CN113194080A - Network security system based on cloud computing and artificial intelligence - Google Patents
Network security system based on cloud computing and artificial intelligence Download PDFInfo
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- CN113194080A CN113194080A CN202110447079.2A CN202110447079A CN113194080A CN 113194080 A CN113194080 A CN 113194080A CN 202110447079 A CN202110447079 A CN 202110447079A CN 113194080 A CN113194080 A CN 113194080A
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- 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
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1408—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
- H04L63/1425—Traffic logging, e.g. anomaly detection
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- 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
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- 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
- H04L41/069—Management of faults, events, alarms or notifications using logs of notifications; Post-processing of notifications
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- 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
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1441—Countermeasures against malicious traffic
- H04L63/145—Countermeasures against malicious traffic the attack involving the propagation of malware through the network, e.g. viruses, trojans or worms
Abstract
The invention relates to the technical field of network security, in particular to a network security system based on cloud computing and artificial intelligence, and aims to solve the problems that in the prior art, data information is difficult to accurately analyze, and judgment is only carried out through single data after data analysis, so that the judgment accuracy is lacked; the cloud computing unit is connected with the data acquisition unit and used for processing the data to be analyzed; the artificial intelligence monitoring unit is connected with the cloud computing unit and used for comparing the processed data to be analyzed and judging to obtain a monitoring result; and the protection unit is connected with the artificial intelligent monitoring unit and used for acquiring a monitoring result and automatically performing coping actions of isolating viruses, notifying an alarm and uploading data stored by the client when the protection unit is attacked by a network. The invention has more comprehensive and accurate analysis of the data information, avoids the influence on judgment caused by the analysis error of the data information, saves time and improves the working efficiency.
Description
Technical Field
The invention relates to the technical field of network security, in particular to a network security system based on cloud computing and artificial intelligence.
Background
Artificial intelligence is a branch of computer science, which attempts to understand the essence of intelligence and produces a new intelligent machine that can respond in a manner similar to human intelligence, the research in this field includes robots, language recognition, image recognition, natural language processing, expert systems, etc., artificial intelligence has grown in theory and technology since birth, and the application field is expanding, it can be assumed that the scientific and technological products brought by future artificial intelligence will be the ' container ' of human intelligence, artificial intelligence can simulate the information process of human consciousness and thinking, artificial intelligence is not human intelligence but can think like people and can exceed human intelligence, with the development of society, network technology is also perfected, but network technology has some safety problems, many people acquire other people's information through network and communicate through short messages, etc., thereby obtaining the labor achievement of others.
The network security system based on artificial intelligence, which is disclosed in the prior patent publication No. CN108965253A, can perform anti-tracking on Trojan viruses and the like through a cloud computing anti-tracking system, can monitor a network environment through an AI artificial intelligence technology through an artificial intelligence monitoring system, can analyze whether the network environment of data exists safely through a big data analysis platform, can monitor the network where the data exists through a safety environment monitoring module, can intercept fraud data through a fraud data interception system, can isolate Trojan viruses through a Trojan virus isolation system, and can detect and process leak data through a leak data detection module, through the data protection isolated system who sets up for protect the isolation to handle data, structure scientific and reasonable, convenience safe in utilization provides very big help for people, but, this network safety system based on artificial intelligence can't realize the setting of analytical element, carries out accurate analysis to data information, and simultaneously, just judge through single data after data analysis, thereby lack the accuracy of judging, for this reason, we propose a network safety system based on cloud computing and artificial intelligence.
Disclosure of Invention
Therefore, an object of the present invention is to provide a network security system based on cloud computing and artificial intelligence, which solves the problems that it is difficult to accurately analyze data information and the determination is performed only by single data after the data analysis, so that the determination accuracy is lacking in the prior art.
The technical purpose of the invention is realized by the following technical scheme:
a cloud computing and artificial intelligence based network security system comprising:
the data acquisition unit is used for acquiring data to be analyzed;
the cloud computing unit is connected with the data acquisition unit and used for processing data to be analyzed;
the artificial intelligence monitoring unit is connected with the cloud computing unit and used for comparing the processed data to be analyzed and judging to obtain a monitoring result;
and the protection unit is connected with the artificial intelligence monitoring unit and used for acquiring a monitoring result and automatically performing coping actions of isolating viruses, notifying an alarm and uploading data stored by the client when the artificial intelligence monitoring unit is attacked by a network.
