CN115310107A - Internet of things data secure storage method and system based on cloud computing - Google Patents
Internet of things data secure storage method and system based on cloud computing Download PDFInfo
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Abstract
The invention relates to the technical field of data acquisition of the Internet of things, and particularly discloses a cloud computing-based safe storage method and system for data of the Internet of things, wherein the method comprises the steps of obtaining equipment data; identifying the equipment data according to a preset reference database, and determining the data state of the equipment data; when the data state is an abnormal state, locking the equipment data, updating a locking record, and storing virtual data determined by the equipment data; and carrying out anomaly analysis on the equipment data based on the locking record, and replacing the virtual data according to an anomaly analysis result. The method and the device perform rapid identification with lower precision on the acquired data, generate the virtual data containing the mapping label when the data is possibly abnormal, store the virtual data according to the original plan, and perform further identification on the data which is possibly abnormal, and only need simple replacement, thereby avoiding the secondary sorting process of a storage party and greatly optimizing a multi-terminal data storage framework.
Description
Technical Field
The invention relates to the technical field of data acquisition of the Internet of things, in particular to a cloud computing-based safe storage method and system for data of the Internet of things.
Background
In current intelligent workshop, have a lot of production facility, data in these equipment are very important, and managers can gather these data, and its purpose in case the product problem appears, can trace to the source according to the data of gathering.
The data acquisition process cannot be separated from the data acquisition end, the working process of the existing data acquisition end is mostly independent, and the data acquisition end can pack the acquired data and then send the data to the master control end; the general control end identifies the collected data, determines the storage mode, and for identification accuracy, the identification process cannot be separated from the manual identification process, and the manual identification process can influence the data storage sequence, so that the storage party still needs to sort the stored data again, and the problem tracing process is convenient. When the data volume is large, the sequencing process is very complicated, and the utilization rate of computing resources is influenced.
Disclosure of Invention
The invention aims to provide a cloud computing-based internet of things data security storage method and system, and aims to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme:
a cloud computing-based Internet of things data secure storage method comprises the following steps:
receiving a filing request containing equipment information input by a user, and determining a data acquisition end according to the equipment information; each device at least corresponds to two data acquisition ends; the device information contains a device number;
sequentially reading the equipment data which are acquired by the data acquisition end and take the equipment number as an index according to a preset reading sequence; the device data comprises input data and corresponding output data;
identifying the equipment data according to a preset reference database, and determining the data state of the equipment data; the data state comprises a normal state and an abnormal state;
when the data state is a normal state, storing the equipment data according to the equipment number;
when the data state is an abnormal state, locking the equipment data, updating a locking record, and storing virtual data determined by the equipment data;
and carrying out anomaly analysis on the equipment data based on the locking record, and replacing the virtual data according to an anomaly analysis result.
As a further scheme of the invention: the step of receiving a filing request containing equipment information input by a user and determining a data acquisition end according to the equipment information comprises the following steps:
receiving a filing request input by a user, acquiring the position information of equipment, and calculating the distance between the equipment according to the position information;
sequentially inquiring adjacent equipment by taking the equipment as a center and taking a preset distance threshold as a radius;
installing a data acquisition end in each device, acquiring the number of adjacent devices, determining the thread of the data acquisition end according to the number and establishing a connection channel with each adjacent device; wherein, each device at least establishes a connection channel with two data acquisition terminals.
As a further scheme of the invention: when one data acquisition end is abnormal, the data acquisition end can transmit abnormal information to other data acquisition ends which are not abnormal, the other data acquisition ends which are not abnormal continue to work normally, the data acquisition end which sends the abnormal information is positioned according to the abnormal information, and the positioning information and the abnormal information are fed back to the system.
