CN116527540A - Equipment safety intelligent supervision system and method based on artificial intelligence - Google Patents

Equipment safety intelligent supervision system and method based on artificial intelligence Download PDF

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Publication number
CN116527540A
CN116527540A CN202310568947.1A CN202310568947A CN116527540A CN 116527540 A CN116527540 A CN 116527540A CN 202310568947 A CN202310568947 A CN 202310568947A CN 116527540 A CN116527540 A CN 116527540A
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data information
data
abnormal
transmission
office equipment
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单剑秋
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Heilongjiang Huarui Times Technology Development Co ltd
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Heilongjiang Huarui Times Technology Development Co ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
    • H04L43/0823—Errors, e.g. transmission errors
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/06—Management of faults, events, alarms or notifications
    • H04L41/0631—Management of faults, events, alarms or notifications using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/16—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
    • H04L43/0823—Errors, e.g. transmission errors
    • H04L43/0829—Packet loss
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/20—Network architectures or network communication protocols for network security for managing network security; network security policies in general
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L69/00—Network arrangements, protocols or services independent of the application payload and not provided for in the other groups of this subclass
    • H04L69/16—Implementation or adaptation of Internet protocol [IP], of transmission control protocol [TCP] or of user datagram protocol [UDP]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Computer Security & Cryptography (AREA)
  • Environmental & Geological Engineering (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Artificial Intelligence (AREA)
  • Databases & Information Systems (AREA)
  • Evolutionary Computation (AREA)
  • Medical Informatics (AREA)
  • Software Systems (AREA)
  • Computer Hardware Design (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Alarm Systems (AREA)

Abstract

The invention relates to the technical field of artificial intelligence, in particular to an equipment safety intelligent supervision system and method based on artificial intelligence, wherein the system comprises a historical data analysis module, an abnormal data evaluation module, a transmission data monitoring module and an early warning module, wherein the abnormal data evaluation module is used for analyzing the relation between preprocessed data in first office equipment and a computer transmission medium, setting a data abnormality judgment condition.

Description

Equipment safety intelligent supervision system and method based on artificial intelligence
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to an equipment safety intelligent supervision system and method based on artificial intelligence.
Background
Artificial intelligence is a theory, method, technology and application system which uses a digital computer or a machine controlled by the digital computer to simulate, extend and expand human intelligence, sense environment, acquire knowledge and acquire optimal conclusion by using the knowledge, along with development of information technology, intelligent office is also continuously improved, and intelligent office is a novel office mode which uses cloud computing technology to intelligently manage software and hardware equipment required by office business and realize unified deployment and delivery of enterprise application software.
At present, data transmission exists in enterprises in various large fields, and various departments can conveniently know data information of various departments through the data transmission, however, along with overlarge data transmission quantity, the safety problem of the data transmission and the safety problem of a data source are still problems to be improved at present.
Disclosure of Invention
The invention aims to provide an artificial intelligence-based equipment safety intelligent supervision system and method, which are used for solving the problems in the background technology, and the invention provides the following technical scheme:
an artificial intelligence based device security intelligent supervision method, the method comprising the steps of:
S1, acquiring a data information source corresponding to transmission data of first office equipment through historical data, preprocessing the acquired data information source, and further classifying the transmission data in the first office equipment according to a preprocessing result;
s2, analyzing the relation between the preprocessed transmission data information in the first office equipment and a computer transmission medium, and setting a data abnormality judgment condition by combining the analysis result;
s3, monitoring a data information set required to be transmitted by the current first office equipment in real time, and judging an early warning signal by combining the analysis results of the S1 and the S2;
s4, sending out an abnormal early warning signal according to the analysis result of S3, and adopting corresponding processing measures for the data required to be transmitted by the current first office equipment according to the type of the early warning signal.
Further, the method in S1 includes the following steps:
step 1001, the data information source corresponding to the transmission data of the first office equipment acquired in step S1 is denoted as a set a,
A＝{A 1 ，A 2 ，A 3 ，...，A n }，
wherein A is n The method comprises the steps of representing an nth data information source in first office equipment, wherein n represents the total number of the data information sources in the first office equipment;
step 1002, obtaining any one of the nth data information sources in the first office equipment to transmit the data information set, and recording the data information set as a set Wherein->Representing an mth transmission data characteristic field in an nth transmission data information set in an nth data information source in first office equipment, wherein the characteristic field is a database preset value;
step 1003, acquiring an abnormal transmission data information set in the history data, which is marked as a set C,
C＝{C 1 ，C 2 ，C 3 ，...，C i }，
wherein C is i An i-th abnormal characteristic field in the abnormal transmission data information set is represented, and i represents the total number of characteristic fields in the abnormal transmission data information set;
step 1004, analyzing the similarity degree between the transmission data information set corresponding to the nth data information source in the first office equipment and the abnormal transmission data information set in the historical data, and marking as
Wherein B is n(β) And n C represents an intersection element between any one of the nth data information sources in the first office equipment and the abnormally transmitted data information set in the history data, L (B) n(β) And C) represents the number of intersection elements between any one of the nth data information sources in the first office apparatus and the abnormally transmitted data information set in the history data,
B n(β) U.C represents the union element between any one of the nth data information sources in the first office equipment and the abnormal transmission data information set in the history data, L (B) n(β) U C) represents the number of union elements between any one of the nth data information sources in the first office equipment and the abnormal transmission data information set in the history data,
if it isIndicating that there is no abnormality in the transmission data information set corresponding to the nth data information source in the first office device,
if it isIndicating that the abnormal condition exists in the transmission data information set corresponding to the nth data information source in the first office equipment;
step 1005, repeating the steps 1002-1004 to obtain an abnormality determination result of each transmission data information set in different data information sources in the first office equipment, and classifying the data information sources corresponding to the transmission data information sets without abnormal data in the first office equipment as E 1 Class, classifying the data information sources corresponding to the transmission data information set with abnormal data in the first office equipment as E 2 Class.