Optionally, the data acquisition unit forms a detailed log of the operation behavior of the host and the object by timing, polling and/or specifying an acquisition rule of a real-time task, where the detailed log includes, but is not limited to, a user name, an IP, an operation, a resource, an access type, time, an authorization result, a summary of a specific design new event, a risk event, report management, system maintenance, rule management, and log retrieval.
Optionally, the cloud computing unit comprises:
the data analysis unit is used for splitting, counting and analyzing the data to be analyzed;
and the data clearing unit is connected with the data analysis unit and is used for clearing redundant data in the data to be analyzed.
Optionally, the artificial intelligence monitoring unit includes:
the training unit is used for training according to various preset loopholes, viruses and preset network security situation prediction results to obtain an artificial intelligence information analysis model;
the extraction unit is connected with the training unit and used for extracting bugs and viruses of the data to be analyzed after being processed by the cloud computing unit;
and the computing unit is connected with the training unit and the extracting unit and used for computing to obtain a network security situation prediction result according to the extracted bugs and viruses and through an artificial intelligence information analysis model.
Optionally, the training unit comprises:
the extraction subunit is used for respectively extracting data parameters of preset bugs and viruses to form a characteristic parameter set;
the processing subunit is used for presetting various network security situation prediction results;
and the training subunit is used for using the characteristic parameter set as input, using a preset network security situation prediction result as expected output, using a self-learning classification method for training, and using a self-learning classifier obtained by training as the artificial intelligence information analysis model.
Optionally, the artificial intelligence monitoring unit is connected with a visualization unit, and the visualization unit performs visualization display on the generated network security situation prediction result in a tree diagram and time sequence diagram manner.
Optionally, the guard unit comprises:
the processing unit is used for repairing the loophole and monitoring, isolating and clearing the virus;
the early warning unit is used for realizing local and/or remote alarm in a mode of informing the mobile terminal by using a flash lamp, a buzzer and a short message;
and the export unit is used for exporting the client storage data and encrypting the client storage data.
Optionally, the export unit is connected with a watermark editing unit which adds a user name, an IP, and time as contents, and the export unit is connected with a cloud disk through the watermark editing unit, and the cloud disk is provided with three security attributes of locking, read-only, and read-write, and can set the security attributes of individuals/groups/all cloud disks through a management background.
The invention has the beneficial effects that:
monitoring network environment through artificial intelligence and cloud computing technology, carry out the analysis to the data collection, whether safe through the network environment that the analytic data exists, and intercept corresponding risk data information, through the integrated processing to various data, judge, increase the accuracy of judging, intercept risk data information, avoid the user to receive the influence after receiving data information, thereby bring the loss of each side, structure scientific and reasonable, convenience safe in utilization, provide very big help for people, and the device has better spreading value.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a schematic diagram of module connections of a network security system based on cloud computing and artificial intelligence according to an embodiment of the present invention.
Description of reference numerals:
1. a data acquisition unit; 2. a cloud computing unit; 21. a data analysis unit; 22. a data clearing unit; 3. an artificial intelligence monitoring unit; 31. a training unit; 32. an extraction unit; 33. a calculation unit; 4. a protection unit; 41. a processing unit; 42. an early warning unit; 43. a derivation unit; 5. a watermark editing unit; 6. a cloud disk; 7. a visualization unit.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that embodiments of the application described herein may be used. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In this application, the terms "upper", "lower", "left", "right", "front", "rear", "top", "bottom", "inner", "outer", "middle", "vertical", "horizontal", "lateral", "longitudinal", and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings. These terms are used primarily to better describe the present application and its embodiments, and are not used to limit the indicated devices, elements or components to a particular orientation or to be constructed and operated in a particular orientation.
Moreover, some of the above terms may be used to indicate other meanings besides the orientation or positional relationship, for example, the term "on" may also be used to indicate some kind of attachment or connection relationship in some cases. The specific meaning of these terms in this application will be understood by those of ordinary skill in the art as appropriate.
