CN111159715A - Industrial control safety audit system and method based on artificial intelligence - Google Patents
Industrial control safety audit system and method based on artificial intelligence Download PDFInfo
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/50—Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
- G06F21/57—Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
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Abstract
The invention discloses an industrial control safety audit system and method based on artificial intelligence, which comprises an audit service end, a switch, an industrial control equipment control end and industrial control equipment, wherein the audit service end, the industrial control equipment control end and the industrial control equipment are connected through the switch; the industrial control equipment control terminal is provided with an audit client, the audit client is communicated with the audit server, and the audit client is used for monitoring and auditing the process, the memory and the CPU use condition of the industrial control equipment control terminal, receiving the strategy information of the audit server and transmitting the audit information of the audit client to the audit server for unified analysis; the auditing server is used for monitoring and auditing the flow, the protocol and the original destination address in the industrial control equipment control end and the industrial control equipment, and visually displaying the auditing result, and the system can fully ensure the safety of the industrial control system.
Description
Technical Field
The invention relates to the field of industrial control safety, in particular to an industrial control safety audit system and method based on artificial intelligence.
Background
With the development of network information technology, more and more industrial control systems are built to be put into production, but the risk is higher and higher. The industrial control network is different from a general office network, belongs to a productive network, and aims at the field of industrial production, wherein the harm is brought by attack. Industrial production is vital for a country and an enterprise, the important industrial production field of the country is damaged, so that social supply is short and social instability is caused, the important industrial production line of the enterprise is damaged, so that production cannot be normally operated, even loss or failure of the enterprise is caused, harm caused by industrial control safety events is greatly higher than that of a common network, the importance of industrial control safety is deeply recognized by countries since 2010 network virus shaking events, 2015 Polish airline events and 2015 Ukran power grid events, and research and investment on the industrial control safety are continuously increased.
For industrial control safety, relevant standards and requirements are set by all countries. China publishes 'network security level protection 2.0' in 2019, 5 months and 10 days, writes relevant requirements of industrial control security into standards, and brings the requirements into the equal protection evaluation range; the united states issued the Control System Security Program (CSSP) by the united states department of homeland security as early as 2011. Along with the requirements of national security standards, the detection and protection of industrial control security are gradually enhanced, so that corresponding security audit equipment is required to be continuously upgraded, and the detection accuracy is improved aiming at a continuously changing attack mode.
Therefore, the invention provides an industrial control safety auditing system and method based on artificial intelligence to strengthen the detection and protection of industrial control safety.
Disclosure of Invention
Technical problem to be solved
The invention aims to solve the technical problem that the industrial control system in the prior art is low in safety.
(II) technical scheme
The invention provides an industrial control safety audit system based on artificial intelligence, which comprises an audit service end, a switch, an industrial control equipment control end and industrial control equipment, wherein the audit service end, the industrial control equipment control end and the industrial control equipment are connected through the switch;
the industrial control equipment control terminal is provided with an audit client, the audit client is communicated with an audit server, and the audit client is used for monitoring and auditing the process, the memory and the CPU use condition of the industrial control equipment control terminal, receiving the strategy information of the audit server and transmitting the audit information of the audit client to the audit server for unified analysis; and the auditing server is used for monitoring and auditing the industrial control equipment control end and the flow, the protocol and the original destination address in the industrial control equipment, and visually displaying the auditing result.
Furthermore, the industrial control equipment control end is a computer.
Furthermore, the audit client comprises a first intelligent analysis module and a monitoring module, wherein the monitoring module is connected with the first intelligent analysis module so as to transmit information to the first intelligent analysis module for audit analysis.
Furthermore, the first intelligent analysis module is connected with the industrial control equipment control end, the first intelligent analysis module learns on a computer before being used, and a classification model is established for the process, the CPU and the memory usage used during the normal operation of the computer; the monitoring module is connected with the industrial control equipment control end to monitor and audit the use and abnormal conditions of processes, CPUs and memories on a computer and monitor and audit the installation and the uninstallation of programs.
Furthermore, the audit server comprises a collection module, a second intelligent analysis module and a display module which are connected in sequence, wherein the collection module is connected with the industrial control equipment control end; the collection module is used for carrying out unified mirror image collection on the industrial control equipment control end and the flow in the industrial control equipment.
Furthermore, the second intelligent analysis module is connected with the industrial control equipment control end, and is used for learning on a computer before use and performing regression modeling on a protocol, an original destination address and flow under the normal operation of the computer.