Further, the method in S2 includes the following steps:
step 2001, obtaining the data information source classification result in step 1005, and optionally extracting E 1 A data information source in the class, denoted asWherein->Representing data information Source +.>A j-th transmission data information set;
step 2002, analyzing packet loss conditions corresponding to the data information sets after the preprocessed data information sets in the first office equipment are transcoded through an alpha-th computer transmission medium, calculating transcoding accuracy, and marking the transcoding accuracy as Y E1 ，
Wherein the method comprises the steps ofRepresenting the total number of data information transmitted after transcoding, < >>Representing data information Source +.>The total number of the data information is transmitted,
if it isThe method indicates that the data information set after the pretreatment in the first office equipment is transcoded by the alpha-th computer transmission medium has no packet loss condition, further judges whether the data information set transmission process has abnormality,
if it isIndicating that the preprocessed data information set in the first office device passes through the alpha-th computerThe data information set transcoded by the transmission medium has the packet loss condition and marks the corresponding computer transmission medium;
step 2003, obtaining the data information source classification result in step 1005, and optionally extracting E 2 A data information source in the class, denoted asWherein->Representing data information Source +.>A kth transmission data information set;
step 2004, source of anomalous data informationThe benefit set corresponding to the abnormal characteristic field in the kth transmission data information set is marked as a set +.>
Wherein the method comprises the steps ofInformation source representing abnormal data->The benefit set corresponding to the kp-th abnormal characteristic field in the kth transmission data information set;
step 2005, taking the benefit corresponding to the characteristic field in the data information set safely transmitted in the historical data as a reference set, and recording as a set L * ，
Wherein the method comprises the steps ofThe method comprises the steps of representing benefits corresponding to a v-th characteristic field in a safe transmission data information set in historical data, wherein v represents the total number of benefits corresponding to the characteristic field in the safe transmission data information set in the historical data, the benefits are database form preset values, and each safe transmission data information set corresponds to one benefit;
step 2006, source of anomalous data informationThe degree of the dispersion between the benefit set corresponding to the kp-th abnormal characteristic field in the kth transmission data information set and the reference set is recorded as mu kp ，
Step 2007, cycling step 2006 to obtain an abnormal data information sourceThe degree of dispersion between benefit sets corresponding to different abnormal characteristic fields in the kth transmission data information set and the reference set in turn,
if the degree of dispersion mu kp Within the preset interval, indicating the abnormal data information sourceThe same benefit value exists between the benefit set corresponding to the kp-th abnormal characteristic field in the kth transmission data information set and the reference set, and the abnormal data information source is primarily judged>Data message capable of being safely transmitted in kth transmission data information set kp abnormal characteristic fieldReplacing corresponding characteristic fields in the information set, and further analyzing the abnormal data information source based on the preliminary judgment result >Compatibility between the replacement element in the benefit set corresponding to the kp-th abnormal feature field in the kth transmission data information set and the adjacent element,
sequentially combining the replacement elements with adjacent elements to obtain a replacement combination set E, arbitrarily obtaining one combination, calculating the comprehensive influence index of the combination after replacement on the combination before replacement, and marking as Y effect ，
Where e represents the total number of replacement elements,representing a weight value, the weight value being a database preset value,
τ t* (k before t ，k t* ，k After t ) Representing a post-replacement form query function for pre-setting a form query combination by a database to (k) Before t ，k t* ，k After t ) Corresponding quantized value τ t (k Before t ，k t ，k After t ) Representing a pre-replacement form query function for pre-setting a form query combination by a database to (k) Before t ，k t ，k After t ) Corresponding quantized values, circularly calculating and selecting Y by combining calculation results effect The combination corresponding to the minimum value is used as a replacement result,
if the degree of dispersion mu kp If the data information source is not in the preset interval, indicating the abnormal data information sourceBenefit set corresponding to kp-th abnormal characteristic field in kth transmission data information setIf the same benefit value does not exist between the reference set and the abnormal data information source +. >The kth abnormal characteristic field in the kth transmission data information set can not be replaced by the corresponding characteristic field in the safety transmission data information set;
step 2008, repeating step 2007, and providing an abnormal data information sourceThe abnormal characteristic fields of each transmission data information set can be classified into a type by replacing the corresponding transmission data information set with elements in the reference set, and are recorded as
Wherein->Information source representing abnormal data->W is more than or equal to 0 and less than or equal to k;
step 2009, executing step 2002, obtains a computer set capable of normally transmitting the transmission data of the first office equipment, and the computer set is denoted as a set R.
According to the method, the device and the system, the data information source classification result is obtained, the packet loss rate of the preprocessed data in the first office equipment in different computer transmission processes is further analyzed, whether the data transmission process is abnormal or not is judged according to the packet loss rate, when the preprocessed data in the first office equipment does not have abnormal conditions, the computer is selected according to the packet loss rate in the data transmission process, when the preprocessed data in the first office equipment has abnormal conditions, whether the abnormal data can be replaced or not is judged, and further the computer capable of being normally transmitted is further selected according to the processed data, so that data reference is provided for the follow-up real-time analysis of whether the current data transmitted by the first office equipment is abnormal or not.
