CN108449366B - Key message infrastructure security based on artificial intelligence threatens intelligence analysis system - Google Patents

Key message infrastructure security based on artificial intelligence threatens intelligence analysis system Download PDF

Info

Publication number
CN108449366B
CN108449366B CN201810483232.5A CN201810483232A CN108449366B CN 108449366 B CN108449366 B CN 108449366B CN 201810483232 A CN201810483232 A CN 201810483232A CN 108449366 B CN108449366 B CN 108449366B
Authority
CN
China
Prior art keywords
information
class
indicate
data
cluster
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201810483232.5A
Other languages
Chinese (zh)
Other versions
CN108449366A (en
Inventor
谢铭
陈祖斌
翁小云
张鹏
袁勇
杭聪
马虹哲
黎新
黄俊杰
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Electric Power Research Institute of Guangxi Power Grid Co Ltd
Guangxi Power Grid Co Ltd
Original Assignee
Guangxi Power Grid Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Guangxi Power Grid Co Ltd filed Critical Guangxi Power Grid Co Ltd
Priority to CN201810483232.5A priority Critical patent/CN108449366B/en
Publication of CN108449366A publication Critical patent/CN108449366A/en
Application granted granted Critical
Publication of CN108449366B publication Critical patent/CN108449366B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • 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
    • H04L63/1416—Event detection, e.g. attack signature detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/23—Clustering techniques
    • G06F18/232—Non-hierarchical techniques
    • G06F18/2321—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions
    • G06F18/23213—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions with fixed number of clusters, e.g. K-means clustering
    • 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
    • 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
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/30—Network architectures or network communication protocols for network security for supporting lawful interception, monitoring or retaining of communications or communication related information
    • H04L63/302—Network architectures or network communication protocols for network security for supporting lawful interception, monitoring or retaining of communications or communication related information gathering intelligence information for situation awareness or reconnaissance

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Security & Cryptography (AREA)
  • General Engineering & Computer Science (AREA)
  • Computer Hardware Design (AREA)
  • Computing Systems (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Probability & Statistics with Applications (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Evolutionary Biology (AREA)
  • General Physics & Mathematics (AREA)
  • Technology Law (AREA)
  • Alarm Systems (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

Key message infrastructure security based on artificial intelligence threatens intelligence analysis system, including information acquisition module, information processing module, intelligent analysis module, manual analysis module and information display terminal, the information acquisition module forms for the security information on real-time collecting network and threatens information bank, the information processing module is used to carry out pretreatment to the threat information threatened in information bank and information data is classified to treated, the intelligent analysis module and manual analysis module are used to carry out comprehensive analysis to current security situation, the information display terminal is used to for the result that analysis obtains being shown, and it alarms when finding dangerous.The invention has the benefit that the threat information on real-time collecting network, and using data mining technology and artificial intelligence technology is handled in real time the threat information collected and depth analysis, to realize timely identification and early warning to attack, the safety of key message infrastructure ensure that.