As a further scheme of the invention: the step of identifying the equipment data according to a preset reference database and determining the data state of the equipment data comprises the following steps:
positioning a target database in a preset reference database according to the equipment number;
reading input data in equipment data, traversing the target database according to the input data, and inquiring reference output data;
reading output data in the equipment data, comparing the output data with the reference output data, and determining the data state of the equipment data according to a comparison result;
when the equipment data is the data of each module, positioning a sub-database corresponding to each module in a target database, and determining the data state of each module in the sub-database based on the input-output relationship; and counting the data state of each module to obtain the data state of the equipment data.
As a further scheme of the invention: when the data state is a normal state, the step of storing the device data according to the device number comprises the following steps:
when the data state is a normal state, inquiring a preset data table with the equipment number as an index according to the equipment number; the data in the data table contains characteristic values;
inputting the equipment data into a trained numerical conversion model to obtain a characteristic value of the equipment data;
extracting the characteristic values in the data table to obtain a characteristic value array;
sequentially calculating the offset rate of the characteristic value of the equipment data and each characteristic value in the characteristic value array;
when any offset rate is zero, deleting the acquired equipment data;
when any deviation rate is smaller than a preset deviation threshold value, marking the corresponding data in the equipment data and the data table;
and when all the deviation rates reach a preset deviation threshold value, inputting the equipment data and the characteristic values thereof into a data table.
As a further scheme of the invention: when the data state is an abnormal state, locking the device data and updating a locking record, wherein the step of storing the virtual data determined by the device data comprises:
when the data state is an abnormal state, inquiring a preset data table with the equipment number as an index according to the equipment number;
locking the equipment data, generating virtual data according to the locked equipment data, and storing the virtual data into a data table; the virtual data and the equipment data both contain the same mapping label;
and when the device data is locked, acquiring locking time, and inserting the locked device data into a locking record by taking the locking time as an index.
As a further scheme of the invention: the locking record is updated in real time, and the step of updating in real time comprises the following steps:
acquiring the current moment in real time, and calculating the storage time of each device data in the locking record according to the current moment;
inquiring a preset time threshold according to the equipment number corresponding to the equipment data, and when the storage time reaches the preset time threshold, cutting the corresponding equipment data in the locking record;
and sending the cut equipment data to the cloud.
As a further scheme of the invention: the step of performing anomaly analysis on the equipment data based on the locking record and replacing the virtual data according to an anomaly analysis result comprises the following steps:
sequentially reading the equipment data in the locking record, inputting the equipment data into the trained recognition model, and performing anomaly analysis on the equipment data;
when the anomaly analysis process fails, sending the equipment data to the manual detection end, receiving evaluation information fed back by the manual detection end, and taking the evaluation information as an anomaly analysis result;
when the anomaly analysis result indicates that no anomaly exists, positioning virtual data in a data table according to the mapping label;
replacing the virtual data according to the device data.
The technical scheme of the invention also provides an internet of things data security storage system based on cloud computing, which comprises:
the acquisition terminal determining module is used for receiving a filing request containing equipment information input by a user and determining a data acquisition terminal according to the equipment information; each device at least corresponds to two data acquisition ends; the device information contains a device number;
the sequence reading module is used for sequentially reading the equipment data which is acquired by the data acquisition end and takes the equipment number as an index according to a preset reading sequence; the device data comprises input data and corresponding output data;
the data state determining module is used for identifying the equipment data according to a preset reference database and determining the data state of the equipment data; the data state comprises a normal state and an abnormal state;
the first storage module is used for storing the equipment data according to the equipment number when the data state is a normal state;
the second storage module is used for locking the equipment data and updating a locking record when the data state is an abnormal state, and storing virtual data determined by the equipment data;
and the abnormity analysis unlocking module is used for carrying out abnormity analysis on the equipment data based on the locking record and replacing the virtual data according to an abnormity analysis result.
As a further scheme of the invention: the acquisition end determining module comprises:
the distance calculation unit is used for receiving a filing request input by a user, acquiring the position information of the equipment and calculating the distance between the equipment according to the position information;
the device query unit is used for sequentially taking the device as a center and taking a preset distance threshold value as a radius to query adjacent devices;
the channel establishing unit is used for installing a data acquisition end in each device, acquiring the number of adjacent devices, determining the thread of the data acquisition end according to the number and establishing a connecting channel with each adjacent device; wherein, each device at least establishes a connection channel with two data acquisition terminals.
