CN110083701A - A kind of cyberspace Mass disturbance early warning system based on average influence - Google Patents
A kind of cyberspace Mass disturbance early warning system based on average influence Download PDFInfo
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Abstract
A kind of cyberspace Mass disturbance early warning system based on average influence is claimed in the present invention, and wherein system includes acquisition module, preprocessing module, identification module, warning module.The present invention carries out more strategies to webpage information by web crawlers and crawls, then is standardized to the data crawled.Standardized data are identified using identification module, and result is input to warning module.Warning module realizes early warning according to preset warning index threshold value and exports visualization report.This system effectively solves existing being concerned only with event itself of pre-warning indexes system and has ignored the influence of the pairs of discrimination of patcicipant's gruop by the inside composition of analysis cyberspace Mass disturbance participant.
Description
Technical field
The invention belongs to information security fields, in particular to a kind of cyberspace group based on average influence
Body sexual behavior part early warning system.
Background technique
Nowadays, national security has not only included traditional national politics safety and military security, cyberspace safety
It is increasingly becoming one of the important composition of national strategy.For Logistics networks space safety, cyberspace sovereignty and country's peace are safeguarded
Entirely, public interests are protected the lawful rights and interests of citizens, legal persons and other organizations, and economic society informationization is promoted to develop in a healthy way,
Country has formulated a series of laws and regulations.The behavior for requiring any individuals and organizations that should be used for network in laws and regulations is negative
Duty.Sound internet laws and regulations are conducive to carry out cyberspace Mass disturbance itself to administer and to causing or push
The people of event calls to account.
It is widely available due to computer and smart phone, network have become the people understand information, expression of opinion,
The main channel of reaction problem.There is a large amount of converging information into cyberspace daily.Wherein there are part criminal or tissue
Premised on common purpose or interests, in Web Publishing or the not firm information disseminated.This leads to cyberspace Mass disturbance frequency
Hair.Cyberspace Mass disturbance, which takes place frequently, not only to be resulted in public resource and is wasted, also generation bad influence, is sent out economy
Exhibition, social harmony or even public safety are all a huge threats.Therefore, it finds to occur in cyberspace as early as possible latent
It is threatening, in time, accurately baneful influence can both avoided to cyberspace Mass disturbance progress early warning as far as possible, promoted economical
Development and social harmony can promote the efficiency of relevant departments' management of public affairs again, avoid the limitation manually supervised and disadvantage
End.
Current research work is mostly to carry out early warning according to burst word or the sensitive vocabulary being pre-created.Based on burst word
There may be a large amount of the phenomenon that judging by accident for early warning system.Burst word can only represent the word in certain time window access times it is unexpected on
It rises.This may be influenced by many situations.In some cases, the higher burst word of the temperature detected may by without threaten or it is low
It is generated in the event of threat, this needs that manual examination and verification is combined to can be only achieved good effect toward contact.Based on the pre- of sensitive vocabulary
Alert system needs artificial formulation and timing updates sensitive vocabulary, usually there is hysteresis quality.Netizen uses part in cyberspace
When word, new explanation may be assigned to partial words.It is usually incomplete when formulating which results in sensitive vocabularys, subsequent
Partial words can also have ambiguity problem when update.
Summary of the invention
Present invention seek to address that the above problem of the prior art.It proposes one kind and effectively solves existing pre-warning indexes system
It is concerned only with event itself and has ignored the cyberspace group based on average influence of the influence of the pairs of discrimination of patcicipant's gruop
Sexual behavior part early warning system.Technical scheme is as follows:
A kind of cyberspace Mass disturbance early warning system based on average influence comprising: acquisition module, pretreatment
Module, identification module, warning module；Wherein,
Acquisition module, for acquiring the web data including forum, microblogging, news website according to acquisition strategies；
Preprocessing module includes: content of text submodule, short chain in the content of text for crawling to acquisition module
It connects, expression and refer to that behavior accounts for the ratio of content of text total number.Then content of text is segmented, removes stop words, then
Content of text is marked into classification according to the sensitive vocabulary constructed in advance；User characteristics submodule, for being crawled to acquisition module
To the essential information of user information extract；Influence power submodule, for the base according to the extraction of user characteristics submodule
This information calculates influence power index of correlation；
Identification module includes: to be divided according to the disaggregated model pre-established the processed data of preprocessing module
Class, and each finger target value in classification results and cyberspace Mass disturbance pre-warning indexes system is input to warning module；
Warning module includes: the classification results and preset threshold value comparison by identification module, if exceeding threshold value,
It exports early warning result and visualization is reported.
