CN119759656A - A communication data backup method and system based on Internet of Things security service - Google Patents
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Abstract
The invention discloses a communication data backup method and system based on internet of things security service, which relate to the technical field of communication data backup, wherein backup periods are respectively set for various communication data according to importance evaluation of the communication data, backup requests of the various communication data are triggered according to the backup periods of the various communication data, the communication data triggering the backup requests are subjected to primary screening, the communication data after the primary screening is subjected to blocking processing, further, sequential backup is performed according to backup demand information of each data block, after the backup of the last data block is triggered, integrity check and risk prediction are performed on the backup data, full backup is performed on the communication data according to an integrity check result, the risk of attack and the possibility of loss of the backup data are evaluated according to a risk prediction result, and then a backup strategy is adjusted. The method realizes efficient and accurate backup operation, and enhances data security through integrity check and risk prediction.
Description
Technical Field
The invention relates to the technical field of communication data backup, in particular to a communication data backup method and system based on internet of things security service.
Background
With the rapid development of internet of things (IoT, I nternet of Th i ngs) technology, various intelligent devices, sensors and communication devices have been widely used in smart home, industrial automation, smart cities, medical health and other fields, and these devices generate massive communication data in daily operations, including sensing data, control signals, environmental data and the like, and these data not only have a great volume, but also relate to characteristics of real-time, dynamic and diversity, and some data need to be backed up and recovered quickly, especially in industrial control and medical applications, where data loss or delay may have serious consequences.
However, the conventional data backup method generally does not fully consider the importance difference of communication data, and easily adopts a uniform backup period and strategy, so that the high-priority key data is not backed up sufficiently, the low-priority data is frequently backed up, thereby wasting storage resources and bandwidth, in the conventional backup system, the situation of repeated backup possibly occurs, especially in the application scene of the Internet of things with huge data volume, the repeated backup of the same data wastes storage space, time consumption and network load in the backup process are increased, the conventional backup method lacks effective integrity check and risk prediction after the data backup, so that potential safety hazards or errors exist in the backup data, and meanwhile, once the backup strategy is fixed, the backup strategy is difficult to adjust according to the actual situation, and in the environment of the Internet of things, the change of the communication data is frequent, the threat situation is also continuously changed, and the function of dynamically adjusting the backup strategy is lacking.
Therefore, in view of the above problems, there is a need for a communication data backup method and system based on the security service of the internet of things.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a communication data backup method and a system based on the security service of the Internet of things, which solve the problems of low data backup efficiency and redundancy.
The communication data backup method based on the internet of things safety service comprises the following steps of collecting communication data based on internet of things equipment, carrying out importance assessment on the communication data, classifying the communication data according to the importance assessment of the communication data, setting backup periods for various communication data respectively, triggering backup requests of the various communication data according to the backup periods of the various communication data, carrying out primary screening on the communication data triggering the backup requests, identifying overlapping areas between the communication data triggering the backup requests and historical backup data, further screening the overlapping areas, carrying out blocking processing on the communication data after the primary screening, further carrying out sorting on the data blocks according to backup requirement information of each data block, carrying out sequential backup according to the sorting result, carrying out integrity check and risk prediction on the backup data after the backup of the last data block is triggered, verifying the backup integrity of the communication data according to the integrity check result, carrying out full backup on the communication data according to the integrity check result, further adjusting the risk of attack and the backup strategy according to the risk of the risk prediction result evaluation data.
Further, carrying out importance evaluation on the communication data, classifying the communication data according to the importance evaluation of the communication data, and respectively setting specific analysis of backup periods for various communication data, wherein the communication data comprises communication content, communication metadata and communication protocols; the method comprises the steps of obtaining importance evaluation parameters of communication data, wherein the importance evaluation parameters of the communication data comprise data sensitivity and data access frequency, obtaining a data sensitivity average value and a data access frequency average value of the communication data, further comparing the data sensitivity average value and the data access frequency average value of the communication data with the data sensitivity average value and the data access frequency average value respectively, dividing the communication data with the data sensitivity higher than the data sensitivity average value and the data access frequency higher than the data access frequency average value into communication first-stage data, representing the communication data of the type as high importance data, dividing the communication data with the data sensitivity higher than the data sensitivity average value and the data access frequency lower than or equal to the data access frequency average value into communication second-stage data, representing the communication data of the type as medium importance data, dividing the communication data with the data sensitivity lower than the data sensitivity average value and the data access frequency lower than the data access frequency average value into communication data, representing the communication data of the type as low importance data, setting the communication first-stage data, the communication second-stage data and third-stage communication data importance degree setting the communication data of the three-stage data importance degree respectively based on the communication first-stage data and the communication data importance of the communication first-stage data importance and the communication data importance degree, backup cycles of communication secondary data and communication tertiary data.