Furthermore, the display module displays the abnormal process, the abnormal memory, the abnormal CPU service time and the abnormal flow in a classified manner according to the auditing analysis results of the first intelligent analysis module and the second intelligent analysis module, and provides a statistical and visual analysis chart for an administrator.
The invention also provides an industrial control safety audit method based on artificial intelligence, which comprises the following steps:
s1: installing an audit client on a control end of industrial control equipment to perform learning modeling;
s2: the auditing server is accessed to an industrial control network for learning modeling;
s3: the audit client and the audit server carry out audit on industrial control equipment and the industrial control equipment control terminal;
s4: when the auditing client side finds abnormal conditions, the auditing server side pops up windows to alarm the abnormal conditions and sends the abnormal condition information to the auditing server side;
s5: and when the audit server side finds the abnormal condition, the abnormal condition is sent to an administrator.
Further, in step S1, manually intervene on the content learned by the auditing client, manually filter the learned content, or manually add a new rule or modify a white list, so as to reduce the error rate generated by intelligent learning; in step S2, the content learned by the auditing server is manually intervened, and the learned content is manually screened or a new rule is manually added or a white list is modified, so as to reduce the error rate generated by intelligent learning.
Further, when the auditing client and the auditing server find abnormal conditions at the same time, the relation between the abnormal conditions is analyzed, the analysis result is informed to an administrator, and the alarm content is specially marked.
(III) advantageous effects
The technical scheme of the invention has the following advantages:
in the industrial control safety audit system based on artificial intelligence, the audit service end, the industrial control equipment control end and the industrial control equipment are connected through the switch, and the audit service end is connected with the switch so as to realize information transmission among the audit service end, the industrial control equipment control end and the industrial control equipment and facilitate the audit service end to monitor and audit the industrial control equipment and the industrial control equipment control end;
the industrial control equipment control end is provided with an audit client which is communicated with the audit server and is convenient for information transmission between the audit client and the audit server, the audit client is used for monitoring and auditing the process, the memory and the CPU use condition of the industrial control equipment control end, receiving strategy information of the audit server, transmitting the audit information of the audit client to the audit server for unified analysis, and the audit client monitors the work conditions of the industrial control equipment and the industrial control equipment control end to ensure the safety of an industrial control system; the auditing server is used for monitoring and auditing the flow, protocol and original destination address in the industrial control equipment control end and the industrial control equipment, visually displaying the auditing result, and performing double monitoring auditing of the auditing server and the auditing client, so that the abnormal conditions in the industrial control system can be comprehensively analyzed, the risk can be better positioned and identified, and the auditing accuracy is improved.
According to the industrial control safety audit method based on artificial intelligence, an audit client is installed on a control end of industrial control equipment to perform learning modeling, and the audit client is installed in the normal operation environment of the control end of the industrial control equipment in advance to perform learning modeling, so that a basis can be provided for subsequent monitoring and auditing; the auditing service end is accessed to an industrial control network for learning and modeling, and the learning and modeling under the normal operation condition can provide a basis for subsequent monitoring and auditing during initial use; the audit client and the audit server audit the industrial control equipment and the industrial control equipment control end, and the industrial control equipment control end are monitored in real time for abnormal conditions, so that the safety of an industrial control network is fully guaranteed; when the audit client side finds the abnormal condition, the audit client side pops the windows to give an alarm, sends the information of the abnormal condition to the audit server side, and when the audit server side finds the abnormal condition, sends the abnormal condition to an administrator, so that a guarantee is provided for an operator to find the abnormal condition in time.
Meanwhile, in the technical scheme provided by the invention, the artificial intelligence learning module is adopted, the system has automatic learning capability, new rules can be continuously learned in the using process, and the safety audit capability of the industrial control system is improved. The second intelligent analysis module of the audit server can combine the results of the first intelligent analysis module of the audit client to synchronously compare the abnormal conditions with the flow service conditions, analyze the association system between the abnormal conditions and improve the accuracy of the analysis results. And the first intelligent analysis module and the second intelligent analysis module can continuously learn after being put into use, continuously optimize the classification model parameters, and correct the established classification model, so that the auditing function of the system can be adjusted according to the adjustment of the system, the reliability of industrial control auditing is further improved, and the safety of the industrial control system is further improved.
Drawings
FIG. 1 is a schematic structural diagram of an industrial control safety audit system based on artificial intelligence;
FIG. 2 is a schematic diagram of the structure of an artificial intelligence-based industrial control safety audit system.