Further, the acquisition module by it is pre-set crawl strategy to page end microblogging and mobile terminal microblogging into
Row crawls, and obtains the text data in microblogging, and crawling strategy includes stochastic model and custom model, and custom model includes that setting is adopted
The time range of collection, keyword, quantity, preserving type, the content for whether crawling user information and forwarding comment, stochastic model can
To be crawled at random according to User ID.
Further, the strategy that crawls being provided with is input to crawlers as configuration file by the acquisition module
In, crawler brings into operation until meeting stop condition, the data after the completion of acquiring, according to crawling strategy generating for preprocessing module
The file format that needs is directly stored in spare in database server, and acquisition module is the data source of early warning system, is passed through
Crawlers 24 hours uninterrupted acquisition data, guarantee the real-time of early warning system, or set centainly in crawling strategy
Acquisition delay, guarantees the stability of early warning system.
Further, the content of text submodule calculates short link, expression in every content of text first and refers to row
For the ratio for accounting for content of text total number, text-independent content that then acquisition module is crawled using Chinese words segmentation into
Row participle, removes stop words, content of text is marked classification further according to the sensitive vocabulary constructed in advance, sensitive vocabulary can be according to reality
Border needs to regularly update；
User characteristics submodule is responsible for handling the user information that acquisition module crawls, be crawled in processing
User information when, to same effectiveness repeated index carry out reduction；
Influence power submodule, be responsible for calculate measure network event influence power index of correlation, mainly include average influence,
User activity, cyberspace Mass disturbance and user's composition of general network event make a big difference, average influence
The difference of this composition, average influence calculation method can be embodied with user activity are as follows:
Wherein InfUiFor the influence power of isolated user, αiFor the weight of isolated user, m indicates to participate in the independence of network event
Number of users；
Average user liveness calculation method are as follows:
Wherein TwUiFor text-independent item number, RegiTimeUiFor isolated user registion time, βiFor the weight of isolated user.
Further, the pre-warning indexes system include: text-independent item number, comment number, forwarding number, participating user's number,
Average influence, certification user's ratio, paying customer's ratio, any one or more in user activity, part index number can
Strategy is crawled using other titles with same effectiveness according to different.
Further, the identification module further include: the network in database is utilized according to the disaggregated model pre-established
Network space group body sexual behavior part disaggregated model is trained in space Mass disturbance library, is classified according to the cyberspace Mass disturbance
Model by the processed information of preprocessing module to being classified.
It advantages of the present invention and has the beneficial effect that:
Cyberspace Mass disturbance early warning system provided by the present invention based on average influence, is climbed according to different
It takes strategy to crawl web data by acquisition module, is standardized collected data using preprocessing module, then will mark
The data of standardization structure are input to identification module and calculate and result is input to warning module, and last warning module according to setting in advance
Fixed warning index threshold value realizes warning function.The present invention is acquired web data using web crawlers, effectively increases number
According to crawling speed, and a variety of strategies can be set to cope with the part webpage more hard to climb taken.The present invention sufficiently analyzes network sky
Between Mass disturbance and push event development participant feature, improve the calculation method of event influence power, and user be added
The one kind of liveness, the certification indexs such as user's ratio and paying customer's ratio as evaluation event authenticity, efficiently solves thing
Influence of the part influence power to event indicates the not high disadvantage of excessively unilateral and discrimination, while reducing as far as possible to artificial judgment
Dependence.
Detailed description of the invention
Fig. 1 is that the present invention provides cyberspace Mass disturbance early warning system of the preferred embodiment based on average influence
System construction drawing；
Fig. 2 is the system flow chart of the cyberspace Mass disturbance early warning system based on average influence；
Fig. 3 is the cyberspace Mass disturbance early warning system pre-warning indexes system figure based on average influence.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, detailed
Carefully describe.Described embodiment is only a part of the embodiments of the present invention.
The technical solution that the present invention solves above-mentioned technical problem is:
The present invention is based on the cyberspace Mass disturbance early warning systems of average influence can set acquisition module interface
It is set to and crawls microblogging.Monitor the hot topic and network event in domestic microblogging, concern is domestic on-line off-line following.
As shown in Figure 1.A kind of cyberspace Mass disturbance early warning system based on average influence is (hereinafter referred to as: pre-
Alert system), comprising: acquisition module, preprocessing module, identification module, warning module；The whole flow process of early warning system such as Fig. 2.