Further, the communication data triggering the backup request is primarily screened, and the overlapping area between the communication data triggering the backup request and the historical backup data is identified, so that the specific analysis of screening the overlapping area is that the communication data triggering the backup request is preprocessed, wherein the preprocessing comprises the processing of a missing value and an abnormal value and the repeated data processing; the method comprises the steps of calling historical backup communication data in a backup system, comparing the preprocessed communication data with the historical backup communication data in an identifier mode, identifying whether the preprocessed communication data have the same identifier data in the historical backup communication data, marking the same identifier data as a duplicate area, packaging and formatting the residual communication data after screening out the duplicate area to generate a backup request, determining a specific path of the duplicate area in the historical backup communication data according to a storage record of the historical backup communication data, and adding the backup path of the duplicate area in the historical backup communication data to the backup request.
The method comprises the steps of carrying out primary screening on communication data, carrying out block processing on the primary screened communication data, further sequencing the data blocks according to backup requirement information of the data blocks, and carrying out specific analysis of sequential backup according to sequencing results, wherein the primary screening communication data is blocked according to time stamps, backup requirement information of the data blocks is respectively obtained, the backup requirement information comprises data modification frequency and data capacity, format normalization processing is carried out on the data modification frequency and the data capacity of the data blocks, further priority scores of the data blocks are obtained according to the data modification frequency and the data capacity of the data blocks, sequencing the data blocks according to the priority scores of the data blocks, and further sequentially triggering backup according to the priority scores.
Further, verifying the backup integrity of the communication data according to the integrity verification result, and performing specific analysis on the communication data according to the integrity verification result, wherein the specific analysis comprises the steps of setting a first hash function, a second hash function and a third hash function, performing hash calculation on the communication data according to the first hash function, the second hash function and the third hash function respectively to obtain a first hash value, a second hash value and a third hash value of the communication data, splicing the first hash value, the second hash value and the third hash value of the communication data to obtain a unique hash identifier of the communication data, performing calculation on the communication data backed up by the first hash function, the second hash function and the third hash function respectively to obtain a first hash value, a second hash value and a third hash value of the backup data, performing hash calculation on the first hash value, the second hash value and the third hash value of the backup data according to obtain a unique hash identifier of the communication data, further performing communication hash identifier and the communication data to obtain a unique hash identifier of the communication data, triggering the communication data and the unique identifier if the communication data is different from the unique identifier, and the unique identifier is triggered, and prompting the safe operation staff of the Internet of things to check the backup abnormality by using the backup abnormality warning until the communication data is the same as the unique hash identifier of the backup data.
Further, according to risk prediction results, risk and loss possibility of the backup data under attack are evaluated, and further specific analysis of the backup strategy is adjusted, namely whether backup abnormal warning is triggered is identified, if the backup abnormal warning is triggered, the backup abnormal value is recorded as 1, if the backup abnormal warning is not triggered, the backup abnormal value is recorded as 0, risk evaluation parameters of the backup data are obtained, the risk evaluation parameters of the backup data specifically comprise vulnerability threat score and recovery capability score, the risk prediction value of the backup data is obtained according to the backup abnormal value, the vulnerability score and the recovery capability score of the backup data, the risk prediction value of the backup data is compared with a risk threshold, when the risk prediction value of the backup data exceeds the risk threshold, the backup data is marked as high risk data, and an internet of things security operation and maintenance person is prompted to adjust the backup strategy, wherein specific adjustment comprises backup period adjustment and backup storage position adjustment.