In the figure: 1. an audit server side; 2. auditing a client; 3. a switch; 4. a control end of industrial control equipment; 5. industrial control equipment; 6. a first intelligent analysis module; 7. a monitoring module; 8. a display module; 9. a second intelligent analysis module; 10. and a collection module.
Detailed Description
The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on those shown in the drawings, and are used only for convenience in describing the present invention and for simplicity in description, and do not indicate or imply that the referenced devices or elements must have a particular orientation, be constructed in a particular orientation, and be operated, and thus are not to be construed as limiting the present invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
As shown in fig. 1-2, the invention provides an industrial control safety audit system based on artificial intelligence, which comprises an audit server 1, a switch 3, an industrial control equipment control terminal 4 and an industrial control equipment 5, wherein the audit server 1, the industrial control equipment control terminal 4 and the industrial control equipment 5 are connected through the switch 3, and the audit server 1 is connected with the switch to realize information transmission among the audit server 1, the industrial control equipment control terminal 4 and the industrial control equipment 5;
the industrial control equipment control terminal 4 is provided with an auditing client terminal 2, the auditing client terminal 2 is communicated with the auditing server terminal 1, and the auditing client terminal 2 is used for monitoring and auditing the process, memory and CPU use conditions of the industrial control equipment control terminal 4, receiving strategy information of the auditing server terminal 1 and transmitting the auditing information of the auditing client terminal 2 to the auditing server terminal 1 for unified analysis; the auditing server 1 is used for monitoring and auditing the flow, protocol and original destination address in the industrial control equipment control terminal 4 and the industrial control equipment 5, and visually displaying the auditing result.
In the above embodiment, the audit server 1, the industrial control equipment control terminal 4 and the industrial control equipment 5 are connected through the switch 3 to realize information communication, the audit client 2 is installed in the industrial control equipment control terminal 4 to monitor and audit the process, memory, CPU service conditions and the like of the industrial control equipment control terminal 4, communication is performed between the audit client 2 and the audit server 1, information communication is facilitated between the audit client 2 and the audit server 1, the audit client 2 receives strategy information of the audit server 1, meanwhile, the audit client 2 also transmits audit information to the audit server 1 to perform unified analysis, monitoring and auditing reliability is improved, and safety of an industrial control system is improved.
Preferably, the industrial control equipment control terminal 4 is a computer.
Specifically, audit client 2 includes first intelligent analysis module 6 and monitoring module 7, and monitoring module 7 is connected with first intelligent analysis module 6 to pass information to first intelligent analysis module 6 audit analysis. The monitoring module 7 is used for monitoring and auditing the use and abnormal conditions of processes, CPUs, memories and the like on the computer, monitoring and auditing the installation and the uninstallation of programs, and the monitoring module 7 transmits the monitored information to the first intelligent analysis module 6 for analysis.
Specifically, the first intelligent analysis module 6 is connected with a computer, the first intelligent analysis module 6 learns on the computer before being used, and a classification model is established for a process, a CPU and memory usage used during normal operation of the computer; the monitoring module 7 is connected with a computer to monitor and audit the use and abnormal conditions of processes, CPUs and memories on the computer and monitor and audit the installation and uninstallation of programs. The auditing client is installed on a computer and runs for two weeks for learning modeling, namely, the first intelligent analysis module 6 establishes a classification model under the computer running normally, and when an abnormal process occurs, the usage amount of a CPU and a memory exceeds an expected value, a popup alarm is given in time, and information is sent to the auditing server.
Specifically, the audit server 1 comprises a collection module 10, a second intelligent analysis module 9 and a display module 8 which are connected in sequence, wherein the collection module 10 is connected with the industrial control equipment control terminal 4; the collection module 10 is used for performing unified mirror image collection on the flows in the industrial control equipment control end 4 and the industrial control equipment 5. The collection module 10 transmits the collected information to the second intelligent analysis module 9 for auditing, and the second intelligent analysis module 9 transmits the auditing result to the display module 8.
Specifically, the second intelligent analysis module 9 is connected to the industrial control device control terminal 4, and performs learning on the computer before use, performs regression modeling on the protocol, the destination address and the flow rate of the computer in normal operation, and performs an alarm when the second intelligent analysis module 9 compares the actual situation with the model of the computer in normal operation and finds that the actual situation deviates from the model. The second intelligent analysis module 9 continuously learns after being put into use, continuously optimizes the classification model parameters, and corrects the established classification model, so that the auditing function of the system can be adjusted according to the adjustment of the system. And the second intelligent analysis module 9 can combine the result of the first intelligent analysis module to synchronously compare the abnormal conditions with the network flow conditions, analyze the relevance between the abnormal conditions and improve the reliability of the analysis result.