Description

Key message infrastructure security based on artificial intelligence threatens intelligence analysis system
Technical field
The invention is related to key message infrastructure security detection field, and in particular to a kind of based on artificial intelligence Key message infrastructure security threatens intelligence analysis system.
Background technique
Great change, state secret, trade secret, secret protection face occur for Information Security Risk mechanism under big data environment Face significant challenge, traditional information security management normal form can not be in face of the prestige under severe form of security, big data environment Side of body intelligence analysis system comes into being, and to threatening, information progress is effective to be analyzed to carry out key message infrastructure security Defence, can analyze the invasion occurred, and effectively prejudged to future threat situation in time, and can help to assess potential Security risk instructs user to formulate effective security decision in turn, therefore, to threatening information effectively to be analyzed, believes key The security protection of breath infrastructure has great importance.
Threat information under big data environment often has that data volume is numerous, source is various and structure is complicated, because This, effectively clusters magnanimity threat data, and abstract data are carried out set grouping, is the weight for threatening the analysis of information Basis is wanted, the present invention provides a kind of key message infrastructure security threat intelligence analysis system based on artificial intelligence, to net Threat information on network is acquired in real time, is classified using clustering algorithm to the threat information collected, is then used Artificial intelligence technology, abnormal behaviour identification technology, Intrusion Detection Technique and Situation Forecast Technique to treated threaten information into Row depth analysis ensure that the peace of key message infrastructure to realize the timely identification and early warning to attack Entirely.
Summary of the invention
In view of the above-mentioned problems, the present invention is intended to provide a kind of key message infrastructure security based on artificial intelligence threatens Intelligence analysis system.
The purpose of the invention is achieved through the following technical solutions:
Key message infrastructure security threat intelligence analysis system based on artificial intelligence, including information acquisition module, Information processing module, intelligent analysis module, manual analysis module and information display terminal, the information acquisition module is for real-time The security information of the facilities such as mobile device, social networks, user access logs, sensor, voice communication, video is collected, is formed Information bank is threatened, the information processing module is used to carry out the threat information threatened in information bank pretreatment and to treated Information data is classified, the intelligent analysis module be used for according to threaten information classification results to current security situation into Row analyzes and predicts that potential risks, the manual analysis module analyze personnel according to the classification for threatening information by staff intelligence As a result comprehensive analysis is carried out to current key message infrastructure security situation with the analysis result of intelligent analysis module, it is described The result that intelligent analysis module and manual analysis module analysis obtain is shown by information display terminal, and in discovery to key The security presence of information infrastructure is alarmed when threatening.
The invention the utility model has the advantages that the present invention provides a kind of key message infrastructure security based on artificial intelligence Intelligence analysis system, the threat information on real-time collecting network are threatened, and uses data mining, artificial intelligence technology, abnormal row The threat information collected is handled in real time for technologies such as identification technology, Intrusion Detection Technique and Tendency Predictions and depth Analysis ensure that the safety of key message infrastructure to realize the timely identification and early warning to attack.
Detailed description of the invention
Innovation and creation are described further using attached drawing, but the embodiment in attached drawing does not constitute and appoints to the invention What is limited, for those of ordinary skill in the art, without creative efforts, can also be according to the following drawings Obtain other attached drawings.
Fig. 1 is schematic structural view of the invention；
Fig. 2 is the structural schematic diagram of information processing module and intelligent analysis module of the present invention.
Appended drawing reference:
Information acquisition module 1；Information processing module 2；Intelligent analysis module 3；Manual analysis module 4；Information display terminal 5；Information pretreatment unit 21；Classification of information unit 22；Suspicious actions recognition unit 31；Network invasion monitoring unit 32；Situation Forecast analysis unit 33.
Specific embodiment
The invention will be further described with the following Examples.
Referring to Fig. 1 and Fig. 2, the key message infrastructure security based on artificial intelligence of the present embodiment threatens intelligence analysis System, including information acquisition module 1, information processing module 2, intelligent analysis module 3, manual analysis module 4 and information display are eventually End 5, the information acquisition module 1 are logical for real-time collecting mobile device, social networks, user access logs, sensor, voice The security information of the facilities such as words, video forms and threatens information bank, and the information processing module 2 is used for in threat information bank Threat information carries out pretreatment and information data is classified to treated, and the intelligent analysis module 3 is used for according to threat The classification results of information are analyzed current security situation and are predicted that potential risks, the manual analysis module 4 pass through Staff intelligence is analyzed personnel and is believed according to the analysis result of the classification results and intelligent analysis module that threaten information current key It ceases infrastructure security situation and carries out comprehensive analysis, the information display terminal 5 is by intelligent analysis module 3 and manual analysis module The result that 4 analyses obtain is shown, and is alarmed when security presence of the discovery to key message infrastructure threatens.