A communication data backup system based on the internet of things security service is applied to the communication data backup method based on the internet of things security service, and comprises a data collection module, a data classification module, a backup initial screening module, a backup control module, a verification and detection module, a integrity check and backup prediction module and a full-risk adjustment and risk adjustment module, wherein the data collection module is used for collecting communication data based on internet of things equipment, the data classification module is used for carrying out importance assessment on the communication data, classifying the communication data according to the importance assessment of the communication data, setting backup periods for various communication data respectively, triggering the backup request of the various communication data according to the backup periods of the various communication data, carrying out initial screening on the communication data triggering the backup request, identifying the overlapping area between the communication data triggering the backup request and historical backup data, further screening the overlapping area, the backup control module is used for carrying out blocking processing on the communication data after the initial screening, further carrying out sorting on the data blocks according to the backup requirement information of the data blocks, carrying out sequential backup according to the sorting result, and carrying out the backup checking and detection module is used for carrying out integrity check and backup prediction on the backup data after the backup of the last data block is triggered, and carrying out the full-risk check and backup prediction on the communication data according to the backup request.
The invention has the following beneficial effects:
According to the communication data backup method and system based on the security service of the Internet of things, by evaluating and classifying the importance of the communication data, different backup periods can be set according to the importance of the data, frequent backup of data which is not important or is not frequently changed is avoided, so that the backup efficiency is improved, and redundancy and resource waste are reduced; the method has the characteristics of saving storage space and backup resources, further improving efficiency by identifying and screening out the overlapping area with the historical backup data, carrying out blocking treatment on communication data, dividing large data volume into a plurality of small blocks for backup, effectively reducing the pressure of each backup, sorting the data blocks according to backup demand information, preferentially backing up key data according to the importance of the data blocks, ensuring that the most important data can be backed up preferentially, carrying out final integrity check, ensuring that the backup data is not damaged or lost in the transmission and storage process, carrying out full backup when the data backup is found to be incomplete, ensuring that the data integrity is comprehensively ensured, carrying out risk prediction on the backup data, evaluating the possibility of the attack risk and loss of the backup data, carrying out early warning on potential safety problems, helping to formulate a countermeasure, being favorable for timely adjusting the backup strategy when the potential threat is found, enhancing the safety of the data, flexibly adjusting the backup strategy according to the risk prediction result, for example, enhancing the encryption and backup frequency of the key data, improving the general attack resistance of the data, carrying out the full backup when the data is found, carrying out large-scale, and carrying out various communication and setting the mass data in real-time, and being suitable for the characteristics of mass communication, important data is timely and efficiently protected, and long-term availability of backup and security services is guaranteed.
Drawings
Fig. 1 is a flowchart of a communication data backup method based on internet of things security service.
Fig. 2 is a block diagram of a communication data backup system based on internet of things security service according to the present invention.
Detailed Description
According to the communication data backup method and system based on the security service of the Internet of things, efficient and accurate backup operation is achieved, and data security is enhanced through integrity check and risk prediction.
The general idea of the embodiment of the application is that based on communication data generated by the Internet of things equipment, different backup periods are set by carrying out importance evaluation and classification management on the data, and high-efficiency backup is carried out by carrying out blocking processing and screening out repeated data, and finally, integrity check and risk prediction are carried out, so that the safety of the data and the reliability of backup are ensured.
Referring to fig. 1, an embodiment of the invention provides a technical scheme of a communication data backup method based on internet of things security service, which comprises the following steps of collecting communication data based on internet of things equipment, carrying out importance assessment on the communication data, classifying the communication data according to the importance assessment of the communication data, setting backup periods for various communication data respectively, triggering backup requests of the various communication data according to the backup periods of the various communication data, carrying out primary screening on the communication data triggering the backup requests, identifying overlapping areas between the communication data triggering the backup requests and historical backup data, further screening the overlapping areas, carrying out blocking processing on the communication data after the primary screening, further carrying out sorting on the data blocks according to backup requirement information of each data block, carrying out sequential backup according to sorting results, carrying out integrity check and risk prediction on the backup data after the backup of the last data block is triggered, verifying the backup integrity of the communication data according to the integrity check results, carrying out full backup on the communication data according to the integrity check results, further adjusting backup strategies according to risk prediction results, and evaluating the possibility of attack and loss of the backup data.
