CN110032869A - A kind of cloud computing protection early warning system based on big data - Google Patents

A kind of cloud computing protection early warning system based on big data Download PDF

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CN110032869A
CN110032869A CN201910315337.4A CN201910315337A CN110032869A CN 110032869 A CN110032869 A CN 110032869A CN 201910315337 A CN201910315337 A CN 201910315337A CN 110032869 A CN110032869 A CN 110032869A
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viroid
module
grade
analysis
enlivens
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CN110032869B (en
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谭道军
杨杰
尹向东
刘小兵
涂凤娇
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Hunan University of Science and Engineering
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/50Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
    • G06F21/55Detecting local intrusion or implementing counter-measures
    • G06F21/56Computer malware detection or handling, e.g. anti-virus arrangements
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/50Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
    • G06F21/55Detecting local intrusion or implementing counter-measures
    • G06F21/56Computer malware detection or handling, e.g. anti-virus arrangements
    • G06F21/561Virus type analysis

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Abstract

Early warning system, including defence acquisition module, data analysis module, analysis and processing module, database, scheme recording module, information sharing module, assessment of risks module and display module are protected in the cloud computing based on big data that the invention discloses a kind of;The present invention is to analyze according to the formulation to each viroid to obtain the different Virus Types for enlivening grade, and each viroid and its solution corresponding to grade are enlivened by first and is transferred to staff together, and it updates, the solution increased is directed into again in defence acquisition module, and second enlivens each viroid corresponding to grade after risk assessment operates, the first hazard class and the second hazard class that will acquire again are respectively processed, and third enlivens each viroid corresponding to grade directly by analysis and processing module, assessment of risks module transfer is to display module, the active division of all kinds of intrusive viruses is combined with danger division, to obtain detailed-oriented processing scheme, greatly improve protection early warning effect.

Description

A kind of cloud computing protection early warning system based on big data
Technical field
The present invention relates to cloud computings to protect early warning technology field, and early warning is protected in specially a kind of cloud computing based on big data System.
Background technique
Cloud computing is increase, use and interactive mode based on internet related service, is often related to mentioning according to internet For the resource of dynamic easily extension and often virtualization.It or distributed computing, parallel computation, effectiveness calculating, network storage, The product of the traditional computers such as virtualization, load balancing and hot-standby redundancy and network technical development fusion.
And now cloud computing mode be but faced with the attack of virus, and with the development of extensive system for cloud computing, disease The variation and propagation of poison also become abnormal rapid.And in existing cloud computing protection early warning system, it is difficult to for the work of virus Jump situation easily causes to defend link quilt to take preparatory control measure because the Different Variation form of similar virus occurs It breaks through, leverages the safe operation of system for cloud computing;The degree of danger sufficiently according to virus is difficult to simultaneously to be directed to make Change scheme causes to defend link collapse, leverages cloud computing to avoid the emergent explosion type invasion phenomenon of virus The protection pre-alerting ability of network.
In order to solve drawbacks described above, a kind of technical solution is now provided.
Summary of the invention
The purpose of the present invention is to provide a kind of, and early warning system is protected in the cloud computing based on big data.
The technical problems to be solved by the invention are as follows:
(1) how according to formulation analysis situation is enlivened obtain each virus, and update accordingly gradually, increases defence number According to, targetedly to be resisted scheme, avoid because the Different Variation form of similar virus occur due to cause defend link dashed forward It is broken, leverage the safe operation of system for cloud computing;
(2) how by a kind of effective mode, to analyze the potential danger source in each virus, and to the disease of different hazard class Poison carries out adaptive processes, causes to defend link collapse, significantly shadow to avoid the emergent explosion type invasion phenomenon of virus The protection pre-alerting ability of system for cloud computing is rung.