Wherein, acquisition module, the data being mainly responsible in acquisition microblogging webpage, are the pending datas of entire early warning system
Module input module.The module crawls page end microblogging and mobile terminal microblogging by the pre-set strategy that crawls,
Obtain the text data in microblogging.Crawling strategy includes stochastic model and custom model.Custom model include setting acquisition when
Between range, keyword, quantity, preserving type, the content etc. for whether crawling user information, forwarding comment.Stochastic model can root
It is crawled at random according to User ID.The strategy that crawls being provided with is input in crawlers as configuration file, crawler opens
Begin run up to meet stop condition (as practical microblog number amount less than presetting maximum value, time range without new microblogging
Etc.).The file format or directly deposit that data after the completion of acquisition can be needed according to strategy generating is crawled for preprocessing module
Enter spare in database server.Acquisition module is the data source of early warning system, is uninterruptedly obtained by crawlers 24 hours
Access evidence, guarantees the real-time of early warning system, and certain acquisition delay can also be set in crawling strategy, guarantees early warning system
Stability.
Preprocessing module is responsible for for the data that acquisition module obtains being standardized.The module can will be standardized
Data save as the file format of identification module needs or are stored directly in spare in database server.Preprocessing module can mention
The speed of service of high identification module is stablized so that entire early warning system is more efficient.
Preprocessing module specifically includes:
Content of text submodule is first responsible for calculating short link, expression in every content of text and refers to that behavior accounts for text
The ratio of content total number.Then the text-independent content that acquisition module crawls is segmented using Chinese words segmentation,
Stop words is removed, content of text is marked into classification further according to the sensitive vocabulary constructed in advance.Sensitive vocabulary can be according to actual needs
It regularly updates.
User characteristics submodule is responsible for handling the user information that acquisition module crawls.It, can by taking microblogging as an example
With registion time, microblog number, the number of fans etc. for extracting user.Different webpages is likely to occur different extracting modes.It is handling
When the user information crawled, reduction is carried out to the repeated index with same effectiveness.
Influence power submodule is responsible for calculating the influence power index of correlation for measuring network event.Mainly include average influence,
User activity, other parts index can be directly acquired without calculating (such as microblog number in network event).Cyberspace
Mass disturbance and user's composition of general network event make a big difference.Average influence and user activity can embody this
The difference of kind composition, helps to improve the accuracy rate of identification module.
Average influence calculation method are as follows:
Wherein InfUiFor the influence power of isolated user, αiFor the weight of isolated user
Average user liveness calculation method are as follows:
Wherein TwUiFor text-independent item number, RegiTimeUiFor isolated user registion time, βiFor the weight of isolated user.
Identification module, is responsible for that treated that data carry out identification classification to estimated processing module.First to partial data into
Row normalization helps to improve the convergence rate of disaggregated model and promotes the timeliness of early warning system.Then according to building in advance
Disaggregated model, classify to processed data.If recognition result is not develop into cyberspace Mass disturbance
General network event (such as certain competitive sports is won the championship), then do not need to refer to warning module input recognition result with each early warning again
Target value.This facilitates the efficiency for promoting early warning system, prevents from occupying resource by the general network event without early warning.
Warning module, be responsible in time analysis with processing identification module classification results, and with preset warning index
Threshold value be compared, if exceed threshold value, output early warning result and visualization report.Pre-warning indexes system includes: independent text
This number, comment number, forwarding number, participating user's number, average influence, certification user's ratio, paying customer's ratio, user are active
It is any one or more in degree.Part index number can crawl strategy using other titles with same effectiveness according to different.
Cyberspace Mass disturbance pre-warning indexes system is as shown in figure 3, each index is described as follows by taking microblogging as an example:
(1) microblog number: the number of microblog number can embody the temperature of network event.
(2) comment on number: comment on number number can embody the discussion temperature of event
(3) forwarding number: forwarding number more multilist is bright to have more users to participate in network event, and continues diffusion downwards.
(4) independent participating user's number: it can really react that how many user participates in the discussion of network event.
(5) user's composition of cyberspace Mass disturbance and general network event can average influence: be embodied
It is different.
(6) user activity: having same function with average influence, can embody cyberspace Mass disturbance with
The difference of user's composition of general network event.
(7) authenticate user's ratio: user's composition in preferable embodiment event, whether side reflects in network event has
The participation of network navy.