The communication data is classified according to the importance evaluation of the communication data, the backup period is set for each type of communication data respectively, the communication data comprises communication content, communication metadata and a communication protocol, the importance evaluation parameters of the communication data are acquired, the importance evaluation parameters of the communication data comprise data sensitivity and data access frequency, the data sensitivity average value and the data access frequency average value of the communication data are acquired, the data sensitivity and the data access frequency of the communication data are respectively compared with the data sensitivity average value and the data access frequency average value, the data sensitivity is higher than the data sensitivity average value, the communication data with the data access frequency higher than the data access frequency average value is divided into communication primary data, the communication data is represented as high importance data, the communication data with the data sensitivity higher than the data sensitivity average value and the data access frequency lower than the data access frequency average value is represented as medium importance data, the communication data with the data sensitivity lower than the data sensitivity average value is represented as medium importance data, the communication data with the data sensitivity lower than the data access frequency average value is divided into communication secondary data, the communication data is represented as medium importance data, the communication data with the data sensitivity lower than the data access frequency average value is represented as medium importance data, and the communication data with the data access frequency lower than the data access frequency average value is represented as medium importance data, backup cycles of communication secondary data and communication tertiary data.
In this embodiment, the data sensitivity refers to the degree of sensitive information contained in the data, the high-sensitivity data contains important contents such as personal information, business confidentiality and the like, the loss or leakage of the important contents can cause serious consequences, the specific data sensitivity is represented by a numerical value or a grade (such as 1-5 grade), the larger the numerical value is, the higher the sensitivity is, the data access frequency refers to the frequency of accessing or using the data, and the data with high access frequency is usually retrieved, modified or shared, and is generally measured by the access times, the number of accesses in a time period (such as each hour and each day) and can also be represented by the access frequency grade.
The specific data sensitivity acquisition mode is that the communication content is analyzed through an automatic data classification tool, sensitive information (such as personal data, sensitive protocols and the like) is identified, sensitivity scores are distributed to the data according to the sensitivity level of the sensitive information, the data which is difficult to identify through automatic tools in specific business scenes is assigned by manually checking the data content, and the data sensitivity can be automatically distributed or evaluated according to industry standards and requirements.
The specific data access frequency acquisition mode is that the access frequency of each communication data is counted by analyzing access logs (such as communication logs, user request logs and the like), the access condition of the communication data can be tracked by using a real-time monitoring tool, and the access frequency is dynamically adjusted according to the actual condition.
Examples of specific settings for the backup period are backup for communication primary data (high importance data) which should be short, possibly daily or every few hours, because these data are very important and frequently accessed, backup for communication secondary data (medium importance data) which may be suitably prolonged, such as weekly or monthly, backup for communication tertiary data (low importance data) which may be longer, e.g. once a quarter or half year.
By classifying the importance of the communication data, a differentiated backup strategy can be realized, communication data with different importance can have different backup periods, for example, the backup period of the important data can be shorter, timely recovery is ensured, unimportant data can have a longer backup period, the waste of storage resources is reduced, the safety of key data can be ensured, the excessive consumption of resources can be reduced, the efficiency of a backup system is improved, and management personnel can reasonably configure storage, bandwidth and computing resources.
The method comprises the steps of pre-screening communication data triggering a backup request, identifying an overlapping area between the communication data triggering the backup request and historical backup data, and further screening out the overlapping area, wherein the pre-processing of the communication data triggering the backup request comprises the steps of processing a missing value and an abnormal value and repeating the data processing; the method comprises the steps of calling historical backup communication data in a backup system, comparing the preprocessed communication data with the historical backup communication data in an identifier mode, identifying whether the preprocessed communication data have the same identifier data in the historical backup communication data, marking the same identifier data as a duplicate area, packaging and formatting the residual communication data after screening out the duplicate area to generate a backup request, determining a specific path of the duplicate area in the historical backup communication data according to a storage record of the historical backup communication data, and adding the backup path of the duplicate area in the historical backup communication data to the backup request.