Compared with the prior art, the invention has the beneficial effects that: the method and the device perform rapid identification with lower precision on the acquired data, generate the virtual data containing the mapping labels when the data is possible to be abnormal, store the virtual data according to the original plan, and perform further identification on the data which is possible to be abnormal, and then only need simple replacement, thereby avoiding the secondary sorting process of a storage party and greatly optimizing a multi-terminal data storage framework.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention.
Fig. 1 is a flow chart of a cloud computing-based internet of things data security storage method.
Fig. 2 is a first sub-flow block diagram of a cloud computing-based internet of things data security storage method.
Fig. 3 is a second sub-flow block diagram of the internet of things data security storage method based on cloud computing.
Fig. 4 is a third sub-flow block diagram of the internet of things data security storage method based on cloud computing.
Fig. 5 is a fourth sub-flow block diagram of the internet of things data security storage method based on cloud computing.
Fig. 6 is a fifth sub-flow block diagram of the internet of things data security storage method based on cloud computing.
Fig. 7 is a block diagram of a composition structure of a data security storage system of the internet of things based on cloud computing.
Detailed Description
In order to make the technical problems, technical solutions and advantageous effects to be solved by the present invention more clearly apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Example 1
Fig. 1 is a flow chart of a secure storage method of internet of things data based on cloud computing, and in an embodiment of the present invention, the secure storage method of internet of things data based on cloud computing includes:
step S100: receiving a recording request containing equipment information input by a user, and determining a data acquisition end according to the equipment information; each device at least corresponds to two data acquisition ends; the device information contains a device number;
in an intelligent production workshop, a plurality of production devices are arranged, data in the devices are important, most workshops collect the data, and the purpose is to trace the source of problems according to the collected data once the product problems occur; it is conceivable that the data acquisition process of the production equipment is required to be accurate and comprehensive; therefore, each device corresponds to at least two data acquisition ends, so that the condition of data unexpected loss can be greatly reduced;
step S200: sequentially reading the equipment data which are acquired by the data acquisition end and take the equipment number as an index according to a preset reading sequence; the device data comprises input data and corresponding output data;
after the data acquisition end is determined, sequentially reading the equipment data acquired by the data acquisition end, and storing;
step S300: identifying the equipment data according to a preset reference database, and determining the data state of the equipment data; the data state comprises a normal state and an abnormal state;
step S400: when the data state is a normal state, storing the equipment data according to the equipment number;
step S500: when the data state is an abnormal state, locking the equipment data, updating a locking record, and storing virtual data determined by the equipment data;
before storing the device data, the device data needs to be identified, if the device data is normal, the device data is directly stored, if the device data is abnormal, a same source virtual data is generated, so that the sequence of the storage process is not greatly changed, and the identification-storage process is carried out according to a preset sequence;
in the technical scheme of the invention, a data acquisition end acquires equipment data in real time, the acquired data is not directly uploaded to a system, but is firstly cached and packaged, and when the system reads the data acquisition end, the packaged data is uploaded uniformly; the reading process of the system is sequential, and the time allocated to each data acquisition end is not too long; therefore, in the process of storing the data of the equipment, the same storage rhythm is ensured by virtue of the virtual data, and the orderliness of the data can be greatly improved;
step S600: and carrying out anomaly analysis on the equipment data based on the locking record, and replacing the virtual data according to an anomaly analysis result.
When abnormal data is detected, whether the abnormal data really exists or not needs to be judged, and the process is likely to involve a manual detection process, so that the required time is long; locking the abnormal data and inputting a locking record, uniformly detecting the locking record by a detector, and replacing the corresponding virtual data if the locking record is normal data; the main purpose of this process is to greatly reduce the recognition accuracy required in step S300, and to reduce the influence of the abnormality recognition process on the data storage process.