The purpose of the present invention can be achieved through the following technical solutions:
A kind of cloud computing protection early warning system based on big data, including defence acquisition module, data analysis module, analysis processing Module, database, scheme recording module, information sharing module, assessment of risks module and display module;
The defence acquisition module is used to prevent the invasion of each viroid, and acquires the exclusive letter of all kinds of intrusive viruses in real time Breath, and proprietary information includes survival duration, survival number and number of times of attack, and Virus Type can be distinguished according to prefix, such as: The prefix of system virus is Win32, PE, Win95, W32 or W95 etc.;The prefix of worm-type virus is Worm;The prefix of script virus For Script, VBS or JS etc.;And duration of surviving, survival number and number of times of attack can be come in fact according to firewall or gateway etc. When obtain, and proprietary information is transmitted to data analysis module;The data analysis module is after receiving proprietary information, to it In survival duration carry out formulation analysis operation together with number of times of attack, and will acquire first enlivens grade, second active Grade and third enliven grade and are transmitted to analysis and processing module;
The analysis and processing module enlivens each viroid corresponding to grade for first and is transmitted to database, and extracts in database Defense schemes corresponding with the viroid are transmitted to defence acquisition module, and then can enliven according to first all kinds of corresponding to grade Virus makes the update of adaptability, increases automatically, sufficiently to cater to actual defence demand, also by the viroid and its relatively The defense schemes answered are transmitted to information sharing module together, and defense schemes are laggard via search, the confirmation of scheme recording module Row typing, and can be according to the mode of information butt joint between scheme recording module and each website, and pass through the search viroid keyword Or the mode of prefix, to get defense schemes corresponding with the viroid in each website, then after confirming via staff Carry out typing;To be electrically connected between the information sharing module and the mobile phone of staff, and by the Virus Type received and Its corresponding defense schemes is shown, staff is enabled timely to recognize more active Virus Type, with And whether applicable defense schemes are reasonable, play positive effect to protection early warning effect is improved;
The analysis and processing module also enlivens each viroid corresponding to grade for second and is transmitted to assessment of risks module;The danger Dangerous evaluation module receive second enliven each viroid corresponding to grade after, from defence acquisition module in transfer and the viroid Corresponding survival number and number of times of attack, and corresponding to the first hazard class that carries out risk assessment operation, while will acquire Each viroid be transmitted to information sharing module, and each viroid corresponding to the second hazard class is transmitted to display mould Block;Third is also enlivened each viroid corresponding to grade through assessment of risks module transfer to showing mould by the analysis and processing module Block adequately to recognize potentially dangerous virus, and may be used also so that staff is in medium active Virus Type In addition the viral and less active virus without potential danger is sent to display module together, so as to staff's progress Record viewing, analysis verification etc., help to improve protection early warning effect.
Further, the concrete operation step of the formulation analysis are as follows:
S1: getting all kinds of viral survival durations in the every time in a period, and be demarcated as Xij, i=1...n, j =1...m, and as j=1, Xi1 is expressed as the first kind viral survival duration in the every time in a period;
S2: first according to formula, j=1...m, each viroid in every time to acquire a period is average Survival duration, and as j=1, T1 is expressed as the first viroid Average Survival duration in the every time in a period, then According to formula, j=1...m, all kinds of viral survivals in every time to acquire a period Duration discrete value, and as j=1, it is discrete that R1 is expressed as the first kind viral survival duration in the every time in a period Value;
S3: the merging of Q, W collection is first set separately according to Tj, Rj and marks survival duration coefficient Dj accordingly, and Q, W are gathered Lap be demarcated as b and the Q unitary part gathered be demarcated as a and the W unitary part gathered is demarcated as c, then by Tj, Rj are right by Tj or Rj institute when meeting Tj and being less than or equal to r more than or equal to t, Rj respectively compared with respective preset value t, r Each viroid answered is placed in b and Dj is assigned a value of B, big less than t, Rj greater than r and Tj more than or equal to t, Rj when meeting Tj When r, each viroid corresponding to Tj or Rj is placed in c and Dj is assigned a value of C, is less than or equal to when meeting Tj less than t, Rj When r, each viroid corresponding to Tj or Rj is placed in a and by Dj assignment A, and B is greater than C and is greater than A;
S4: getting each virus-like attacks number in the every time in a period, and be demarcated as Yij, i=1...n, j =1...m, and as j=1, Yi1 is expressed as the first virus-like attacks number in the every time in a period;
S5: first according to formula, j=1...m, each virus-like attacks in every time to acquire a period are total Number, and as j=1, E1 is expressed as the sum of the first virus-like attacks in the every time in a period, and is demarcated as Coefficient Fj is attacked, then Ej is compared with preset range e, it, will be equal with the Fj of each viroid corresponding to Ej when Ej is located in e It is assigned a value of q, when Ej is more than or equal to e, will be assigned a value of w with the Fj of each viroid corresponding to Ej, when Ej is less than or equal to e, It will be assigned a value of s with the Fj of each viroid corresponding to Ej, and w is greater than q and is greater than s, Ej and Tj, Rj are corresponded;
Wherein, a period can be defined as one month, and every time can be defined as every 84 hours;
The data analysis module is when getting Xij and Tj, Rj and Yij and Ej, by the survival duration coefficient corresponding to it Dj, attack coefficient Fj carry out weight distribution compared to the influence accounting of viral activity, and successively will be corresponding to Dj, Fj distribution Weighted value k, h, and k is greater than h, k+h=1, while according to formula, j=1...m, to acquire period Each viroid active degree in every time, and Gj is compared with preset range g, it, will be right with Gj institute when Gj is located in g Each viroid answered generates second and enlivens grade, when Gj is more than or equal to g, enlivens generating second with each viroid corresponding to Gj Grade enlivens grade for third is generated with each viroid corresponding to Gj when Gj is less than or equal to g.