In this embodiment, the specific logic steps of the identifier comparison include extracting a key identifier (such as a data packet ID, a timestamp, a data hash value, etc.) from the communication data triggering the backup request and the historical backup data, performing necessary preprocessing on the communication data triggering the backup request, including removing a missing value and an abnormal value, processing repeated data, etc., to ensure the quality of the data to be compared, performing a one-to-one comparison on the identifier of the preprocessed communication data and the identifier in the historical backup data, typically using a hash matching, string comparison, etc., and identifying whether the same identifier exists, and if the same identifier exists, marking the same identifier as the overlapping area.
The data package is specifically organized according to a predetermined format, such as being divided into blocks with proper size, or being encoded according to a specific data structure (such as JSON, XML or binary format), and the formatted data package result is packaged into a backup request, wherein the backup request comprises information such as identifier, size, type and the like of newly added data, a corresponding backup path, metadata such as a backup time stamp, version number and the like, and backup path information of a superposition area
The method and the device have the advantages that the overlapping area between communication data triggering the backup request and historical backup data is identified, the repeated backup of the same data is avoided, the waste of storage space and time and computing resources required by backup are reduced, particularly when the data volume is large, the efficiency of the backup process can be remarkably improved, the backed-up data is removed from the current backup by screening the overlapping area, the backup of only newly added and unrepeated data is ensured, the storage space is saved to the greatest extent, the backup path of the overlapping area is accurately identified and recorded, the integrity and consistency of the new backup request and the historical backup data are ensured to be maintained, the problem of inconsistent data caused by repeated backup is avoided, the requirement of human intervention is reduced through an automatic overlapping area identification and path adding mechanism, the backup task can be managed more intelligently, and the automation level of a backup system is improved.
The method comprises the steps of carrying out block processing on communication data subjected to primary screening, and then sequencing the data blocks according to backup requirement information of the data blocks, wherein specific analysis of sequential backup is carried out according to sequencing results, namely carrying out block partitioning on the communication data subjected to primary screening according to a timestamp, respectively obtaining backup requirement information of the data blocks, wherein the backup requirement information comprises data modification frequency and data capacity, carrying out format normalization processing on the data modification frequency and the data capacity of the data blocks, further obtaining priority scores of the data blocks according to the data modification frequency and the data capacity of the data blocks, and further obtaining a specific priority score obtaining expression, wherein ps represents the priority score, dmr represents the data modification frequency, dcs represents the data capacity, alpha 1 represents a weight value of the data modification frequency, alpha 2 represents a weight value of the data capacity, sequencing the data blocks according to the priority score of the data blocks, and further triggering backup in sequence according to the priority score of the data blocks.
In the embodiment, the data modification frequency and the data capacity are set in a weight value setting mode that if the system considers that the data with high modification frequency is critical to service continuity, higher weight can be given, the backup of the data block with larger capacity can be ensured not to be ignored by setting a certain weight, the influence of the data modification frequency and the data capacity can be flexibly balanced according to the actual application scene, or importance degree analysis setting is carried out on the data modification frequency and the data capacity according to professionals in the related field, and finally the sum of the weight values of the data modification frequency and the data capacity is ensured to be 1.
The time stamp represents the collection time of communication data, is used for carrying out block processing on the data according to time, ensures that the data can be processed and backed up according to the correct time sequence, and specifically, the time stamp is generated through extracting time information from a data source or through the inside of a system, the data blocks represent single data segments of the communication data subjected to preliminary screening after being subjected to time stamp segmentation, each data block comprises a plurality of data records, and each data block is generated as required through carrying out segment processing on the time stamp of the original communication data.
The data modification frequency is obtained by analyzing modification time intervals in the data block or by the system log, and the data capacity size is obtained according to the size of the data block (e.g., number of bytes, number of records, etc.).
The method has the advantages that the method is beneficial to preferentially backing up the data blocks with higher modification frequency and larger capacity according to the priority of the data blocks, ensures that important data cannot be lost or damaged due to backup delay, improves the overall performance of the system, dynamically adjusts the backup strategy by acquiring the modification frequency and the capacity of the data in real time, can adapt to different data change conditions, avoids excessive backup or insufficient backup, reasonably arranges the backup sequence according to backup demand information, and can avoid resource competition and performance bottleneck caused by simultaneous backup of a large amount of data of the system.
