information to the slicing unit before uploading it, and the data acquisition unit will clean up the personal information after the transmission is completed.

[0011] Furthermore, the segmentation unit divides privacy data into several equally divided real-time privacy data segments in a sequential manner, with the number of segments preset by the administrator.

[0012] Furthermore, the specific method for assigning a mapping value to each real-time privacy data segment is as follows:

[0013] The facial information corresponding to the personal information is obtained, and then several key element values ​​are obtained from the facial information. Each key element value is used to reflect the value of a certain part of the face.

[0014] Then synchronize the already stored fragment mapping tables in the database;

[0015] By utilizing different key element values ​​extracted from facial information corresponding to personal information, real-time mapping values ​​are formed for corresponding real-time privacy data segments; the specific method is as follows:

[0016] First, a key element value that does not appear at the beginning of the mapped values ​​will be selected in descending order and used as the first value.

[0017] If a key element value cannot be selected, it will automatically be extended to two sequentially combined key element values. This value will be used as the first value and compared with all other mapped values ​​starting from the first character. If no matching value is found, the second key element value will still be selected in descending order.

[0018] For each piece of privacy data, obtain the leading value of that piece of privacy data.

[0019] Then, the same privacy data is divided into several real-time privacy data segments, and the corresponding number of multi-precedence values ​​are obtained;

[0020] Then, select the non-repeating subsequent data from the remaining key element values ​​in descending order;

[0021] The front-end data and the back-end data are merged to form real-time mapping values. Each real-time mapping value is combined with real-time privacy data segments arranged in descending order of its preceding and following data to form a new mapping relationship. The slicing unit is used to upload the new mapping relationship to the manufacturer's server through the uploading unit. The manufacturer's server is used to add the received mapping relationship to the fragment mapping table. The manufacturer's server only stores the fragment mapping table consisting of the real-time mapping values ​​and their corresponding privacy data segments.

[0022] Furthermore, the subsequent data is obtained in the following way:

[0023] First, select the next key element value from the remaining key element values ​​after removing the preceding data, in descending order, and use it as the subsequent data. If the number of key element values ​​is less than the number of privacy data segments, then a combination method is adopted, and a different key element value is selected to form a combination of two key element values. The first key element value in the subsequent data is selected in descending order. After selection, the second key element value is selected from the remaining key element values ​​in descending order. If two are still not enough, a third is selected, until the number of privacy data segments is met. The selected key element values ​​are then combined to form new subsequent data.

[0024] Furthermore, the slicing unit is also used to process the facial information of personal information based on the real-time mapping value, retaining only the key element values ​​of the corresponding real-time mapping value, while covering or masking the rest, and retaining it as the corresponding calling feature in the slicing unit on the user end. The calling feature will retain the number of characters of the preceding and following data.

[0025] Furthermore, when a user needs to access their private data, the call will be processed through a local call unit. After multiple verifications of the user's identity using facial recognition or other verification methods, the call characteristics stored locally are obtained, and the corresponding private data segment is matched with the manufacturer's server based on the call characteristics.

[0026] Furthermore, the specific method for accessing the privacy data segment is as follows:

[0027] To determine the number of characters in the preceding data of the called features, first obtain the number of preceding data items, and then list them in ascending order of character count;

[0028] Select the element with the smallest number of characters, retrieve all element values ​​from the called features, and then select the element values ​​with the corresponding number of characters in descending order of element values ​​to obtain the preceding data.

[0029] Then, in descending order, select the corresponding data following the element values ​​according to the number of characters. The first selected data following the element is combined with the first selected data following the element. Then, select the data following the element corresponding to the number of privacy data segments according to the number of times and combine them with the data following the element. This gives the real-time mapping value of each privacy data segment of the first privacy data. Obtain the privacy data segment with the corresponding real-time mapping value in the corresponding segment mapping table and combine them to restore a privacy data.

[0030] Then restore the remaining privacy data in sequence.

[0031] Compared with the prior art, the beneficial effects of the present invention are:

[0032] This application segments several private data points in the user's personal information using a slicing unit, dividing them into several private data segments. Each private data segment corresponds to a real-time mapping value that is analyzed in real time based on the user's personal characteristics. The real-time mapping value is composed of several element values ​​arranged in a regular pattern, thus obtaining a mapping relationship that includes the user's private data segments and the real-time mapping value.

[0033] By using an upload unit to upload user mapping relationships to the fragment mapping table on the manufacturer's server, the manufacturer's server can only store corresponding fragment-type privacy data. In this way, each piece of data exists on the server in segments, and even if it is leaked, personal privacy will not be obtained. This invention is simple, effective, and easy to use. Attached Figure Description

[0034] Figure 1 This is a system block diagram of Embodiment 1 of the present invention;

[0035] Figure 2 This is a system block diagram of Embodiment 2 of the present invention. Detailed Implementation

[0036] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0037] Please see Figure 1 This application provides an information security protection system for smart homes. As an embodiment of this application, its specific details are as follows:

[0038] It includes a data acquisition unit, used to acquire the user's personal information stored in the smart home. The personal information includes several pieces of privacy data. Each piece of privacy data can refer to any kind of identity information, face, or other privacy information, including video-authenticated face, etc. Generally, anything involving user privacy is included here.