Further, the concrete operation step of the risk assessment operation are as follows:
U1: getting all kinds of viral survival numbers and number of times of attack in every section time in a stage, and demarcates one accordingly Each virus-like attacks success rate Pij, i=1...n, j=1...m in every section time in a stage, and as j=1, Pi1 is indicated For the first virus-like attacks success rate in every section time in a stage;
U2: first according to formula, i=1...n, come acquire each virus-like attacks in a stage at Power coefficient, and as i=1, L1 is expressed as the first virus-like attacks success rate coefficient in a stage, then by Li and presets Value f, andCompared with preset value d, when Li be less than or equal to f,It, will be right with Li institute when more than or equal to d Each viroid answered generates the first hazard class, and each viroid corresponding to other and Li generates the second hazard class;
Wherein, a period can be defined as one month, and every time can be defined as every 84 hours.
Beneficial effects of the present invention:
The present invention is to enliven the Virus Type of grade according to the formulation analysis to each viroid to obtain difference, and first is enlivened Each viroid corresponding to grade and its solution are transferred to staff together, and update, the solution that increases imports again Into defence acquisition module, and second enlivens each viroid corresponding to grade after risk assessment operates, will acquire first Each viroid corresponding to hazard class is transmitted to information sharing module, and each viroid corresponding to the second hazard class is equal It is transmitted to display module, and third is enlivened each viroid corresponding to grade and is directly passed by analysis and processing module, assessment of risks module Display module is transported to, i.e., is combined the active division of all kinds of intrusive viruses with danger division, to obtain detailed-oriented processing side Case greatly improves protection early warning effect;
1. the present invention is first to acquire the proprietary information of all kinds of intrusive viruses in real time by defence acquisition module, and transmit it to number According to analysis module, and data analysis module is after receiving proprietary information, to survival duration therein together with number of times of attack into Row formulation analysis operates, and in formulating analysis operation, by the regional ensembleization analysis of all kinds of viral survival durations and respectively The normalized analysis of virus-like attacks number combines, and assigns to the survival duration coefficient Dj and attack coefficient Fj that respectively mark Value, then each viroid active degree and its corresponding each first that enlivens grade, and will acquire are obtained according to weight distribution It enlivens grade, second enliven grade and third enlivens grade and is transmitted to analysis and processing module, and analysis and processing module enlivens grade for first Corresponding each viroid is transmitted to database, and extracts defense schemes corresponding with the viroid in database and be transmitted to Defend acquisition module, so can according to first enliven each viroid corresponding to grade from the dynamic update for making adaptability, increase, Sufficiently to cater to actual defence demand, the viroid and its corresponding defense schemes are also transmitted to information sharing mould together Block, and by information sharing module by the Virus Type received and its corresponding defense schemes in the mobile phone of staff It shows, staff is enabled timely to recognize that more active Virus Type, and applicable defense schemes are It is no reasonable, positive effect is played to protection early warning effect is improved, effectively avoids the Different Variation form because of similar virus Occur and cause that link is defendd to be broken, leverages the safe operation of system for cloud computing;
2. the analysis and processing module in the present invention also enlivens each viroid corresponding to grade for second and is transmitted to assessment of risks mould Block, and assessment of risks module will transfer survival number corresponding with the viroid and number of times of attack from defence acquisition module, And carry out risk assessment operation, and in risk assessment operation, by the success attack rate coefficient of each viroid and maximum attack at Power combines, and to obtain each hazard class, and each viroid corresponding to the first hazard class that will acquire is transmitted to information Sharing module, and each viroid corresponding to the second hazard class is transmitted to display module, while analysis and processing module is also Third is enlivened into each viroid corresponding to grade through assessment of risks module transfer to display module, so that staff is medium In active Virus Type, adequately to recognize potentially dangerous virus, and will also can not in addition have potential danger It is viral be sent to display module together with less active virus, so that staff carries out record viewing, analysis is verified etc., Protection early warning effect is helped to improve, causes to defend link collapse to avoid the emergent explosion type invasion phenomenon of virus, Leverage the protection pre-alerting ability of system for cloud computing.