Specifically, the display module 8 displays the abnormal process, the abnormal memory, the abnormal CPU service time, and the abnormal traffic in a classified manner according to the audit analysis results of the first intelligent analysis module 6 and the second intelligent analysis module 9, and provides a statistical and visual analysis chart for an administrator.
The invention also provides an industrial control safety audit method based on artificial intelligence, which comprises the following steps:
s1: the audit client terminal 2 is installed on the industrial control equipment control terminal 4 for learning modeling;
s2: accessing the audit server 1 to an industrial control network for learning modeling;
s3: the auditing client 2 and the auditing server 1 audit the industrial control equipment 5 and the industrial control equipment control terminal 4;
s4: when the auditing client 2 finds the abnormal condition, the auditing server pops up the alarm of the abnormal condition and sends the information of the abnormal condition to the auditing server 1;
s5: and when the auditing server 1 finds the abnormal condition, the abnormal condition is sent to an administrator.
In the above embodiment, the audit server 1 and the audit client 2 perform learning modeling in advance in a normal operating environment of the industrial control equipment control terminal to provide a basis for subsequent monitoring and auditing, when the audit client 2 and the audit server 1 perform auditing on the industrial control equipment 5 and the industrial control equipment control terminal 4 to find abnormality, the audit client 2 performs popup alarm on the abnormal condition, and the audit server 1 sends the abnormal condition to a manager.
Specifically, in step S1, manually intervene on the content learned by the audit client 2, manually screen the learned content, or manually add a new rule or modify a white list, so as to reduce the error rate generated by intelligent learning; in step S2, the content learned by the auditing server 1 is manually intervened, and the learned content is manually screened or a new rule is manually added or a white list is modified, so as to reduce the error rate generated by intelligent learning. Through manual intervention on intelligent learning, the error rate generated by intelligent learning is reduced, and the reliability of system monitoring audit is improved.
Specifically, when the audit client 2 and the audit server 1 find abnormal conditions at the same time, the relation between the abnormal conditions is analyzed, the analysis result is notified to the administrator, and the alarm content is specially marked. When the audit client 2 and the audit server 1 find out abnormal conditions at the same time, the danger of the industrial control system is indicated, and the abnormal conditions need to be processed in time.
The invention provides an industrial control safety audit system based on artificial intelligence, which is a set of C-B/S system, and the system supports client access and browser access. The auditing service end 1 can still normally monitor and audit traffic, protocols and the like when the auditing client end 2 is not available. Through intelligent analysis, the client side abnormal condition and the industrial control network abnormal condition are comprehensively analyzed, the relevance between the abnormal conditions is analyzed, risks are better identified and positioned, and the accuracy of safety audit is improved.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (10)
1. The industrial control safety audit system based on artificial intelligence is characterized by comprising an audit server (1), a switch (3), an industrial control equipment control terminal (4) and industrial control equipment (5), wherein the audit server (1), the industrial control equipment control terminal (4) and the industrial control equipment (5) are connected through the switch (3), and the audit server (1) is connected with the switch so as to realize information transmission among the audit server (1), the industrial control equipment control terminal (4) and the industrial control equipment (5);
the industrial control equipment control terminal (4) is provided with an audit client (2), the audit client (2) is communicated with an audit server (1), and the audit client (2) is used for monitoring and auditing the process, the memory and the CPU service condition of the industrial control equipment control terminal (4), receiving the strategy information of the audit server (1), and transmitting the audit information of the audit client (2) to the audit server (1) for unified analysis; the auditing server (1) is used for monitoring and auditing the flow, protocol and original destination address in the industrial control equipment control end (4) and the industrial control equipment (5), and visually displaying the auditing result.
2. The industrial control safety audit system based on artificial intelligence of claim 1 wherein, the industrial control equipment control end (4) is a computer.
3. The artificial intelligence based industrial safety audit system according to claim 2 wherein, the audit client (2) includes a first intelligent analysis module (6) and a monitoring module (7), the monitoring module (7) is connected with the first intelligent analysis module (6) to transmit information to the first intelligent analysis module (6) for audit analysis.