Fig. 2 is a block diagram of a first sub-flow of a secure storage method of internet of things data based on cloud computing, where the step of receiving a filing request containing device information input by a user, and determining a data acquisition end according to the device information includes steps S101 to S103:
step S101: receiving a filing request input by a user, acquiring the position information of equipment, and calculating the distance between the equipment according to the position information;
step S102: sequentially taking the equipment as a center and a preset distance threshold as a radius, and inquiring adjacent equipment;
step S103: installing a data acquisition end in each device, acquiring the number of adjacent devices, determining the thread of the data acquisition end according to the number and establishing a connection channel with each adjacent device; wherein, each device at least establishes a connection channel with two data acquisition ends.
According to the content, similar production equipment shares the same data acquisition end according to the distance, the data acquisition end is integrated on the production equipment, and once the data acquisition end is installed, the production data of adjacent production equipment can be acquired; it can be expected that if a data acquisition terminal is installed on each production device, the production data of each device can be acquired by the data acquisition terminals of the adjacent devices, so that the anti-interference performance of the data acquisition process can be effectively improved.
Furthermore, all data acquisition ends corresponding to the same equipment can communicate with each other, when one data acquisition end is abnormal, the data acquisition end can transmit abnormal information to other data acquisition ends which are not abnormal, the other data acquisition ends which are not abnormal continue to work normally, the data acquisition end which sends the abnormal information is positioned according to the abnormal information, and the positioning information and the abnormal information are fed back to the system.
The data acquisition ends can communicate with each other, and when a certain data acquisition end goes wrong, the adjacent data acquisition ends position the data acquisition end which goes wrong and feed back the data acquisition end to the staff.
Fig. 3 is a second sub-flow block diagram of the internet of things data security storage method based on cloud computing, where the identifying of the device data according to the preset reference database and the determining of the data state of the device data include steps S301 to S303:
step S301: positioning a target database in a preset reference database according to the equipment number;
step S302: reading input data in equipment data, traversing the target database according to the input data, and inquiring reference output data;
step S303: reading output data in the equipment data, comparing the output data with the reference output data, and determining the data state of the equipment data according to a comparison result;
the above details describe the identification process of the device data, and as can be seen from the above, the accuracy requirement of this identification process is very low, and the purpose is to identify apparently normal data; obviously normal data can be preset into a data table, if the equipment data belongs to the data table, the equipment data is indicated to be normal data, and if the equipment data does not belong to the data table, the equipment data is considered to be abnormal data; due to the comprehensive problem of the data table, a lot of data which are judged to be abnormal data are actually normal data, so that further detection needs to be carried out in the subsequent process;
when the equipment data is the data of each module, positioning a sub-database corresponding to each module in a target database, and determining the data state of each module in the sub-database based on the input-output relationship; and counting the data state of each module to obtain the data state of the equipment data.
A device may contain many modules, and the data analysis process for the modules is essentially the same as the data analysis process for the device, i.e., the minimum unit is changed.
Fig. 4 is a third sub-flow block diagram of the internet of things data security storage method based on cloud computing, where when the data state is a normal state, the step of storing the device data according to the device number includes steps S401 to S407:
step S401: when the data state is a normal state, inquiring a preset data table with the equipment number as an index according to the equipment number; the data in the data table contains characteristic values;
step S402: inputting the equipment data into a trained numerical conversion model to obtain a characteristic value of the equipment data;
step S403: extracting the characteristic values in the data table to obtain a characteristic value array;
step S404: sequentially calculating the offset rate of the characteristic value of the equipment data and each characteristic value in the characteristic value array;
step S405: when any offset rate is zero, deleting the acquired equipment data;
step S406: when any deviation rate is smaller than a preset deviation threshold value, marking the equipment data and corresponding data in the data table;
step S407: and when all the deviation rates reach a preset deviation threshold value, inputting the equipment data and the characteristic values thereof into a data table.