Detailed description of the invention
In order to facilitate the understanding of those skilled in the art, the present invention will be further described below with reference to the drawings.
Fig. 1 is system block diagram of the invention.
Specific embodiment
As shown in Figure 1, early warning system, including defence acquisition module, data point are protected in a kind of cloud computing based on big data Analyse module, analysis and processing module, database, scheme recording module, information sharing module, assessment of risks module and display module;
Defence acquisition module is used to prevent the invasion of each viroid, and acquires the proprietary information of all kinds of intrusive viruses in real time, and Proprietary information includes survival duration, survival number and number of times of attack, and Virus Type can be distinguished according to prefix, such as: system The prefix of virus is Win32, PE, Win95, W32 or W95 etc.;The prefix of worm-type virus is Worm;The prefix of script virus is Script, VBS or JS etc.;And duration of surviving, survival number and number of times of attack can be come in real time according to firewall or gateway etc. It obtains, and proprietary information is transmitted to data analysis module;Data analysis module is deposited after receiving proprietary information to therein Duration living carries out formulation analysis with number of times of attack together with and operates, and will acquire first enlivens grade, second enlivens grade and the Three, which enliven grade, is transmitted to analysis and processing module;
Analysis and processing module enlivens each viroid corresponding to grade for first and is transmitted to database, and extracts in database and be somebody's turn to do The corresponding defense schemes of viroid are transmitted to defence acquisition module, and then can enliven each viroid corresponding to grade according to first Automatically it makes the update of adaptability, increase, sufficiently to cater to actual defence demand, also by the viroid and its corresponding Defense schemes are transmitted to information sharing module together, and defense schemes after the search of scheme recording module, confirmation via being recorded Enter, and can be according to the mode of information butt joint between scheme recording module and each website, and passes through the search viroid keyword or preceding The mode sewed carries out to get defense schemes corresponding with the viroid in each website, then after confirming via staff Typing;To be electrically connected between information sharing module and the mobile phone of staff, and by the Virus Type received and its corresponding Defense schemes show, enable staff timely to recognize more active Virus Type, and be applicable in Whether defense schemes are reasonable, play positive effect to protection early warning effect is improved;
Analysis and processing module also enlivens each viroid corresponding to grade for second and is transmitted to assessment of risks module;Assessment of risks mould Block receive second enliven each viroid corresponding to grade after, from defence acquisition module in transfer it is corresponding with the viroid Survival number and number of times of attack, and all kinds of diseases corresponding to the first hazard class that carries out risk assessment operation, while will acquire Poison is transmitted to information sharing module, and each viroid corresponding to the second hazard class is transmitted to display module;Analysis Third is also enlivened each viroid corresponding to grade through assessment of risks module transfer to display module, to work by processing module Personnel are in medium active Virus Type, adequately to recognize potentially dangerous virus, and will in addition can not also have The viral and less active virus being potentially dangerous is sent to display module together, so as to staff carry out record viewing, Analysis verification etc. helps to improve protection early warning effect.