[0039] Then, the data acquisition unit will transmit the private data in the personal information to the slicing unit before uploading it. After the data acquisition unit completes the transmission, it will completely delete the personal information. Afterwards, the slicing unit will process the data locally. The specific processing method is as follows:

[0040] Select any person's information, choose any piece of privacy data from the personal information, and divide it into several equal real-time privacy data segments in sequence. The number of segments is preset by the administrator.

[0041] Several sequentially split real-time privacy data segments are obtained, and each real-time privacy data segment is assigned a mapping value, specifically in the following manner:

[0042] After obtaining the facial information corresponding to the individual's information, the facial information is analyzed to obtain key facial feature values. These key feature values ​​include several administrator-defined feature values ​​such as the longest value of the left eye, the longest value of the right eye, the longest value of the nose, and the distance between the ears. These will form a feature table, and each of these features can be uniquely obtained from the image. Personal information is then collected for each individual using the following method:

[0043] When collecting the corresponding face information, obtain the length value represented by a single pixel, then obtain the number of pixels occupied by any element value in the element table, and then convert it into a value to obtain the corresponding element value.

[0044] Then synchronize the stored fragment mapping table in the database. The fragment mapping table includes past mapping values ​​and past privacy data segments. Past mapping values ​​are a series of combined values, generally composed of at least one element value. Past privacy data segments are several segments that correspond to privacy data that have been divided.

[0045] By utilizing different key element values ​​extracted from facial information corresponding to personal information, real-time mapping values ​​are formed for corresponding real-time privacy data segments; the specific method is as follows:

[0046] First, a key element value that does not appear at the beginning of the mapped values ​​will be selected in descending order and used as the first value.

[0047] If a key element value cannot be selected, it will automatically be extended to two key element values ​​in sequence. This first value will be compared with all other mapped values ​​starting from the first character. If no matching value is found, the second key element value will still be selected in descending order. For example, if there is a mapped value 5655789420, it cannot be 56 if it is a single key element value, and it cannot be 5655 if it is two key element values ​​in any sequence.

[0048] Here we need to obtain the number of private data entries. The number of private data entries is determined by the value preceding the corresponding number of private data entries.

[0049] Then, for the same privacy data, it is divided into several real-time privacy data segments. The corresponding number of leading values ​​are obtained. Then, the next key element value is selected from the remaining key element values ​​in descending order and used as the subsequent data. If the number of key element values ​​is less than the number of privacy data segments, a combination method is adopted, and a different key element value is selected to form a combination of two key element values. The first key element value in the subsequent data is selected in descending order. After selection, the second key element value is selected from the remaining key element values ​​in descending order. If two are still not enough, a third is selected, until the number of privacy data segments is met. The selected key element values ​​are combined to form new subsequent data.

[0050] The front-end data and the back-end data are merged to form a real-time mapping value. Each real-time mapping value is combined with the real-time privacy data segments arranged in order of descending size of the data before and after it to form a new mapping relationship. The slicing unit is used to upload the new mapping relationship to the manufacturer's server through the uploading unit. The manufacturer's server is used to add the received mapping relationship to the fragment mapping table. The manufacturer's server only stores the fragment mapping table consisting of the real-time mapping value and its corresponding privacy data segment.

[0051] The slicing unit is also used to process the facial information of personal information based on the real-time mapping value. Only the key element values ​​of the corresponding real-time mapping value are retained in the facial information, while the rest are covered or masked. This is retained as the corresponding calling feature in the slicing unit on the user end. The calling feature will retain the number of characters of the preceding and following data. For example, if there are five privacy data, there will be the number of characters of the preceding and following data corresponding to the five privacy data.

[0052] As a second embodiment of this application, this embodiment is implemented based on the first embodiment. The difference between this embodiment and the first embodiment is that when a user needs to access their own private data, the access is processed through a local access unit. The specific access processing method is as follows:

[0053] First, after verifying the user's identity through multiple methods such as face verification or other verification methods, the call characteristics stored on the local end are obtained. Based on the call characteristics, the corresponding privacy data segment is matched with the manufacturer's server. The call method is also relatively simple. It is to first obtain the number of characters in the preceding data of the call characteristics, and then list them in ascending order of the number of characters.

[0054] Select the element with the smallest number of characters, retrieve all element values ​​from the called features, and then select the element values ​​with the corresponding number of characters in descending order of element values ​​to obtain the preceding data.

[0055] Then, in descending order, select the corresponding data following the element values ​​according to the number of characters. The first selected data following the element is combined with the first selected data following the element. Then, select the data following the element corresponding to the number of privacy data segments according to the number of times and combine them with the data following the element. This gives the real-time mapping value of each privacy data segment of the first privacy data. Obtain the privacy data segment with the corresponding real-time mapping value in the corresponding segment mapping table and combine them to restore a privacy data.

[0056] Then restore the remaining privacy data in sequence.