This preferred embodiment provides a kind of key message infrastructure security threat intelligence analysis system based on artificial intelligence It unites, the threat information on real-time collecting network, and using data mining, artificial intelligence technology, abnormal behaviour identification technology, invasion The technologies such as detection technique and Tendency Prediction are handled in real time the threat information collected and depth analysis, thus realization pair The timely identification and early warning of attack, ensure that the safety of key message infrastructure.
Preferably, the information processing module 2 includes information pretreatment unit 21 and classification of information unit 22, the information Pretreatment unit 21 is used for the pre- place for threatening information to carry out data filtering, Supplementing Data and data deduplication in threat data library Reason operation, the classification of information unit 22 classify to pretreated threat information using possibility C means clustering algorithm Operation.
Preferably, the classification of information unit 22 is using possibility C means clustering algorithm to pretreated threat information Classify, the objective function of possibility C means clustering algorithm is improved, defining improved objective function is fnew, The then calculation formula of fnew are as follows:
In formula, uikIndicate the data x that FCM algorithm defineskBelong to the degree of membership of the i-th class, m indicates the mould that FCM algorithm uses Paste index parameter, and m > 1, gikIndicate data x defined in PCM algorithmkBelong to the probability of the i-th class, t indicates that PCM algorithm uses Fuzzy indicator parameter, and t > 1, ciIndicate that the cluster centre of the i-th class, C indicate that cluster classification number, n indicate sample number, caAnd cb Respectively indicate the cluster centre of a class and b class；
The degree of membership of a possibility that corresponding to C means clustering algorithm and the more new formula of cluster centre are as follows:
In formula, cpAnd ciRespectively indicate the cluster centre of pth class and the i-th class, uikIndicate the data x that FCM algorithm defineskBelong to In the degree of membership of the i-th class, uihIndicate data x in FCM algorithmhBelong to the degree of membership of the i-th class, m indicates that FCM algorithm uses fuzzy Index parameter, and m > 1, gikIndicate the data x that PCM algorithm defineskBelong to the probability of the i-th class, gihIndicate the number that PCM algorithm defines According to xhBelong to the probability of the i-th class, t indicates the fuzzy indicator parameter that PCM algorithm uses, and t > 1, C indicate cluster classification number, n table Show sample number.
This preferred embodiment improves the objective function of possibility C means clustering algorithm, overcomes clustering algorithm pair The more sensitive defect of noise, and make the clustering algorithm handle between class and class there are it is Chong Die the case where when it is not easy to make mistakes, In addition, the compact and separation degree for introducing data set of the objective function as penalty term, can obtain preferable cluster effect Fruit.
Preferably, the possibility C means clustering algorithm uses a kind of side that preferable clustering number is determined based on Information Granularity Method defines the Cluster Validity Index H of possibility C means clustering algorithm by the information degree of coupling and separating degreeCS, for determining The best cluster classification number of possibility C means clustering algorithm, then Cluster Validity Index HCSCalculation formula are as follows:
In formula, C indicates that cluster classification number, n indicate sample number, ciAnd ckThe cluster centre of the i-th class and kth class is respectively indicated,Indicate the cluster centre of sample set；
It successively chooses different cluster classification numbers to be clustered, HCSCorresponding C value is best cluster classification when minimum value Number.
This preferred embodiment combines clustering algorithm with Information Granularity analysis, and introduces the information degree of coupling and separating degree The Validity Index of clustering algorithm is calculated, so that it is determined that the preferable clustering number of clustering algorithm, can not only effectively obtain best Cluster numbers, and make the clustering algorithm can adapt to threaten this large-scale dataset of information cluster.
Preferably, intelligent analysis module 3 includes that suspicious actions recognition unit 31, network invasion monitoring unit 32 and situation are pre- Survey analytical unit 33, the suspicious actions recognition unit 31 be used for according to treated threaten information in network user it is current Behavior pattern is detected, and is compared with normal behaviour mode, to recognize whether suspicious actions, the network enters Detection unit 32 is invaded for according to threatening the classification results of information data to analyse whether there are intrusion behavior, the Tendency Prediction to divide Analysis unit 33 is according to suspicious actions recognition unit 31 and network invasion monitoring unit 32 and threatens the classification results of information to working as Preceding network safety situation is predicted.
This preferred embodiment is pre- from suspicious actions identification, network invasion monitoring and situation according to the cluster result of threat information It surveys three different aspects and the cluster result for threatening information is analyzed by artificial intelligence technology, more can comprehensively sentence The network security situation for breaking current, and judge that the safe condition of network provides help for subsequent manual analysis.
Finally it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than the present invention is protected The limitation of range is protected, although explaining in detail referring to preferred embodiment to the present invention, those skilled in the art are answered Work as understanding, it can be with modification or equivalent replacement of the technical solution of the present invention are made, without departing from the reality of technical solution of the present invention Matter and range.