Further, the concrete operation step of analysis is formulated are as follows:
S1: getting all kinds of viral survival durations in the every time in a period, and be demarcated as Xij, i=1...n, j =1...m, and as j=1, Xi1 is expressed as the first kind viral survival duration in the every time in a period;
S2: first according to formula, j=1...m, each viroid in every time to acquire a period is average Survival duration, and as j=1, T1 is expressed as the first viroid Average Survival duration in the every time in a period, then According to formula, j=1...m, all kinds of viral survivals in every time to acquire a period Duration discrete value, and as j=1, it is discrete that R1 is expressed as the first kind viral survival duration in the every time in a period Value;
S3: the merging of Q, W collection is first set separately according to Tj, Rj and marks survival duration coefficient Dj accordingly, and Q, W are gathered Lap be demarcated as b and the Q unitary part gathered be demarcated as a and the W unitary part gathered is demarcated as c, then by Tj, Rj are right by Tj or Rj institute when meeting Tj and being less than or equal to r more than or equal to t, Rj respectively compared with respective preset value t, r Each viroid answered is placed in b and Dj is assigned a value of B, big less than t, Rj greater than r and Tj more than or equal to t, Rj when meeting Tj When r, each viroid corresponding to Tj or Rj is placed in c and Dj is assigned a value of C, is less than or equal to when meeting Tj less than t, Rj When r, each viroid corresponding to Tj or Rj is placed in a and by Dj assignment A, and B is greater than C and is greater than A;
S4: getting each virus-like attacks number in the every time in a period, and be demarcated as Yij, i=1...n, j =1...m, and as j=1, Yi1 is expressed as the first virus-like attacks number in the every time in a period;
S5: first according to formula, j=1...m, each virus-like attacks in every time to acquire a period are total Number, and as j=1, E1 is expressed as the sum of the first virus-like attacks in the every time in a period, and is demarcated as Coefficient Fj is attacked, then Ej is compared with preset range e, it, will be equal with the Fj of each viroid corresponding to Ej when Ej is located in e It is assigned a value of q, when Ej is more than or equal to e, will be assigned a value of w with the Fj of each viroid corresponding to Ej, when Ej is less than or equal to e, It will be assigned a value of s with the Fj of each viroid corresponding to Ej, and w is greater than q and is greater than s, Ej and Tj, Rj are corresponded;
Wherein, a period can be defined as one month, and every time can be defined as every 84 hours;
Data analysis module when getting Xij and Tj, Rj and Yij and Ej, by corresponding to it survival duration coefficient Dj, The influence accounting that coefficient Fj is attacked compared to viral activity carries out weight distribution, and power successively that Dj, Fj distribution is corresponding Weight values k, h, and k is greater than h, k+h=1, while according to formula, j=1...m, to acquire the every of period Each viroid active degree in the section time, and Gj is compared with preset range g, when Gj is located in g, will with corresponding to Gj Each viroid generate and second enliven grade, when Gj is more than or equal to g, second will be generated with each viroid corresponding to Gj and enlivened Grade enlivens grade for third is generated with each viroid corresponding to Gj when Gj is less than or equal to g.
Further, the concrete operation step of risk assessment operation are as follows:
U1: getting all kinds of viral survival numbers and number of times of attack in every section time in a stage, and demarcates one accordingly Each virus-like attacks success rate Pij, i=1...n, j=1...m in every section time in a stage, and as j=1, Pi1 is indicated For the first virus-like attacks success rate in every section time in a stage;
U2: first according to formula, i=1...n, come acquire each virus-like attacks in a stage at Power coefficient, and as i=1, L1 is expressed as the first virus-like attacks success rate coefficient in a stage, then by Li and presets Value f, andCompared with preset value d, when Li be less than or equal to f,It, will be right with Li institute when more than or equal to d Each viroid answered generates the first hazard class, and each viroid corresponding to other and Li generates the second hazard class;
Wherein, a period can be defined as one month, and every time can be defined as every 84 hours.