Further, the method for judging whether the data transmission process is abnormal or not comprises the following steps:
step 2002-1, obtaining a data transmission rate of the first office equipment, denoted as V 1 ；
Step 2002-2, obtaining the data output rate of the alpha-stage computer, and recording as V 2 ；
Step 2002-3, judging whether the data output rate of the alpha-th computer meets the normal transmission of the data transmitted by the first office equipment,
if V 1 ≥V 2 Then it is determined that the data output rate of the alpha-th computer does not satisfy the normal transmission of the data transmitted by the first office equipment,
if V 1 <V 2 Judging that the data output rate of the alpha-th computer meets the normal transmission of the data transmitted by the first office equipment;
step 2002-4, repeating steps 2002-2 to 2002-3 to obtain a computer set conforming to normal transmission of the transmission data of the first office equipment, wherein the computer set is denoted as J= (J) 1 ，J 2 ，J 3 ，...，J u ) Wherein J u And the computer which indicates that the u-th station accords with the normal transmission of the transmission data of the first office equipment, wherein J epsilon R.
According to the method, whether the abnormal condition exists in the data information source corresponding to the first office equipment transmission data in the historical data is analyzed, corresponding measures are further taken according to the judging result, if the abnormal value does not exist in the first office equipment transmission data, whether the normal transmission of the first office equipment transmission data is met in the computer transmission process is further judged, if the abnormal value exists in the first office equipment transmission data, the abnormal condition is further processed, and data reference is provided for the follow-up screening of the computers conforming to the normal transmission.
Further, the method in S3 includes the following steps:
step 3001, recording a data information source corresponding to the transmission data required by the current first office equipment as a set g= { G 1 ，G 2 ，G 3 ，...，G t }, wherein G t Representation ofThe method comprises the steps that t-th data information sources are in current first office equipment, and t represents the total number of the data information sources in the current first office equipment;
step 3002, sequentially executing the data information sources corresponding to the data information sets required to be transmitted by the current first office equipment in step 1002-step 1005 to obtain abnormal conditions of the transmitted data information sets corresponding to the data information sources corresponding to the data information sets required to be transmitted by the current first office equipment.
Further, the method in S4 includes the following steps:
step 4001, acquiring an abnormal condition analysis report of a transmission data information set corresponding to a data information source corresponding to a data information set required to be transmitted by the first office equipment in step 3002;
step 4002, combining the analysis report obtained in step 4001 to set the early warning condition value,
if there is no abnormal condition in the transmission data corresponding to the data information source corresponding to the data information set required to be transmitted by the first office device, executing steps 2002-1 to 2002-3, judging whether the data output rate of the corresponding computer meets the normal transmission of the data transmitted by the first office device, when the data output rate of the corresponding computer can meet the normal transmission of the data transmitted by the first office device, not sending out an early warning signal, when the data output rate of the corresponding computer cannot meet the normal transmission of the data transmitted by the first office device, sending out an early warning signal, and replacing the computer to perform data transmission,
If there is an abnormal condition in the transmission data corresponding to the data information source corresponding to the data information set required to be transmitted by the current first office equipment, sending an early warning signal, executing step 2004-step 2008 to obtain the computer set capable of normally transmitting the data transmitted by the current first office equipment, removing the marked computer, obtaining the removed computer set, and screening the computer with the largest occurrence number as the selection of the current first office equipment capable of normally transmitting the data.
An artificial intelligence based device security intelligent supervision system, the system comprising the following modules:
historical data analysis module: the historical data analysis module is used for acquiring a data information source corresponding to the transmission data of the first office equipment through historical data and preprocessing the acquired data information source;
an abnormal data evaluation module: the abnormal data evaluation model is used for analyzing the relation between the preprocessed data in the first office equipment and the computer transmission medium and setting data abnormal judgment conditions;
and a transmission data monitoring module: the transmission data detection module is used for monitoring a data information set required to be transmitted by the current first office equipment in real time, and setting an early warning signal by combining the historical data analysis module and the abnormal data information set assessment module;
And the early warning module is used for: the early warning module is used for further sending out early warning signals according to the analysis result of the transmission data monitoring module and taking corresponding measures for different early warning condition values.
Further, the historical data analysis module comprises a data acquisition unit, a data analysis unit and a data preprocessing unit:
the data acquisition unit is used for acquiring a data information source corresponding to a data information set transmitted by the first office equipment in the historical database;
the data analysis unit is used for further judging abnormal values of the data information set by combining the data of the data acquisition module and marking the abnormal data;
the data preprocessing unit is used for further processing the abnormal value data by combining the analysis result of the data analysis module.
Further, the abnormal data evaluation module comprises an abnormal data analysis unit and an early warning condition judgment unit:
the abnormal data analysis unit is used for acquiring the processing result of the data preprocessing unit and further analyzing abnormal data and judging whether the abnormal data information set can be replaced or not;
the early warning condition judging unit is used for further setting early warning condition values by combining the abnormal data analyzing unit, and setting different early warning benefits according to different abnormal data analyzing results.
Further, the early warning module comprises an early warning unit and an early warning and extinguishing unit:
the early warning unit is used for monitoring whether the data transmission state is abnormal in real time and sending an early warning signal according to the monitoring result;
the early warning and cancellation unit is used for combining the early warning signals of the early warning unit and performing cancellation processing on the opposite early warning signals under different conditions.