Claims (3)

1. the key message infrastructure security based on artificial intelligence threatens intelligence analysis system, characterized in that received including information Collect module, information processing module, intelligent analysis module, manual analysis module and information display terminal, the information acquisition module For the security information in real-time collecting mobile device, social networks, user access logs, sensor, voice communication and video, It is formed and threatens information bank, the information processing module is used to carry out the threat information threatened in information bank pretreatment and to processing Information data afterwards is classified, and the intelligent analysis module is used for the classification results according to threat information to current safe shape Gesture is analyzed and is predicted that potential risks, the manual analysis module analyze personnel according to threat information by staff intelligence The analysis result of classification results and intelligent analysis module carries out comprehensive analysis to current key message infrastructure security situation, The result that intelligent analysis module and manual analysis module analysis obtain is shown by the information display terminal, and in discovery pair The security presence of key message infrastructure is alarmed when threatening, and the information processing module includes information pretreatment unit With classification of information unit, the information pretreatment unit is used to carry out data filtering, number to the threat information threatened in information bank According to the pretreatment operation of completion and data deduplication, the classification of information unit is using possibility C means clustering algorithm to pretreatment Threat information afterwards carries out sort operation, improves to the objective function of possibility C means clustering algorithm, defines improved Objective function is fnew, then fnewCalculation formula are as follows:
In formula, uikIndicate the data x that FCM algorithm defineskBelong to the degree of membership of the i-th class, m indicates the fuzzy finger that FCM algorithm uses Mark parameter, and m > 1, gikIndicate data x defined in PCM algorithmkBelong to the probability of the i-th class, t indicates the mould that PCM algorithm uses Paste index parameter, and t > 1, ciIndicate that the cluster centre of the i-th class, C indicate that cluster classification number, n indicate sample number, caAnd cbRespectively Indicate the cluster centre of a class and b class；
The degree of membership of a possibility that corresponding to C means clustering algorithm and the more new formula of cluster centre are as follows:
In formula, cpAnd ciRespectively indicate the cluster centre of pth class and the i-th class, uikIndicate the data x that FCM algorithm defineskBelong to i-th The degree of membership of class, uihIndicate data x in FCM algorithmhBelong to the degree of membership of the i-th class, m indicates the fuzzy indicator that FCM algorithm uses Parameter, and m > 1, gikIndicate the data x that PCM algorithm defineskBelong to the probability of the i-th class, gihIndicate the data x that PCM algorithm definesh Belong to the probability of the i-th class, t indicates the fuzzy indicator parameter that PCM algorithm uses, and t > 1, C indicate that cluster classification number, n indicate sample This number.
2. the key message infrastructure security according to claim 1 based on artificial intelligence threatens intelligence analysis system, It is characterized in that the possibility C means clustering algorithm uses a kind of method for determining preferable clustering number based on Information Granularity, pass through The information degree of coupling and separating degree define the Cluster Validity Index H of possibility C means clustering algorithmCS, for determining possibility C The best cluster classification number of means clustering algorithm, then Cluster Validity Index HCSCalculation formula are as follows:
In formula, C indicates that cluster classification number, n indicate sample number, ciAnd ckThe cluster centre of the i-th class and kth class is respectively indicated,Table Show the cluster centre of sample set；
It successively chooses different cluster classification numbers to be clustered, HCSCorresponding C value is best cluster classification number when minimum value.
3. the key message infrastructure security according to claim 2 based on artificial intelligence threatens intelligence analysis system, It is characterized in that intelligent analysis module includes suspicious actions recognition unit, network invasion monitoring unit and Tendency Prediction analytical unit, The suspicious actions recognition unit is used to threaten information to examine the current behavior mode of user in network according to treated It surveys, and is compared with normal behaviour mode, to recognize whether suspicious actions, the network invasion monitoring unit is used for Analyse whether that there are intrusion behavior, the Tendency Prediction analytical unit is according to suspicious row according to the classification results of threat information data For recognition unit and network invasion monitoring unit analysis result and threaten the classification results of information to current network security Situation is predicted.
CN201810483232.5A 2018-05-18 2018-05-18 Key message infrastructure security based on artificial intelligence threatens intelligence analysis system Active CN108449366B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201810483232.5A CN108449366B (en) 2018-05-18 2018-05-18 Key message infrastructure security based on artificial intelligence threatens intelligence analysis system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201810483232.5A CN108449366B (en) 2018-05-18 2018-05-18 Key message infrastructure security based on artificial intelligence threatens intelligence analysis system

Publications (2)

Publication Number Publication Date
CN108449366A CN108449366A (en) 2018-08-24
CN108449366B true CN108449366B (en) 2019-01-22

Family

ID=63204929

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201810483232.5A Active CN108449366B (en) 2018-05-18 2018-05-18 Key message infrastructure security based on artificial intelligence threatens intelligence analysis system

Country Status (1)

Country Link
CN (1) CN108449366B (en)