The data storage process is limited in the steps from S401 to S407, firstly, a data table corresponding to the equipment data is positioned, and a corresponding data table is preset for each production equipment; then, converting the equipment data, converting the multi-format data into a numerical value, and judging the relationship between the equipment data to be stored and the existing equipment data according to the numerical value;
specifically, if any offset rate is zero, it indicates that other data acquisition terminals have acquired and stored the data of the device; if all the deviation rates reach the preset deviation threshold value, the data table does not have the same data, and the data need to be stored; if any deviation rate is smaller than the preset deviation threshold value, it is indicated that data similar to the data of the device to be stored exists in the data table, the reason for the similarity is that data acquired and stored by other data acquisition terminals already exist in the data table, but the acquired data is different from the newly acquired data, which is likely to cause a problem of one data acquisition terminal, and therefore, marking is needed to wait for further processing.
Fig. 5 is a fourth sub-flow block diagram of the internet of things data secure storage method based on cloud computing, where when the data state is an abnormal state, the device data is locked and a lock record is updated, and the step of storing the virtual data determined by the device data includes steps S501 to S503:
step S501: when the data state is an abnormal state, inquiring a preset data table with the equipment number as an index according to the equipment number;
step S502: locking the equipment data, generating virtual data according to the locked equipment data, and storing the virtual data into a data table; the virtual data and the equipment data both contain the same mapping label;
step S503: and when the device data is locked, acquiring locking time, and inserting the locked device data into a locking record by taking the locking time as an index.
When the data state is an abnormal state, generating virtual data according to a preset conversion relation, storing the virtual data into a data table, locking the abnormal data, and inserting a locking record according to locking time;
further, the locking record is updated in real time, and the step of updating in real time includes:
acquiring the current moment in real time, and calculating the storage time of each device data in the locking record according to the current moment;
inquiring a preset time threshold according to the equipment number corresponding to the equipment data, and cutting the corresponding equipment data in the locking record when the storage time reaches the preset time threshold;
and sending the cut device data to the cloud.
The locking record is added with an updating function, and when abnormal data in the locking record exist for too long time, the abnormal data are uploaded to the cloud; it is worth mentioning that different production devices have different corresponding standards, and some important production devices have longer time threshold and correspondingly, the storage time can be longer.
Fig. 6 is a fifth sub-flow block diagram of the internet of things data security storage method based on cloud computing, where the step of performing anomaly analysis on device data based on the locking record and replacing the virtual data according to an anomaly analysis result includes steps S601 to S604:
step S601: sequentially reading the equipment data in the locking record, inputting the equipment data into a trained recognition model, and performing anomaly analysis on the equipment data;
step S602: when the anomaly analysis process fails, sending the equipment data to the manual detection end, receiving evaluation information fed back by the manual detection end, and taking the evaluation information as an anomaly analysis result;
step S603: when the abnormal analysis result is that no abnormality exists, positioning virtual data in a data table according to the mapping label;
step S604: replacing the virtual data according to the device data.
Step S601 to step S604 define the further identification process of the abnormal data, and first, the equipment data is identified by using the existing identification model with higher precision, so that the workload of manual identification can be reduced; then, the device data which cannot be identified is handed to manual identification; and finally, replacing the virtual data in the data table according to the data with normal identification result, wherein the replacement process cannot leave the mapping tag, and the mapping tag has the function of simplifying the query positioning process.
Example 2
Fig. 7 is a block diagram of a structure of an internet of things data security storage system based on cloud computing, in an embodiment of the present invention, an internet of things data security storage system based on cloud computing includes:
the acquisition terminal determining module 11 is configured to receive a filing request containing device information input by a user, and determine a data acquisition terminal according to the device information; each device at least corresponds to two data acquisition ends; the device information contains a device number;
the sequence reading module 12 is configured to sequentially read, according to a preset reading sequence, device data that is acquired by the data acquisition end and indexed by a device number; the device data comprises input data and corresponding output data;
the data state determining module 13 is configured to identify the device data according to a preset reference database, and determine a data state of the device data; the data state comprises a normal state and an abnormal state;
the first storage module 14 is configured to store the device data according to the device number when the data state is a normal state;
a second storage module 15, configured to lock the device data and update a lock record when the data state is an abnormal state, and store virtual data determined by the device data;
and the abnormality analysis unlocking module 16 is used for performing abnormality analysis on the equipment data based on the locking record and replacing the virtual data according to an abnormality analysis result.