According to the invention, the abnormal condition in the data transmission process of the first office equipment is analyzed through the historical data, corresponding measures are further taken in combination with the abnormal condition, and the computer for transmission is selected in combination with the packet loss rate in the data transmission process of the first office equipment by judging whether the corresponding abnormal data in the data transmission process of the first office equipment can be replaced by the data with equivalent benefits, so that the data transmission efficiency of the first office equipment is improved, and the maximization of the data transmission is realized.
Drawings
FIG. 1 is a flow chart of an artificial intelligence based device security intelligent supervision method of the present invention;
FIG. 2 is a schematic diagram of a module of an artificial intelligence based device security intelligent supervision system of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1: referring to fig. 1, in this embodiment:
the method for intelligently monitoring the safety of the equipment based on the artificial intelligence is realized and comprises the following steps:
s1, acquiring a data information source corresponding to transmission data of first office equipment through historical data, preprocessing the acquired data information source, and further classifying the transmission data in the first office equipment according to a preprocessing result;
the method in S1 comprises the following steps:
step 1001, the data information source corresponding to the transmission data of the first office equipment acquired in step S1 is denoted as a set a,
A＝{A 1 ，A 2 ，A 3 ，...，A n }，
wherein A is n The method comprises the steps of representing an nth data information source in first office equipment, wherein n represents the total number of the data information sources in the first office equipment;
step 1002, obtaining any one of the nth data information sources in the first office equipment to transmit the data information set, and recording the data information set as a setWherein->Representing an mth transmission data characteristic field in an nth transmission data information set in an nth data information source in first office equipment, wherein the characteristic field is a database preset value;
step 1003, acquiring an abnormal transmission data information set in the history data, which is marked as a set C,
C＝{C 1 ，C 2 ，C 3 ，...，C i }，
wherein C is i An i-th abnormal characteristic field in the abnormal transmission data information set is represented, and i represents the total number of characteristic fields in the abnormal transmission data information set;
Step 1004, analyzing the similarity degree between the transmission data information set corresponding to the nth data information source in the first office equipment and the abnormal transmission data information set in the historical data, and marking as
Wherein B is n(β) And n C represents an intersection element between any one of the nth data information sources in the first office equipment and the abnormally transmitted data information set in the history data, L (B) n(β) And C) represents the number of intersection elements between any one of the nth data information sources in the first office apparatus and the abnormally transmitted data information set in the history data,
B n(β) U.C represents the union element between any one of the nth data information sources in the first office equipment and the abnormal transmission data information set in the history data, L (B) n(β) U C) represents the number of union elements between any one of the nth data information sources in the first office equipment and the abnormal transmission data information set in the history data,
if it isIndicating that there is no abnormality in the transmission data information set corresponding to the nth data information source in the first office device,
if it isIndicating that the abnormal condition exists in the transmission data information set corresponding to the nth data information source in the first office equipment;
Step 1005, repeating the steps 1002-1004 to obtain an abnormality determination result of each transmission data information set in different data information sources in the first office equipment, and classifying the data information sources corresponding to the transmission data information sets without abnormal data in the first office equipment as E 1 Class, classifying the data information sources corresponding to the transmission data information set with abnormal data in the first office equipment as E 2 Class.
S2, analyzing the relation between the preprocessed transmission data information in the first office equipment and a computer transmission medium, and setting a data abnormality judgment condition by combining the analysis result;
the method in S2 comprises the steps of:
step 2001, obtaining the data information source classification result in step 1005, and optionally extracting E 1 A data information source in the class, denoted asWherein->Representing data information Source +.>A j-th transmission data information set;
step 2002, analyzing packet loss conditions corresponding to the data information sets after the preprocessed data information sets in the first office equipment are transcoded through an alpha-th computer transmission medium, calculating transcoding accuracy, and marking the transcoding accuracy as Y E1 ，
Wherein the method comprises the steps ofRepresenting the total number of data information transmitted after transcoding, < >>Representing data information Source +.>The total number of the data information is transmitted,
If it isThe method indicates that the data information set after the pretreatment in the first office equipment is transcoded by the alpha-th computer transmission medium has no packet loss condition, further judges whether the data information set transmission process has abnormality,
if it isThe situation that the data information set after the preprocessing in the first office equipment is subjected to the transcoding through the alpha-th computer transmission medium has packet loss is indicated, and the corresponding computer transmission medium is marked;
step 2003, obtaining the data information source classification result in step 1005, and optionally extracting E 2 A data information source in the class, denoted asWherein->Representing data information Source +.>A kth transmission data information set;
step 2004, source of anomalous data informationThe benefit set corresponding to the abnormal characteristic field in the kth transmission data information set is marked as a set +.>
Wherein the method comprises the steps ofInformation source representing abnormal data->The benefit set corresponding to the kp-th abnormal characteristic field in the kth transmission data information set;
step 2005, toThe benefit corresponding to the characteristic field in the data information set of the safe transmission in the historical data is taken as a reference set and is recorded as a set L * ，
Wherein the method comprises the steps ofThe method comprises the steps of representing benefits corresponding to a v-th characteristic field in a safe transmission data information set in historical data, wherein v represents the total number of benefits corresponding to the characteristic field in the safe transmission data information set in the historical data, the benefits are database form preset values, and each safe transmission data information set corresponds to one benefit;