4. The industrial control safety audit system based on artificial intelligence as claimed in claim 3, wherein the first intelligent analysis module (6) is connected with the industrial control equipment control terminal (4), the first intelligent analysis module (6) learns on a computer before use, and establishes a classification model for processes, CPUs and memory usage used during normal operation of the computer; the monitoring module (7) is connected with the industrial control equipment control end (4) to monitor and audit the use and abnormal conditions of processes, CPUs and memories on a computer and monitor and audit the installation and uninstallation of programs.
5. The industrial control safety audit system based on artificial intelligence as claimed in claim 2, wherein the audit service end (1) comprises a collection module (10), a second intelligent analysis module (9) and a display module (8) which are connected in sequence, the collection module (10) is connected with the industrial control equipment control end (4); the collection module (10) is used for carrying out unified mirror image collection on the flow in the industrial control equipment control end (4) and the industrial control equipment (5).
6. The industrial control safety audit system based on artificial intelligence as claimed in claim 5, wherein the second intelligent analysis module (9) is connected with the industrial control equipment control terminal (4), and is used for learning on a computer before use, and performing regression modeling on protocols, original destination addresses and flow sizes under normal operation of the computer.
7. The industrial control safety audit system based on artificial intelligence as claimed in claim 5, wherein the display module (8) displays the abnormal process, the abnormal memory, the abnormal CPU usage time and the abnormal flow in a classified manner according to the audit analysis results of the first intelligent analysis module (6) and the second intelligent analysis module (9), so as to provide a statistical and visual analysis chart for the administrator.
8. An industrial control safety audit method based on artificial intelligence is characterized by comprising the following steps:
s1: an audit client (2) is installed on a control end (4) of industrial control equipment to perform learning modeling;
s2: the auditing server (1) is accessed to an industrial control network for learning modeling;
s3: the auditing client (2) and the auditing server (1) audit the industrial control equipment (5) and the industrial control equipment control terminal (4);
s4: when the auditing client (2) finds the abnormal condition, the auditing server pops up the alarm of the abnormal condition and sends the information of the abnormal condition to the auditing server (1);
s5: and when the audit server (1) finds the abnormal condition, the abnormal condition is sent to an administrator.
9. The artificial intelligence based industrial safety audit method according to claim 8 wherein, in step S1, the content learned by the audit client (2) is manually intervened, and the learned content is manually screened or new rules are manually added or white lists are modified to reduce the error rate generated by intelligent learning; in step S2, the content learned by the auditing server (1) is manually intervened, and the learned content is manually screened or a new rule is manually added or a white list is modified, so as to reduce the error rate generated by intelligent learning.
10. The industrial control safety audit method based on artificial intelligence as claimed in claim 8, wherein when the audit client (2) and the audit server (1) find abnormal conditions at the same time, the relation between the abnormal conditions is analyzed, the analysis result is informed to the administrator, and the alarm content is specially marked.
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| CN111506022A (en) * | 2019-01-30 | 2020-08-07 | 中国石油天然气集团有限公司 | Industrial control system and safety auditing method in industrial control system |
| CN112437041A (en) * | 2020-10-27 | 2021-03-02 | 北京珞安科技有限责任公司 | Industrial control safety audit system and method based on artificial intelligence |
| CN112804225A (en) * | 2021-01-07 | 2021-05-14 | 北京码牛科技有限公司 | User security audit method and system |
| CN113656122A (en) * | 2021-07-28 | 2021-11-16 | 上海纽盾科技股份有限公司 | Information screening method, device and system for equal protection evaluation |
| CN113746706A (en) * | 2021-09-16 | 2021-12-03 | 杭州安恒信息技术股份有限公司 | Flow analysis method, device and equipment and readable storage medium |
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| CN112437041A (en) * | 2020-10-27 | 2021-03-02 | 北京珞安科技有限责任公司 | Industrial control safety audit system and method based on artificial intelligence |
| CN112437041B (en) * | 2020-10-27 | 2022-11-18 | 北京珞安科技有限责任公司 | Industrial control safety audit system and method based on artificial intelligence |
| CN112804225A (en) * | 2021-01-07 | 2021-05-14 | 北京码牛科技有限公司 | User security audit method and system |
| CN113656122A (en) * | 2021-07-28 | 2021-11-16 | 上海纽盾科技股份有限公司 | Information screening method, device and system for equal protection evaluation |
| CN113656122B (en) * | 2021-07-28 | 2023-05-16 | 上海纽盾科技股份有限公司 | Information screening method, device and system for equal-protection assessment |
| CN113746706A (en) * | 2021-09-16 | 2021-12-03 | 杭州安恒信息技术股份有限公司 | Flow analysis method, device and equipment and readable storage medium |
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