Further, the acquisition end determining module 11 includes:
the distance calculation unit is used for receiving a filing request input by a user, acquiring the position information of the equipment and calculating the distance between the equipment according to the position information;
the device query unit is used for sequentially taking the device as a center and taking a preset distance threshold value as a radius to query adjacent devices;
the channel establishing unit is used for installing data acquisition ends in each device, acquiring the number of adjacent devices, determining the threads of the data acquisition ends according to the number and establishing connection channels with the adjacent devices; wherein, each device at least establishes a connection channel with two data acquisition ends.
The above description is intended to be illustrative of the preferred embodiment of the present invention and should not be taken as limiting the invention, but rather, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.
Claims (10)
1. A cloud computing-based Internet of things data secure storage method is characterized by comprising the following steps:
receiving a recording request containing equipment information input by a user, and determining a data acquisition end according to the equipment information; each device at least corresponds to two data acquisition ends; the device information contains a device number;
sequentially reading the equipment data which are acquired by the data acquisition end and take the equipment number as an index according to a preset reading sequence; the device data comprises input data and corresponding output data;
identifying the equipment data according to a preset reference database, and determining the data state of the equipment data; the data state comprises a normal state and an abnormal state;
when the data state is a normal state, storing the equipment data according to the equipment number;
when the data state is an abnormal state, locking the equipment data, updating a locking record, and storing virtual data determined by the equipment data;
and carrying out anomaly analysis on the equipment data based on the locking record, and replacing the virtual data according to an anomaly analysis result.
2. The cloud computing-based internet of things data security storage method according to claim 1, wherein the step of receiving a filing request containing equipment information input by a user, and the step of determining a data acquisition end according to the equipment information comprises:
receiving a recording request input by a user, acquiring the position information of equipment, and calculating the distance between the equipment according to the position information;
sequentially inquiring adjacent equipment by taking the equipment as a center and taking a preset distance threshold as a radius;
installing a data acquisition end in each device, acquiring the number of adjacent devices, determining the thread of the data acquisition end according to the number and establishing a connection channel with each adjacent device; wherein, each device at least establishes a connection channel with two data acquisition terminals.
3. The Internet of things data security storage method based on cloud computing as claimed in claim 2, wherein all data acquisition ends corresponding to the same device can communicate with each other, when one data acquisition end is abnormal, the data acquisition end transmits abnormal information to other data acquisition ends which are not abnormal, the other data acquisition ends which are not abnormal continue to work normally, the data acquisition end which sends the abnormal information is positioned according to the abnormal information, and the positioning information and the abnormal information are fed back to the system.
4. The cloud-computing-based internet of things data security storage method according to claim 1, wherein the step of identifying the device data according to a preset reference database and determining the data state of the device data comprises:
positioning a target database in a preset reference database according to the equipment number;
reading input data in equipment data, traversing the target database according to the input data, and inquiring reference output data;
reading output data in the equipment data, comparing the output data with the reference output data, and determining the data state of the equipment data according to a comparison result;
when the equipment data is the data of each module, positioning a sub-database corresponding to each module in a target database, and determining the data state of each module in the sub-database based on the input-output relationship; and counting the data state of each module to obtain the data state of the equipment data.