Step 2006, source of anomalous data informationThe degree of the dispersion between the benefit set corresponding to the kp-th abnormal characteristic field in the kth transmission data information set and the reference set is recorded as mu kp ，
Step 2007, cycling step 2006 to obtain an abnormal data information sourceThe degree of dispersion between benefit sets corresponding to different abnormal characteristic fields in the kth transmission data information set and the reference set in turn,
if the degree of dispersion mu kp Within the preset interval, indicating the abnormal data information sourceThe same benefit value exists between the benefit set corresponding to the kp-th abnormal characteristic field in the kth transmission data information set and the reference set, and the abnormal data information source is primarily judged>The kth p abnormal characteristic field in the kth transmission data information set can be replaced by the corresponding characteristic field in the safety transmission data information set, and the abnormal data information source is further analyzed based on the preliminary judgment result>Compatibility between the replacement element in the benefit set corresponding to the kp-th abnormal feature field in the kth transmission data information set and the adjacent element,
sequentially combining the replacement elements with adjacent elements to obtain a replacement combination set E, arbitrarily obtaining one combination, calculating the comprehensive influence index of the combination after replacement on the combination before replacement, and marking as Y effect ，
Where e represents the total number of replacement elements,representing a weight value, the weight value being a database preset value,
τ t* (k before t ，k t* ，k After t ) Representing a post-replacement form query function for pre-setting a form query combination by a database to (k) Before t ，k t* ，k After t ) Corresponding quantized value τ t (k Before t ，k t ，k After t ) Representing a pre-replacement form query function for pre-setting a form query combination by a database to (k) Before t ，k t ，k After t ) Corresponding quantized values, circularly calculating and selecting Y by combining calculation results effect The combination corresponding to the minimum value is used as a replacement result,
if the degree of dispersion mu kp If the difference is not within the preset interval, the difference is indicatedConstant data information sourceIf the benefit set corresponding to the kp-th abnormal characteristic field in the kth transmission data information set does not have the same benefit value with the reference set, the abnormal data information source is +.>The kth abnormal characteristic field in the kth transmission data information set can not be replaced by the corresponding characteristic field in the safety transmission data information set;
step 2008, repeating step 2007, and providing an abnormal data information sourceThe abnormal characteristic fields of each transmission data information set can be classified into a type by replacing the corresponding transmission data information set with elements in the reference set, and are recorded as
Wherein->Information source representing abnormal data->W is more than or equal to 0 and less than or equal to k;
step 2009, executing step 2002, obtains a computer set capable of normally transmitting the transmission data of the first office equipment, and the computer set is denoted as a set R.
The method for judging whether the data transmission process is abnormal or not comprises the following steps:
step 2002-1, obtaining a data transmission rate of the first office equipment, denoted as V 1 ；
Step 2002-2, obtaining the data output rate of the alpha-stage computer, and recording as V 2 ；
Step 2002-3, judging whether the data output rate of the alpha-th computer meets the normal transmission of the data transmitted by the first office equipment,
if V 1 ≥V 2 Then it is determined that the data output rate of the alpha-th computer does not satisfy the normal transmission of the data transmitted by the first office equipment,
if V 1 <V 2 Judging that the data output rate of the alpha-th computer meets the normal transmission of the data transmitted by the first office equipment;
step 2002-4, repeating steps 2002-2 to 2002-3 to obtain a computer set conforming to normal transmission of the transmission data of the first office equipment, wherein the computer set is denoted as J= (J) 1 ，J 2 ，J 3 ，...，J u ) Wherein J u And the computer which indicates that the u-th station accords with the normal transmission of the transmission data of the first office equipment, wherein J epsilon R.
S3, monitoring a data information set required to be transmitted by the current first office equipment in real time, and judging an early warning signal by combining the analysis results of the S1 and the S2;
The method in S3 comprises the following steps:
step 3001, recording a data information source corresponding to the transmission data required by the current first office equipment as a set g= { G 1 ，G 2 ，G 3 ，...，G t }, wherein G t The method comprises the steps of representing the t-th data information source in the current first office equipment, wherein t represents the total number of the data information sources in the current first office equipment;
step 3002, sequentially executing the data information sources corresponding to the data information sets required to be transmitted by the current first office equipment in step 1002-step 1005 to obtain abnormal conditions of the transmitted data information sets corresponding to the data information sources corresponding to the data information sets required to be transmitted by the current first office equipment.
S4, sending out an abnormal early warning signal according to the analysis result of S3, and adopting corresponding processing measures for the data required to be transmitted by the current first office equipment according to the type of the early warning signal.
The method in S4 includes the steps of:
step 4001, acquiring an abnormal condition analysis report of a transmission data information set corresponding to a data information source corresponding to a data information set required to be transmitted by the first office equipment in step 3002;
step 4002, combining the analysis report obtained in step 4001 to set the early warning condition value,
if there is no abnormal condition in the transmission data corresponding to the data information source corresponding to the data information set required to be transmitted by the first office device, executing steps 2002-1 to 2002-3, judging whether the data output rate of the corresponding computer meets the normal transmission of the data transmitted by the first office device, when the data output rate of the corresponding computer can meet the normal transmission of the data transmitted by the first office device, not sending out an early warning signal, when the data output rate of the corresponding computer cannot meet the normal transmission of the data transmitted by the first office device, sending out an early warning signal, and replacing the computer to perform data transmission,
If there is an abnormal condition in the transmission data corresponding to the data information source corresponding to the data information set required to be transmitted by the current first office equipment, sending an early warning signal, executing step 2004-step 2008 to obtain the computer set capable of normally transmitting the data transmitted by the current first office equipment, removing the marked computer, obtaining the removed computer set, and screening the computer with the largest occurrence number as the selection of the current first office equipment capable of normally transmitting the data.