The backup integrity of the communication data is verified according to the integrity check result, and the communication data is fully backed up according to the integrity check result is specifically analyzed by setting a first hash function, a second hash function and a third hash function; the communication data is respectively subjected to hash computation according to the first hash function, the second hash function and the third hash function to obtain a first hash value, a second hash value and a third hash value of the communication data, the first hash value, the second hash value and the third hash value of the communication data are spliced to obtain a unique hash identifier of the communication data, the communication data is respectively subjected to calculation by utilizing the first hash function, the second hash function and the third hash function to obtain a first hash value, a second hash value and a third hash value of the backup data, the first hash value, the second hash value and the third hash value of the backup data are spliced to obtain a unique hash identifier of the backup data, the unique hash identifier of the communication data is compared with the unique hash identifier of the backup data to identify whether the communication data is the same as the unique hash identifier of the backup data, if the communication data is the same as the unique hash identifier of the backup data, the communication data is full, if the communication hash data is not the communication hash identifier of the unique hash identifier of the backup data is different from the second hash value, the communication data is triggered by the second hash value, the communication data is not triggered by the unique hash identifier of the communication data, and the unique hash value of the communication data is triggered by the second hash value, and the communication data is triggered by the unique hash identifier of the communication data is triggered by the unique hash value, and the unique communication data is triggered by the unique hash identifier of the communication data is triggered by the communication data, if the communication data is different, until the communication data is identical to the unique hash identifier of the backup data.
In this embodiment, the first hash function, the second hash function and the third hash function are used to calculate the expression, wherein the first hash value of the communication data D is H 1(D)＝hash1 (D), the second hash value of the communication data D is H 2(D)＝hash2 (D), the third hash value of the communication data D is H 3(D)＝hash3(D),hash(1,2,3) () representing a specific hash function, and in order to ensure that the different hash functions are not easy to collide, the first hash function, the second hash function and the third hash function are selected to satisfy the following conditions that the first hash function is selected to be MD5 or SHA-256 for quickly generating the hash value of the data, the second hash function is selected to be SHA-1 or SHA-512 for increasing the diversity, and the third hash function is selected to be HMAC (key-based hash) for providing additional security.
An example of a specific acquisition expression of the unique hash identifier is uhid =h 1(D)H2(D)H3 (D), where uhid is the unique hash identifier and l represents the concatenation operation of hash values.
The system automatically triggers a secondary backup request and checks once the hash identifiers are not matched, and timely discovers and solves the problem of backup abnormality, and through accurate hash identifier check, backup failure caused by data tampering or transmission errors can be effectively avoided, the safety risk of Internet of things equipment and communication data is reduced, the backup abnormality warning function is beneficial to safety operation staff of the Internet of things to discover potential problems in time and take measures, and the requirement of human intervention is reduced.
The risk assessment parameters of the backup data are obtained, the risk assessment parameters of the backup data specifically comprise vulnerability threat scores and recovery capacity scores, the risk prediction values of the backup data are obtained according to the backup abnormal values of the backup data, the vulnerability threat scores and the recovery capacity scores, and the specific risk prediction value obtaining expression examples are as follows: Wherein rpv represents a risk prediction value, bav represents a backup abnormal value, vts represents a vulnerability threat score, rcs represents a recovery capacity score, the risk prediction value of backup data is compared with a risk threshold, when the risk prediction value of the backup data exceeds the risk threshold, the backup data is marked as high risk data, and an Internet of things security operation and maintenance personnel is prompted to adjust a backup strategy, wherein the specific adjustment comprises backup period adjustment and backup storage position adjustment.
In this embodiment, the vulnerability threat score represents the severity of the security vulnerability threat currently faced by the backup data or the backup system, and specific considerations include the type of vulnerability present (such as a system vulnerability, a software vulnerability, etc.), the severity and potential impact of the vulnerability (such as whether it can be exploited by an attacker, whether it can lead to data leakage or tampering), whether the vulnerability has been repaired or alleviated (such as whether a patch, reinforcement, etc.), and the vulnerability threat score detects the known vulnerability present in the backup system, specifically by an automated security scanning tool (such as a vulnerability scanner), and is obtained based on the hazard level of the vulnerability.