In addition, the term "plurality" shall mean two as well as more than two.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
A network security system based on cloud computing and artificial intelligence, as shown in fig. 1, includes a data acquisition unit 1 for acquiring data to be analyzed; the cloud computing unit 2 is connected with the data acquisition unit 1 and used for processing data to be analyzed; the artificial intelligence monitoring unit 3 is connected with the cloud computing unit 2 and used for comparing the processed data to be analyzed and judging to obtain a monitoring result; and the protection unit 4 is connected with the artificial intelligence monitoring unit 3 and used for acquiring a monitoring result and automatically performing coping actions of isolating viruses, notifying an alarm and uploading data stored by the client when the client is attacked by a network.
As shown in fig. 1, the data collection unit 1 forms a detailed log of the operation behaviors of the host and the object by timing, polling and/or specifying the collection rules of the real-time tasks, where the detailed log includes but is not limited to a user name, an IP, an operation, a resource, an access type, time, an authorization result, a summary of a specific design new event, a risk event, report management, system maintenance, rule management, and log retrieval.
As shown in fig. 1, the cloud computing unit 2 includes a data analysis unit 21, configured to perform splitting, statistics, and analysis operations on data to be analyzed; and the data clearing unit 22 is connected with the data analysis unit 21 and is used for clearing redundant data in the data to be analyzed. The cloud computing unit 2 decomposes a huge data computing processing program into countless small programs through a network cloud, then processes and analyzes the small programs through a system consisting of a plurality of servers to obtain results and returns the results, and the results are not only distributed computing, but also results of hybrid evolution and leap of computer technologies such as distributed computing, utility computing, load balancing, parallel computing, network storage, hot backup, redundancy, virtualization and the like, so that data information is accurately analyzed, and the judgment accuracy is improved.
As shown in fig. 1, the artificial intelligence monitoring unit 3 includes a training unit 31, which trains according to preset various vulnerabilities, viruses and preset network security situation prediction results to obtain an artificial intelligence information analysis model; the extraction unit 32 is connected with the training unit 31 and is used for extracting bugs and viruses of the data to be analyzed after being processed by the cloud computing unit 2; and the computing unit 33 is connected with the training unit 31 and the extracting unit 32, and is used for computing a network security situation prediction result according to the extracted vulnerabilities and viruses and through an artificial intelligence information analysis model. The training unit 31 includes an extraction subunit, configured to extract data parameters of a preset vulnerability and a virus, respectively, to form a feature parameter set; the processing subunit is used for presetting various network security situation prediction results; and the training subunit is used for using the characteristic parameter set as input, using a preset network security situation prediction result as expected output, using a self-learning classification method for training, and using a self-learning classifier obtained by training as the artificial intelligence information analysis model. In addition, the artificial intelligence monitoring unit 3 is connected with a visualization unit 7, and the visualization unit 7 visually displays the generated network security situation prediction result in a tree diagram and time sequence diagram mode.
As shown in fig. 1, the protection unit 4 includes a processing unit 41, which is used to repair a bug and monitor, isolate and remove viruses; the early warning unit 42 is used for realizing local and/or remote alarm in a mode of informing the mobile terminal by using a flash lamp, a buzzer and a short message; and an export unit 43, configured to export the client storage data and perform encryption. The export unit 43 is connected with a watermark editing unit 5 which adds a user name, an IP and time as contents, the export unit 43 is connected with a cloud disk 6 through the watermark editing unit 5, the cloud disk 6 is provided with three security attributes of locking, read-only and read-write, and the security attributes of individuals/groups/all cloud disks can be set through a management background.
The working principle of the network safety system is as follows: the data acquisition unit 1 forms a detailed log according to the operation behaviors of a host and an object by timing, polling and/or specifying the acquisition rule of a real-time task, then the detailed log is transmitted to the cloud computing unit 2, a huge data computing processing program is decomposed into countless small programs through a network cloud, then the small programs are processed and analyzed through a system consisting of a plurality of servers to obtain results and are returned to the data analysis unit 21, the data are split, counted and analyzed, redundant data in the data to be analyzed are eliminated through the data elimination unit 22, the vulnerability and the virus of the data to be analyzed after being processed by the cloud computing unit 2 are extracted and extracted through the extraction unit 32, the computing unit 33 obtains a network security situation prediction result according to the vulnerability and the virus and through an artificial intelligent information analysis model of the training unit 31, and on one hand, the visualization unit 7 adopts a tree diagram and a time sequence diagram mode to predict the generated network security situation on the one hand The measured result is displayed visually, on the other hand, the processing unit 41 repairs the bug, monitors, isolates and clears the virus, and the early warning unit 42 realizes local and/or remote alarm by using a flash lamp, a buzzer and a short message notification mobile terminal; the export unit 43 exports and encrypts the client storage data, and realizes the safe transfer and effective authority management of the file.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are within the scope of the invention.