In this embodiment:
an artificial intelligence based device security intelligent supervision system (as shown in fig. 2) is disclosed, which is used for realizing the specific scheme content of the method.
Example 2: setting an abnormal data information sourceThere are 3 elements, and the benefits corresponding to each element are recorded as a set
Taking benefits corresponding to all data information sets safely transmitted in historical data as reference sets, and taking abnormal data information sourcesThe benefits corresponding to the elements in the reference set are matched with the elements in the reference set one by one, a replacement element set corresponding to the sensitive word 1 is obtained through similar calculation and is marked as X 1 = (element 1, element 2), the replacement element corresponding to the sensitive word 2 is element 3, and the replacement element set corresponding to the sensitive word 3 is denoted as X 3 = (element 4),
the combination which can be replaced is (element 1, element 3, element 4), (element 2, element 3, element 4) according to the replacement element set
Combining the used replacement element with the adjacent element to obtain a combined body: (k) Before element 1 ，k Element 1 ，k After element 1 )，(k Element 3 front ，k Element 3 ，k Element 3 back )，(k Before element 4 ，k Element 4 ，k Element 4 back )
And (2) combining two: (k) Before element 2 ，k Element 2 ，k Element 2 back )，(k Element 3 front ，k Element 3 ，k Element 3 back )，(k Before element 4 ，k Element 4 ，k Element 4 back )
The combination is obtained by the form query after replacement as (k) Before element 1 ，k Element 1 ，k After element 1 ) The corresponding quantized value is 2, combined as (k Element 3 front ，k Element 3 ，k Element 3 back ) The corresponding quantized value is 3, combined as (k Before element 4 ，k Element 4 ，k Element 4 back ) The corresponding quantized value is 4, combined as (k Before element 2 ，k Element 2 ，k Element 2 back ) The corresponding quantization value is 1 and,
obtaining quantized values corresponding to the combination (element 1, element 3 and element 4) as 4 and quantized values corresponding to the combination (element 2, element 3 and element 4) as 5 through the form query before replacement,
calculating the impact index under the corresponding combination, and marking as Y effect 1 and Y effect 2，
Because of Y effect 1＞Y effect 2, thus Y effect 2 as a result of the substitution.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. An artificial intelligence based device security intelligent supervision method is characterized by comprising the following steps:
s1, acquiring a data information source corresponding to transmission data of first office equipment through historical data, preprocessing the acquired data information source, and further classifying the transmission data in the first office equipment according to a preprocessing result;
s2, analyzing the relation between the preprocessed transmission data information in the first office equipment and a computer transmission medium, and setting a data abnormality judgment condition by combining the analysis result;
s3, monitoring a data information set required to be transmitted by the current first office equipment in real time, and judging an early warning signal by combining the analysis results of the S1 and the S2;
s4, sending out an abnormal early warning signal according to the analysis result of S3, and adopting corresponding processing measures for the data required to be transmitted by the current first office equipment according to the type of the early warning signal.
2. The method for monitoring and controlling the safety and the intelligence of equipment based on artificial intelligence according to claim 1, wherein the method in S1 comprises the following steps:
step 1001, the data information source corresponding to the transmission data of the first office equipment acquired in step S1 is denoted as a set a,
A＝{A 1 ，A 2 ，A 3 ，...，A n }，
wherein A is n The method comprises the steps of representing an nth data information source in first office equipment, wherein n represents the total number of the data information sources in the first office equipment;
Step 1002, obtaining any one of the nth data information sources in the first office equipment to transmit the data information set, and recording the data information set as a setWherein->Representing an mth transmission data characteristic field in an nth transmission data information set in an nth data information source in first office equipment, wherein the characteristic field is a database preset value;
step 1003, acquiring an abnormal transmission data information set in the history data, which is marked as a set C,
C＝{C 1 ，C 2 ，C 3 ，...，C i }，
wherein C is i An i-th abnormal characteristic field in the abnormal transmission data information set is represented, and i represents the total number of characteristic fields in the abnormal transmission data information set;
step 1004, analyzing the similarity degree between the transmission data information set corresponding to the nth data information source in the first office equipment and the abnormal transmission data information set in the historical data, and marking as D similarity (B n(β),C )，
Wherein B is n(β) And n C represents an intersection element between any one of the nth data information sources in the first office equipment and the abnormally transmitted data information set in the history data, L (B) n(β) And C) represents the number of intersection elements between any one of the nth data information sources in the first office apparatus and the abnormally transmitted data information set in the history data,
B n(β) U.C represents the union element between any one of the nth data information sources in the first office equipment and the abnormal transmission data information set in the history data, L (B) n(β) U C) represents the number of union elements between any one of the nth data information sources in the first office equipment and the abnormal transmission data information set in the history data,
if it isIndicating that there is no abnormality in the transmission data information set corresponding to the nth data information source in the first office device,
if it isIndicating that the abnormal condition exists in the transmission data information set corresponding to the nth data information source in the first office equipment;
step 1005, repeating the steps 1002-1004 to obtain an abnormality determination result of each transmission data information set in different data information sources in the first office equipment, and classifying the data information sources corresponding to the transmission data information sets without abnormal data in the first office equipment as E 1 Class, classifying the data information sources corresponding to the transmission data information set with abnormal data in the first office equipment as E 2 Class.