(8) paying customer's ratio: there is same function with certification user's ratio, the user group in preferable embodiment event
At side reflects the participation for whether having network navy in network event.
The above embodiment is interpreted as being merely to illustrate the present invention rather than limit the scope of the invention.?
After the content for having read record of the invention, technical staff can be made various changes or modifications the present invention, these equivalent changes
Change and modification equally falls into the scope of the claims in the present invention.
Claims (6)
1. a kind of cyberspace Mass disturbance early warning system based on average influence characterized by comprising acquisition mould
Block, preprocessing module, identification module, warning module；Wherein,
Acquisition module, for acquiring the web data including forum, microblogging, news website according to acquisition strategies；
Preprocessing module includes: content of text submodule, short link, table in the content of text for crawling to acquisition module
It feelings and refers to that behavior accounts for the ratio of content of text total number, then content of text is segmented, stop words is removed, further according to pre-
Content of text is marked classification by the sensitive vocabulary first constructed；User characteristics submodule, the use for being crawled to acquisition module
The essential information of family information extracts；Influence power submodule, for the essential information according to the extraction of user characteristics submodule
Calculate influence power index of correlation；
Identification module includes: the disaggregated model that basis pre-establishes, and is classified to the processed data of preprocessing module, and
Each finger target value in classification results and cyberspace Mass disturbance pre-warning indexes system is input to warning module；
Warning module includes: the classification results and preset threshold value comparison by identification module, if exceeding threshold value, output
Early warning result and visualization are reported.
2. a kind of cyberspace Mass disturbance early warning system based on average influence according to claim 1, special
Sign is that the acquisition module crawls page end microblogging and mobile terminal microblogging by the pre-set strategy that crawls, and obtains
The text data in microblogging is obtained, crawling strategy includes stochastic model and custom model, and custom model includes the time of setting acquisition
Range, keyword, quantity, preserving type, whether crawl user information and forwarding comment content, stochastic model can according to
Family ID is crawled at random.
3. a kind of cyberspace Mass disturbance early warning system based on average influence according to claim 2, special
Sign is that the strategy that crawls being provided with is input in crawlers by the acquisition module as configuration file, and crawler starts
It runs up to and meets stop condition, the data after the completion of acquiring, according to the file for crawling strategy generating and being needed for preprocessing module
Format is directly stored in spare in database server, and acquisition module is the data source of early warning system, passes through crawlers 24
Hour uninterrupted acquisition data, guarantee the real-time of early warning system, or certain acquisition delay is set in crawling strategy, protect
Demonstrate,prove the stability of early warning system.
4. a kind of cyberspace Mass disturbance early warning system based on average influence described in one of -3 according to claim 1
System, which is characterized in that the content of text submodule calculates short link, expression in every content of text first and refers to behavior
The ratio of content of text total number is accounted for, then the text-independent content that acquisition module crawls is carried out using Chinese words segmentation
Participle removes stop words, content of text is marked classification further according to the sensitive vocabulary constructed in advance, sensitive vocabulary can be according to reality
It needs to regularly update；
User characteristics submodule is responsible for handling the user information that acquisition module crawls, in the use that processing crawls
When the information of family, reduction is carried out to the repeated index with same effectiveness；
Influence power submodule is responsible for calculating the influence power index of correlation for measuring network event, mainly includes average influence, user
Liveness, cyberspace Mass disturbance and user's composition of general network event make a big difference, average influence and use
Family liveness can embody the difference of this composition, average influence calculation method are as follows:
Wherein InfUiFor the influence power of isolated user, αiFor the weight of isolated user；M indicates to participate in the isolated user of network event
Quantity；
Average user liveness calculation method are as follows:
Wherein TwUiFor text-independent item number, RegiTimeUiFor isolated user registion time, βiFor the weight of isolated user.
5. a kind of cyberspace Mass disturbance early warning system based on average influence described in one of -3 according to claim 1
System, which is characterized in that the pre-warning indexes system includes: text-independent item number, comment number, forwarding number, participating user's number, is averaged
Influence power, certification user's ratio, paying customer's ratio, any one or more in user activity, part index number can basis
Different crawls strategy using other titles with same effectiveness.
6. a kind of cyberspace Mass disturbance early warning system based on average influence according to claim 5, special
Sign is, the identification module further include: utilizes the cyberspace group in database according to the disaggregated model pre-established
Event base train network space group body sexual behavior part disaggregated model, according to the cyberspace Mass disturbance disaggregated model to by
The processed information of preprocessing module is classified.
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