A kind of cloud computing protection early warning system based on big data, during the work time, first by defence acquisition module real When acquire the proprietary information of all kinds of intrusive viruses, and transmit it to data analysis module, and data analysis module is receiving After proprietary information, formulation analysis operation is carried out together with number of times of attack to survival duration therein, and in formulation analysis behaviour In work, the regional ensembleization of all kinds of viral survival durations is analyzed and is combined with the normalized analysis of each virus-like attacks number, And each viroid is active to be shown with coefficient Fj assignment, then foundation weight distribution is attacked to the survival duration coefficient Dj respectively marked Degree and its corresponding each first that enlivens grade, and will acquire enliven grade, second enliven grade and third is enlivened grade and transmitted To analysis and processing module, and analysis and processing module enlivens each viroid corresponding to grade for first and is transmitted to database, and mentions Defense schemes corresponding with the viroid in database are taken to be transmitted to defence acquisition module, and then can be according to the first active grade institute Corresponding each viroid makes the update of adaptability from moving, increases, sufficiently to cater to actual defence demand, also by such disease Malicious and its corresponding defense schemes are transmitted to information sharing module, and the virus that will be received by information sharing module together Type and its corresponding defense schemes are shown in the mobile phone of staff, and staff is timely understood To more active Virus Type, and whether applicable defense schemes are reasonable, play actively to protection early warning effect is improved Effect, effectively avoiding because the Different Variation form of similar virus occurs causes that link is defendd to be broken, and leverages The safe operation of system for cloud computing;
And analysis and processing module also enlivens each viroid corresponding to grade for second and is transmitted to assessment of risks module, and danger is commented Survival number corresponding with the viroid and number of times of attack will be transferred from defence acquisition module by estimating module, and be carried out risk and commented Estimate operation, and in risk assessment operation, the success attack rate coefficient of each viroid is combined with maximum success attack rate, with Each viroid corresponding to the first hazard class that obtains each hazard class, and will acquire is transmitted to information sharing module, and Each viroid corresponding to second hazard class is transmitted to display module, while third is also enlivened a grade institute by analysis and processing module Corresponding each viroid is through assessment of risks module transfer to display module, so that staff is in medium active Virus Type In, adequately to recognize potentially dangerous virus, and will also can not in addition have the viral of potential danger and less live The virus of jump is sent to display module together, so that staff carries out record viewing, analysis verification etc., helps to improve protection Early warning effect causes to defend link collapse, leverages cloud meter to avoid the emergent explosion type invasion phenomenon of virus Calculate the protection pre-alerting ability of network.
Above content is only to structure of the invention example and explanation, affiliated those skilled in the art couple Described specific embodiment does various modifications or additions or is substituted in a similar manner, without departing from invention Structure or beyond the scope defined by this claim, is within the scope of protection of the invention.

Claims (3)

1. early warning system is protected in a kind of cloud computing based on big data, which is characterized in that including defence acquisition module, data analysis Module, analysis and processing module, database, scheme recording module, information sharing module, assessment of risks module and display module;
The defence acquisition module is used to prevent the invasion of each viroid, and acquires the exclusive letter of all kinds of intrusive viruses in real time Breath, and proprietary information includes survival duration, survival number and number of times of attack, and proprietary information is transmitted to data analysis module; The data analysis module carries out formulation point after receiving proprietary information, to survival duration therein together with number of times of attack Analysis operation, and will acquire first enlivens grade, second enlivens grade and third enlivens grade and is transmitted to analysis and processing module;
The analysis and processing module enlivens each viroid corresponding to grade for first and is transmitted to database, and extracts in database Defense schemes corresponding with the viroid are transmitted to defence acquisition module, also by the viroid and its corresponding defense schemes It is transmitted to information sharing module together, and defense schemes are via carrying out typing after the search of scheme recording module, confirmation;The letter It ceases to be electrically connected between sharing module and the mobile phone of staff, and by the Virus Type received and its corresponding defender Case is shown;
The analysis and processing module also enlivens each viroid corresponding to grade for second and is transmitted to assessment of risks module;The danger Dangerous evaluation module receive second enliven each viroid corresponding to grade after, from defence acquisition module in transfer and the viroid Corresponding survival number and number of times of attack, and corresponding to the first hazard class that carries out risk assessment operation, while will acquire Each viroid be transmitted to information sharing module, and each viroid corresponding to the second hazard class is transmitted to display mould Block;Third is also enlivened each viroid corresponding to grade through assessment of risks module transfer to showing mould by the analysis and processing module Block.