3. The method for device security and intelligence supervision based on artificial intelligence according to claim 2, wherein the method in S2 comprises the following steps:
step 2001, obtaining the data information source classification result in step 1005, and optionally extracting E 1 A data information source in the class, denoted asWherein->Representing data information Source +. >A j-th transmission data information set;
step 2002, analyzing packet loss conditions corresponding to the data information sets after the preprocessed data information sets in the first office equipment are transcoded through an alpha-th computer transmission medium, calculating transcoding accuracy, and marking the transcoding accuracy as Y E1 ，
Wherein the method comprises the steps ofRepresenting the total number of data information transmitted after transcoding, < >>Representing data information Source +.>The total number of the data information is transmitted,
if it isThe method indicates that the data information set after the pretreatment in the first office equipment is transcoded by the alpha-th computer transmission medium has no packet loss condition, further judges whether the data information set transmission process has abnormality,
if it isThe situation that the data information set after the preprocessing in the first office equipment is subjected to the transcoding through the alpha-th computer transmission medium has packet loss is indicated, and the corresponding computer transmission medium is marked;
step 2003, obtaining the data information source classification result in step 1005, and optionally extracting E 2 A data information source in the class, denoted asWherein->Representing data information Source +.>A kth transmission data information set;
step 2004, source of anomalous data informationThe benefit set corresponding to the abnormal characteristic field in the kth transmission data information set is marked as a set +. >
Wherein the method comprises the steps ofInformation source representing abnormal data->The benefit set corresponding to the kp-th abnormal characteristic field in the kth transmission data information set;
step 2005, taking the benefit corresponding to the characteristic field in the data information set safely transmitted in the historical data as a reference set, and recording as a set L * ，
Wherein the method comprises the steps ofRepresenting the benefit corresponding to the v-th characteristic field in the safety transmission data information set in the historical data, wherein v represents the total number of benefits corresponding to the characteristic field in the safety transmission data information set in the historical data, the benefits are database form preset values, and each safety transmission data messageThe interest set corresponds to one benefit;
step 2006, source of anomalous data informationThe degree of the dispersion between the benefit set corresponding to the kp-th abnormal characteristic field in the kth transmission data information set and the reference set is recorded as mu kp ，
Step 2007, cycling step 2006 to obtain an abnormal data information sourceThe degree of dispersion between the benefit sets corresponding to the abnormal characteristic fields in each transmission data information set and the reference set in turn,
if the degree of dispersion mu kp Within the preset interval, indicating the abnormal data information sourceThe same benefit value exists between the benefit set corresponding to the kp-th abnormal characteristic field in the kth transmission data information set and the reference set, and the abnormal data information source is primarily judged >The kth p abnormal characteristic field in the kth transmission data information set can be replaced by the corresponding characteristic field in the safety transmission data information set, and the abnormal data information source is further analyzed based on the preliminary judgment result>Compatibility between the replacement element in the benefit set corresponding to the kp-th abnormal feature field in the kth transmission data information set and the adjacent element,
to replace element and adjacent elementSequentially combining to obtain a replacement combination set E, arbitrarily obtaining one combination, calculating the comprehensive influence index of the combination after replacement on the combination before replacement, and marking as Y effect ，
Where e represents the total number of replacement elements,representing a weight value, the weight value being a database preset value,
τ t* (k before t ，k t* ，k After t ) Representing a post-replacement form query function for pre-setting a form query combination by a database to (k) Before t ，k t* ，k After t ) Corresponding quantized value τ t (k Before t ，k t ，k After t ) Representing a pre-replacement form query function for pre-setting a form query combination by a database to (k) Before t ，k t ，k After t ) Corresponding quantized values, circularly calculating and selecting Y by combining calculation results effect The combination corresponding to the minimum value is used as a replacement result,
If the degree of dispersion mu kp If the data information source is not in the preset interval, indicating the abnormal data information sourceIf the benefit set corresponding to the kp-th abnormal characteristic field in the kth transmission data information set does not have the same benefit value with the reference set, the abnormal data information source is +.>The kth abnormal characteristic field in the kth transmission data information set can not be replaced by the corresponding characteristic field in the safety transmission data information set;
step 2008Repeating step 2007 to obtain abnormal data information sourceThe abnormal characteristic fields of each transmission data information set can be classified into a type by replacing the corresponding transmission data information set with elements in the reference set, and are recorded as
Wherein->Information source representing abnormal data->W is more than or equal to 0 and less than or equal to k;
step 2009, executing step 2002, obtains a computer set capable of normally transmitting the transmission data of the first office equipment, and the computer set is denoted as a set R.
4. The device security intelligent supervision method based on artificial intelligence according to claim 3, wherein the method for judging whether the data transmission process is abnormal comprises the following steps:
step 2002-1, obtaining a data transmission rate of the first office equipment, denoted as V 1 ；
Step 2002-2, obtaining the data output rate of the alpha-stage computer, and recording as V 2 ；
Step 2002-3, judging whether the data output rate of the alpha-th computer meets the normal transmission of the data transmitted by the first office equipment,
if V 1 ≥V 2 Then it is determined that the data output rate of the alpha-th computer does not satisfy the normal transmission of the data transmitted by the first office equipment,
if V 1 <V 2 Judging that the data output rate of the alpha-th computer meets the normal transmission of the data transmitted by the first office equipment;
step 2002-4, repeating steps 2002-2 to 2002-3 to obtain a computer set conforming to normal transmission of the transmission data of the first office equipment, wherein the computer set is denoted as J= (J) 1 ，J 2 ，J 3 ，...，J u ) Wherein J u And the computer which indicates that the u-th station accords with the normal transmission of the transmission data of the first office equipment, wherein J epsilon R.