Families Citing this family (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109783823A (en) * 2019-03-07 2019-05-21 百度在线网络技术（北京）有限公司 Voice monitoring method, device, equipment and computer-readable medium
CN110334904B (en) * 2019-05-30 2023-03-03 北京理工大学 LightGBM-based key information infrastructure type unit attribution determination method
CN110674238B (en) * 2019-09-26 2022-11-04 四川科瑞软件有限责任公司 Toxicity prohibition information studying and judging system based on big data
CN111209564B (en) * 2020-01-03 2022-11-22 深信服科技股份有限公司 Cloud platform security state prediction method, device, equipment and storage medium
CN112201020B (en) * 2020-10-10 2022-01-18 合肥远康信息技术有限公司 Wisdom 110 networking synthesis alarm platform visual system
CN112202818B (en) * 2020-12-01 2021-03-09 南京中孚信息技术有限公司 Network traffic intrusion detection method and system fusing threat information
CN114143036A (en) * 2021-11-04 2022-03-04 湖南天云软件技术有限公司 Alarm method, device, equipment and computer storage medium

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105553957A (en) * 2015-12-09 2016-05-04 国家电网公司 Network safety situation awareness early-warning method and system based big data
CN106101252A (en) * 2016-07-01 2016-11-09 何钟柱 Information Security Risk guard system based on big data and trust computing
CN106713341A (en) * 2017-01-04 2017-05-24 成都四方伟业软件股份有限公司 Network security early-warning method and system based on big data

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102663530B (en) * 2012-05-25 2015-08-12 中国南方电网有限责任公司超高压输电公司 HVDC (High Voltage Direct Current) transmission system safe early warning and evaluating system

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105553957A (en) * 2015-12-09 2016-05-04 国家电网公司 Network safety situation awareness early-warning method and system based big data
CN106101252A (en) * 2016-07-01 2016-11-09 何钟柱 Information Security Risk guard system based on big data and trust computing
CN106713341A (en) * 2017-01-04 2017-05-24 成都四方伟业软件股份有限公司 Network security early-warning method and system based on big data

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
一种约束的改进可能性Ｃ均值聚类方法研究;肖振球等;《甘肃农业大学学报》;20161231;全文

Also Published As

Publication number Publication date
CN108449366A (en) 2018-08-24

Similar Documents

Publication Publication Date Title
CN108449366B (en) Key message infrastructure security based on artificial intelligence threatens intelligence analysis system
Liu et al. Research on intrusion detection based on particle swarm optimization in IoT
Goeschel Reducing false positives in intrusion detection systems using data-mining techniques utilizing support vector machines, decision trees, and naive Bayes for off-line analysis
CN106790256B (en) Active machine learning system for dangerous host supervision
CN103441982A (en) Intrusion alarm analyzing method based on relative entropy
CN101557327A (en) Intrusion detection method based on support vector machine (SVM)
CN118353702B (en) Network information safety protection system
Nadiammai et al. A comprehensive analysis and study in intrusion detection system using data mining techniques
CN114598551A (en) Information network security early warning system for dealing with continuous threat attack
Lam Detecting unauthorized network intrusion based on network traffic using behavior analysis techniques
Ganapathy et al. An intelligent system for intrusion detection using outlier detection
Yu et al. Network security monitoring method based on deep learning
Manandhar et al. Intrusion detection based on outlier detection method
Liao et al. Research on network intrusion detection method based on deep learning algorithm
CN109522715A (en) A kind of data fusion classification method and system towards safe and intelligent power grid
Das et al. Crime Pattern Detection Using Data Mining
Patond et al. Survey on data mining techniques for intrusion detection system
Sujatha et al. A proposal for analysis of crime based on socio–economic impact using data mining techniques
CN118573487B (en) Network anomaly detection method and system for detecting zero positive anomaly of isolated forest fusion
Huang et al. Research on network communication model and network security technology through big data
Udayakumar et al. Machine Learning Based Intrusion Detection System
Harsha et al. Machine Learning-based Oddity Detection of Smoke and Gas Sensor Data in a Large Gated Community
Deepa et al. Efficient intrusion detection system using random tree
Deny et al. ‘Neural networks and machine learning techniques for intrusion detection system
Yin et al. Research on Network Intrusion Detection Technology Based on Artificial Intelligence

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
TR01 Transfer of patent right
TR01 Transfer of patent right

Effective date of registration: 20210409

Address after: No. 6 Democracy Road, Xingning District, Nanning City, Guangxi Zhuang Autonomous Region, 530000

Patentee after: GUANGXI POWER GRID Co.,Ltd.

Patentee after: ELECTRIC POWER RESEARCH INSTITUTE, GUANGXI POWER GRID Co.,Ltd.

Address before: No. 6 Democracy Road, Xingning District, Nanning City, Guangxi Zhuang Autonomous Region, 530000

Patentee before: GUANGXI POWER GRID Co.,Ltd.