Claims (8)
1. A network security system based on cloud computing and artificial intelligence, comprising:
the data acquisition unit (1) is used for acquiring data to be analyzed;
the cloud computing unit (2) is connected with the data acquisition unit (1) and is used for processing data to be analyzed;
the artificial intelligence monitoring unit (3) is connected with the cloud computing unit (2) and used for comparing the processed data to be analyzed and judging to obtain a monitoring result;
and the protection unit (4) is connected with the artificial intelligence monitoring unit (3) and is used for acquiring a monitoring result and automatically performing coping actions of isolating viruses, notifying an alarm and uploading client storage data when the artificial intelligence monitoring unit is attacked by a network.
2. The cloud computing and artificial intelligence based network security system of claim 1, wherein the data collection unit (1) forms a detailed log of the operation behavior of the host and the object by timing, polling and/or specifying collection rules of real-time tasks, wherein the detailed log includes but is not limited to user name, IP, operation, resource, access type, time, authorization result, specific design new event summarization, risk event, report management, system maintenance, rule management, log retrieval.
3. A cloud computing and artificial intelligence based network security system according to claim 1, wherein the cloud computing unit (2) comprises:
the data analysis unit (21) is used for carrying out splitting, statistics and analysis operations on the data to be analyzed;
and the data clearing unit (22) is connected with the data analysis unit (21) and is used for clearing redundant data in the data to be analyzed.
4. A cloud computing and artificial intelligence based network security system according to claim 1, characterized in that the artificial intelligence monitoring unit (3) comprises:
the training unit (31) is used for training according to preset various bugs and viruses and preset network security situation prediction results to obtain an artificial intelligence information analysis model;
the extraction unit (32) is connected with the training unit (31) and is used for extracting bugs and viruses of the data to be analyzed after being processed by the cloud computing unit (2);
and the computing unit (33) is connected with the training unit (31) and the extracting unit (32) and is used for computing to obtain a network security situation prediction result according to the extracted vulnerabilities and viruses and through an artificial intelligence information analysis model.
5. A cloud computing and artificial intelligence based network security system according to claim 4, characterized in that the training unit (31) comprises:
the extraction subunit is used for respectively extracting data parameters of preset bugs and viruses to form a characteristic parameter set;
the processing subunit is used for presetting various network security situation prediction results;
and the training subunit is used for using the characteristic parameter set as input, using a preset network security situation prediction result as expected output, using a self-learning classification method for training, and using a self-learning classifier obtained by training as the artificial intelligence information analysis model.
6. The network safety system based on cloud computing and artificial intelligence as claimed in claim 4, wherein the artificial intelligence monitoring unit (3) is connected with a visualization unit (7), and the visualization unit (7) adopts a tree diagram and a time sequence diagram to visually display the generated network safety situation prediction result.
7. A cloud computing and artificial intelligence based network security system according to claim 1, wherein the protection unit (4) comprises:
the processing unit (41) is used for repairing the loophole and monitoring, isolating and clearing the virus;
the early warning unit (42) is used for realizing local and/or allopatric warning in a mode of informing the mobile terminal by using a flash lamp, a buzzer and a short message;
and the export unit (43) is used for exporting the client storage data and encrypting the client storage data.
8. The network security system based on cloud computing and artificial intelligence of claim 7 is characterized in that the export unit (43) is connected with a watermark editing unit (5) which adds user names, IP and time to contents, the export unit (43) is connected with a cloud disk (6) through the watermark editing unit (5), the cloud disk (6) is provided with three security attributes of locking, read-only and read-write, and the security attributes of individuals/groups/all cloud disks can be set through a management background.
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