5. A method of device security intelligent supervision based on artificial intelligence according to claim 3, wherein the method in S3 comprises the steps of:
step 3001, recording a data information source corresponding to the transmission data required by the current first office equipment as a set g= { G 1 ，G 2 ，G 3 ，...，G t }, wherein G t The method comprises the steps of representing the t-th data information source in the current first office equipment, wherein t represents the total number of the data information sources in the current first office equipment;
step 3002, sequentially executing the data information sources corresponding to the data information sets required to be transmitted by the current first office equipment in step 1002-step 1005 to obtain abnormal conditions of the transmitted data information sets corresponding to the data information sources corresponding to the data information sets required to be transmitted by the current first office equipment.
6. A method of device security intelligent supervision based on artificial intelligence according to claim 3, wherein the method in S4 comprises the steps of:
step 4001, acquiring an abnormal condition analysis report of a transmission data information set corresponding to a data information source corresponding to a data information set required to be transmitted by the first office equipment in step 3002;
step 4002, combining the analysis report obtained in step 4001 to set the early warning condition value,
if there is no abnormal condition in the transmission data corresponding to the data information source corresponding to the data information set required to be transmitted by the first office device, executing steps 2002-1 to 2002-3, judging whether the data output rate of the corresponding computer meets the normal transmission of the data transmitted by the first office device, when the data output rate of the corresponding computer can meet the normal transmission of the data transmitted by the first office device, not sending out an early warning signal, when the data output rate of the corresponding computer cannot meet the normal transmission of the data transmitted by the first office device, sending out an early warning signal, and replacing the computer to perform data transmission,
if there is an abnormal condition in the transmission data corresponding to the data information source corresponding to the data information set required to be transmitted by the current first office equipment, sending an early warning signal, executing step 2004-step 2008 to obtain the computer set capable of normally transmitting the data transmitted by the current first office equipment, removing the marked computer, obtaining the removed computer set, and screening the computer with the largest occurrence number as the selection of the current first office equipment capable of normally transmitting the data.
7. An artificial intelligence based device security intelligent supervision system, characterized in that the system comprises the following modules:
historical data analysis module: the historical data analysis module is used for acquiring a data information source corresponding to the transmission data of the first office equipment through historical data and preprocessing the acquired data information source;
an abnormal data evaluation module: the abnormal data evaluation model is used for analyzing the relation between the preprocessed data in the first office equipment and the computer transmission medium and setting data abnormal judgment conditions;
and a transmission data monitoring module: the transmission data detection module is used for monitoring a data information set required to be transmitted by the current first office equipment in real time, and setting an early warning signal by combining the historical data analysis module and the abnormal data information set assessment module;
and the early warning module is used for: the early warning module is used for further sending out early warning signals according to the analysis result of the transmission data monitoring module and taking corresponding measures for different early warning condition values.
8. The artificial intelligence based device security intelligent supervision system according to claim 7, wherein the historical data analysis module comprises a data acquisition unit, a data analysis unit, and a data preprocessing unit:
The data acquisition unit is used for acquiring a data information source corresponding to a data information set transmitted by the first office equipment in the historical database;
the data analysis unit is used for further judging abnormal values of the data information set by combining the data of the data acquisition module and marking the abnormal data;
the data preprocessing unit is used for further processing the abnormal value data by combining the analysis result of the data analysis module.
9. The artificial intelligence based device security intelligent supervision system according to claim 8, wherein the abnormal data assessment module comprises an abnormal data analysis unit and an early warning condition determination unit:
the abnormal data analysis unit is used for acquiring the processing result of the data preprocessing unit and further analyzing abnormal data and judging whether the abnormal data information set can be replaced or not;
the early warning condition judging unit is used for further setting early warning condition values by combining the abnormal data analyzing unit, and setting different early warning benefits according to different abnormal data analyzing results.
10. The device security intelligent supervision system based on artificial intelligence according to claim 9, wherein the early warning module comprises an early warning unit and an early warning and elimination unit:
The early warning unit is used for monitoring whether the data transmission state is abnormal in real time and sending an early warning signal according to the monitoring result;
the early warning and cancellation unit is used for combining the early warning signals of the early warning unit and performing cancellation processing on the opposite early warning signals under different conditions.
CN202310568947.1A 2023-05-19 2023-05-19 Equipment safety intelligent supervision system and method based on artificial intelligence Pending CN116527540A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117037349A (en) * 2023-08-28 2023-11-10 珠海市辰宇智能技术有限公司 Face recognition technology and data interaction service management and control method and system
CN117251331A (en) * 2023-11-17 2023-12-19 常州满旺半导体科技有限公司 Chip performance data supervision and transmission system and method based on Internet of things

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117037349A (en) * 2023-08-28 2023-11-10 珠海市辰宇智能技术有限公司 Face recognition technology and data interaction service management and control method and system
CN117037349B (en) * 2023-08-28 2024-02-20 珠海市辰宇智能技术有限公司 Face recognition technology and data interaction service management and control method and system
CN117251331A (en) * 2023-11-17 2023-12-19 常州满旺半导体科技有限公司 Chip performance data supervision and transmission system and method based on Internet of things
CN117251331B (en) * 2023-11-17 2024-01-26 常州满旺半导体科技有限公司 Chip performance data supervision and transmission system and method based on Internet of things

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