[0057] The data in the above formula are all calculated by removing the dimensions and taking the numerical values. The formula is the closest to the real situation obtained by software simulation of a large amount of collected data. The preset parameters and preset thresholds in the formula are set by those skilled in the art according to the actual situation or obtained through simulation of a large amount of data.

[0058] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. An information security protection system for smart homes, characterized in that, include: The slicing unit is used to segment several pieces of privacy data in the acquired user personal information into several privacy data segments. Each privacy data segment corresponds to a real-time mapping value that is analyzed in real time based on the user's personal characteristics. The upload unit is used to upload the user's privacy data segments and real-time mapping values ​​to the fragment mapping table of the manufacturer's server. The fragment mapping table includes past mapping values ​​and past privacy data segments, which are used by users who have verified their identity to read their personal privacy data. The method by which the slicing unit assigns a real-time mapping value to each real-time privacy data segment is as follows: Obtain facial information corresponding to personal information, extract several key element values ​​from the facial information, and each key element value is used to represent the value of a certain part of the face; Synchronize the previously stored fragment mapping table in the database; By utilizing different key element values ​​extracted from facial information corresponding to personal information, real-time mapping values ​​are formed for corresponding real-time privacy data segments; the specific method is as follows: Select a key element value that does not appear at the beginning of the mapped values, in descending order, and use it as the first value; If a key element value cannot be selected, it will automatically be extended to two sequentially combined key element values ​​as the first value. It will be compared with all other mapped values ​​starting from the first character. If there is no matching value, the second key element value will still be selected in descending order. For each piece of privacy data, obtain the leading value of that piece of privacy data. For the same privacy data being divided into several real-time privacy data segments, obtain the corresponding number of leading values; Select the next data that is not repeated from the remaining key element values ​​in descending order; The front-end data and the back-end data are merged to form real-time mapping values. Each real-time mapping value is combined with real-time privacy data segments arranged in order of decreasing size of the data before and after it to form a new mapping relationship. The slicing unit is used to upload the new mapping relationship to the manufacturer's server through the uploading unit. The manufacturer's server is used to add the received mapping relationship to the fragment mapping table. The manufacturer's server only stores the fragment mapping table consisting of real-time mapping values ​​and their corresponding privacy data segments.

2. The information security protection system for smart homes according to claim 1, characterized in that, The real-time mapping value is composed of several element values ​​arranged in a regular pattern; the past mapping value is a series of combined values, and the past privacy data segment is a number of segments into which the corresponding privacy data has been divided.

3. The information security protection system for smart homes according to claim 1, characterized in that, The user's personal information, consisting of several pieces of privacy data, is acquired by the data acquisition unit.

4. The information security protection system for smart homes according to claim 3, characterized in that, The data acquisition unit transmits the privacy data in the personal information to the slicing unit before uploading it, and the data acquisition unit clears the personal information after the upload is completed.

5. The information security protection system for smart homes according to claim 1, characterized in that, The slicing unit segments the privacy data in the following way: it sequentially splits the data into several equally divided real-time privacy data segments, with the number of segments preset by the administrator.

6. The information security protection system for smart homes according to claim 1, characterized in that, The method for obtaining subsequent data is as follows: Select the next key element value from the remaining key element values ​​after removing the preceding data, in descending order, and use it as the subsequent data; If the number of key element values ​​is less than the number of privacy data segments, a combination method is adopted. A different key element value is selected to form a combination of two key element values. The first key element value in the subsequent data is selected in descending order. After selection, the second key element value is selected from the remaining key element values ​​in descending order. If two are still not enough, a third is selected, until the number of privacy data segments is met. The selected key element values ​​are then combined to form new subsequent data.

7. The information security protection system for smart homes according to claim 1, characterized in that, The slicing unit is also used to process the facial information of personal information according to the real-time mapping value, retain only the key element value of the facial information corresponding to the real-time mapping value, and cover or mask the rest, and retain it as the corresponding calling feature in the slicing unit on the user end. The calling feature will retain the number of characters of the preceding and following data.

8. The information security protection system for smart homes according to claim 1, characterized in that, When a user needs to access their private data, the call is processed through a local call unit. After multiple verifications of the user's identity, such as facial recognition or other verification methods, the call characteristics stored locally are obtained, and the corresponding private data segment is matched with the manufacturer's server based on the call characteristics.

9. The information security protection system for smart homes according to claim 8, characterized in that, The specific method for matching privacy data segments is as follows: To determine the number of characters in the preceding data of the called features, first obtain the number of preceding data items, and then list them in ascending order of character count; Select the element with the smallest number of characters, retrieve all element values ​​from the called features, and then select the element values ​​with the corresponding number of characters in descending order of element values ​​to obtain the preceding data. Then, in descending order, select the corresponding data following the element values ​​according to the number of characters. The first selected data following the element is combined with the first selected data following the element. Then, select the data following the element corresponding to the number of privacy data segments according to the number of times and combine them with the data following the element. This gives the real-time mapping value of each privacy data segment of the first privacy data. Obtain the privacy data segment with the corresponding real-time mapping value in the corresponding segment mapping table and combine them to restore a privacy data. Then restore the remaining privacy data in sequence.

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