5. The cloud-computing-based internet of things data security storage method according to claim 1, wherein when the data state is a normal state, the step of storing the device data according to the device number comprises:
when the data state is a normal state, inquiring a preset data table with the equipment number as an index according to the equipment number; the data in the data table contains characteristic values;
inputting the equipment data into a trained numerical conversion model to obtain a characteristic value of the equipment data;
extracting the characteristic values in the data table to obtain a characteristic value array;
sequentially calculating the offset rate of the characteristic value of the equipment data and each characteristic value in the characteristic value array;
when any offset rate is zero, deleting the acquired equipment data;
when any deviation rate is smaller than a preset deviation threshold value, marking the equipment data and corresponding data in the data table;
and when all the deviation rates reach a preset deviation threshold value, inputting the equipment data and the characteristic values thereof into a data table.
6. The cloud-computing-based secure storage method of data of the internet of things, as claimed in claim 1, wherein when the data state is an abnormal state, the device data is locked and a locking record is updated, and the step of storing the virtual data determined by the device data includes:
when the data state is an abnormal state, inquiring a preset data table with the equipment number as an index according to the equipment number;
locking the equipment data, generating virtual data according to the locked equipment data, and storing the virtual data into a data table; the virtual data and the equipment data both contain the same mapping label;
and when the device data is locked, acquiring locking time, and inserting the locked device data into a locking record by taking the locking time as an index.
7. The cloud-computing-based internet of things data secure storage method of claim 6, wherein the locking record is updated in real time, and the real-time updating step comprises:
acquiring the current moment in real time, and calculating the storage time of each device data in the locking record according to the current moment;
inquiring a preset time threshold according to the equipment number corresponding to the equipment data, and cutting the corresponding equipment data in the locking record when the storage time reaches the preset time threshold;
and sending the cut equipment data to the cloud.
8. The cloud-computing-based secure storage method of data of the internet of things according to claim 6, wherein the step of performing anomaly analysis on the device data based on the locking record and replacing the virtual data according to an anomaly analysis result comprises:
sequentially reading the equipment data in the locking record, inputting the equipment data into a trained recognition model, and performing anomaly analysis on the equipment data;
when the anomaly analysis process fails, sending the equipment data to the manual detection end, and receiving evaluation information fed back by the manual detection end as an anomaly analysis result;
when the anomaly analysis result indicates that no anomaly exists, positioning virtual data in a data table according to the mapping label;
replacing the virtual data according to the device data.
9. A cloud computing-based Internet of things data security storage system, characterized in that the system comprises:
the acquisition terminal determining module is used for receiving a recording request containing equipment information input by a user and determining a data acquisition terminal according to the equipment information; each device at least corresponds to two data acquisition ends; the device information contains a device number;
the sequence reading module is used for sequentially reading the equipment data which is obtained by the data acquisition end and takes the equipment number as an index according to a preset reading sequence; the device data comprises input data and corresponding output data;
the data state determining module is used for identifying the equipment data according to a preset reference database and determining the data state of the equipment data; the data state comprises a normal state and an abnormal state;
the first storage module is used for storing the equipment data according to the equipment number when the data state is a normal state;
the second storage module is used for locking the equipment data and updating a locking record when the data state is an abnormal state, and storing virtual data determined by the equipment data;
and the abnormity analysis unlocking module is used for carrying out abnormity analysis on the equipment data based on the locking record and replacing the virtual data according to an abnormity analysis result.
10. The cloud-computing-based internet of things data security storage system of claim 9, wherein the acquisition side determination module comprises:
the distance calculation unit is used for receiving a filing request input by a user, acquiring the position information of the equipment and calculating the distance between the equipment according to the position information;
the device query unit is used for sequentially taking the device as a center and taking a preset distance threshold value as a radius to query adjacent devices;
the channel establishing unit is used for installing data acquisition ends in each device, acquiring the number of adjacent devices, determining the threads of the data acquisition ends according to the number and establishing connection channels with the adjacent devices; wherein, each device at least establishes a connection channel with two data acquisition terminals.
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| CN117171158A (en) * | 2023-11-02 | 2023-12-05 | 太一云境技术有限公司 | Service processing system and method based on digital certificate |
| CN117171158B (en) * | 2023-11-02 | 2024-02-20 | 太一云境技术有限公司 | Service processing system and method based on digital certificate |
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