The recovery capability score represents the recovery capability of the backup data after encountering an attack or a fault, and specific considerations include the speed and the integrity of the data recovery, the availability in the recovery process (such as whether the backup is easy to access, whether the recovery process needs manual intervention, etc.), the redundancy of the backup (such as whether the backup has a plurality of places or a plurality of backup versions), the recovery capability score is evaluated by testing the recovery process of the backup data, or is obtained through calculation according to the backup strategy (such as backup frequency, storage mode, etc.).
The specific acquisition mode of the risk threshold is that a relatively conservative threshold is set by analyzing the security event of the historical backup data, so that measures can be taken in time when the potential risk is found, and the threshold can be dynamically adjusted according to the overall security state of the backup system, the vulnerability threat score and the change condition of the recovery capacity score.
The method comprises the steps of monitoring and evaluating the safety of backup data in real time based on a risk evaluation mode, ensuring that potential risks in the backup process can be found timely, being beneficial to taking measures in advance to avoid data loss or being attacked, identifying and preventing the expansion of the data risks in advance by triggering a backup abnormality warning mechanism when the occurrence of abnormality is found, prompting operation and maintenance personnel to adjust the backup strategy in time if a risk prediction value exceeds a set threshold value, adjusting the backup strategy according to comparison results of the risk prediction value and the risk threshold value, for example, adjusting backup period and backup storage position according to different risk levels, thereby improving the safety of data backup, focusing on abnormality of the backup data, and carrying out multidimensional risk analysis by combining vulnerability threat score and recovery capacity score, so that the backup risk evaluation is more comprehensive and accurate.
A communication data backup system based on the internet of things security service is applied to the communication data backup method based on the internet of things security service, and comprises a data collection module, a data classification module, a backup initial screening module, a backup control module, a verification and detection module, a integrity check and backup prediction module and a full-risk adjustment and risk adjustment module, wherein the data collection module is used for collecting communication data based on internet of things equipment, the data classification module is used for carrying out importance assessment on the communication data, classifying the communication data according to the importance assessment of the communication data, setting backup periods for various communication data respectively, triggering the backup request of the various communication data according to the backup periods of the various communication data, carrying out initial screening on the communication data triggering the backup request, identifying the overlapping area between the communication data triggering the backup request and historical backup data, further screening the overlapping area, the backup control module is used for carrying out blocking processing on the communication data after the initial screening, further carrying out sorting on the data blocks according to the backup requirement information of the data blocks, carrying out sequential backup according to the sorting result, and carrying out the backup checking and detection module is used for carrying out integrity check and backup prediction on the backup data after the backup of the last data block is triggered, and carrying out the full-risk check and backup prediction on the communication data according to the backup request.
In summary, the present application has at least the following effects:
The method comprises the steps of carrying out importance evaluation and classification on communication data, setting different backup periods for various data, distributing backup resources more reasonably, avoiding the problem of resource waste or insufficient backup of key data caused by the same kernel of all data, identifying and screening out overlapping areas in a preliminary screening step, avoiding repeated backup, further improving backup efficiency, optimizing backup sequence according to backup requirement information of data blocks by a blocking processing and sequencing backup strategy, ensuring high priority or priority processing of important data, ensuring accuracy of the backup data, avoiding backup failure caused by data damage or transmission errors, evaluating risk of attack and possibility of loss of the backup data by risk prediction, adjusting the backup strategy in time, such as increasing backup frequency, adopting safer storage mode and the like, coping with potential safety threat, and taking the full backup strategy as a countermeasure of a integrity check result, so that when the data is found out to be damaged or lost, the full data can be restored rapidly, and the risk of data loss is reduced.
It will be apparent to those skilled in the art that embodiments of the present invention may be provided as methods, systems. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and block diagrams of methods, systems according to embodiments of the invention. It will be understood that each flowchart and block diagram combinations of the flowchart and block diagrams can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
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