2. early warning system is protected in a kind of cloud computing based on big data according to claim 1, which is characterized in that the public affairs The concrete operation step of formulaization analysis are as follows:
S1: getting all kinds of viral survival durations in the every time in a period, and be demarcated as Xij, i=1...n, j =1...m;
S2: first according to formula, j=1...m, each viroid in every time to acquire a period averagely deposits Duration living, then according to formula, j=1...m is all kinds of in the every time to acquire a period Viral survival duration discrete value;
S3: the merging of Q, W collection is first set separately according to Tj, Rj and marks survival duration coefficient Dj accordingly, and Q, W are gathered Lap be demarcated as b and the Q unitary part gathered be demarcated as a and the W unitary part gathered is demarcated as c, then by Tj, Rj are right by Tj or Rj institute when meeting Tj and being less than or equal to r more than or equal to t, Rj respectively compared with respective preset value t, r Each viroid answered is placed in b and Dj is assigned a value of B, big less than t, Rj greater than r and Tj more than or equal to t, Rj when meeting Tj When r, each viroid corresponding to Tj or Rj is placed in c and Dj is assigned a value of C, is less than or equal to when meeting Tj less than t, Rj When r, each viroid corresponding to Tj or Rj is placed in a and by Dj assignment A, and B is greater than C and is greater than A;
S4: getting each virus-like attacks number in the every time in a period, and be demarcated as Yij, i=1...n, j =1...m;
S5: first according to formula, j=1...m, each virus-like attacks in every time to acquire a period are total Number, and be demarcated as attacking coefficient Fj, then Ej is compared with preset range e, when Ej is located in e, will with corresponding to Ej The Fj of each viroid be assigned a value of q, when Ej is more than or equal to e, will be assigned a value of w with the Fj of each viroid corresponding to Ej, When Ej is less than or equal to e, it will be assigned a value of s with the Fj of each viroid corresponding to Ej, and w is greater than q and is greater than s, Ej and Tj, Rj mono- One is corresponding;
Wherein, a period can be defined as one month, and every time can be defined as every 84 hours;
The data analysis module is when getting Xij and Tj, Rj and Yij and Ej, by the survival duration coefficient corresponding to it Dj, attack coefficient Fj carry out weight distribution compared to the influence accounting of viral activity, and successively will be corresponding to Dj, Fj distribution Weighted value k, h, and k is greater than h, k+h=1, while according to formula, j=1...m, to acquire period Each viroid active degree in every time, and Gj is compared with preset range g, it, will be right with Gj institute when Gj is located in g Each viroid answered generates second and enlivens grade, when Gj is more than or equal to g, enlivens generating second with each viroid corresponding to Gj Grade enlivens grade for third is generated with each viroid corresponding to Gj when Gj is less than or equal to g.
3. early warning system is protected in a kind of cloud computing based on big data according to claim 1, which is characterized in that the wind The concrete operation step of dangerous evaluation operation are as follows:
U1: getting all kinds of viral survival numbers and number of times of attack in every section time in a stage, and demarcates one accordingly Each virus-like attacks success rate Pij, i=1...n, j=1...m in every section time in a stage;
U2: first according to formula, i=1...n, come acquire each virus-like attacks in a stage at Power coefficient, then by Li and preset value f, andCompared with preset value d, when Li be less than or equal to f,Greatly When being equal to d, the first hazard class will be generated with each viroid corresponding to Li, and each viroid corresponding to other and Li generates Second hazard class;
Wherein, a period can be defined as one month, and every time can be defined as every 84 hours.
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110798484A (en) * 2019-11-13 2020-02-14 珠海市鸿瑞信息技术股份有限公司 Industrial control protocol characteristic attack filtering and analyzing system
CN113722573A (en) * 2020-05-26 2021-11-30 中国电信股份有限公司 Method, system and storage medium for generating network security threat data set

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103092739A (en) * 2013-01-18 2013-05-08 浪潮电子信息产业股份有限公司 Memory error checking and correcting (ECC) error reporting and alarm mechanism
CN103118036A (en) * 2013-03-07 2013-05-22 上海电机学院 Cloud end based intelligent security protection system and method
CN104065622A (en) * 2013-03-20 2014-09-24 腾讯科技(深圳)有限公司 Security early warning method and apparatus of network equipment
CN105376222A (en) * 2015-10-30 2016-03-02 四川九洲电器集团有限责任公司 Intelligent defense system based on cloud computing platform
US20160359899A1 (en) * 2012-02-29 2016-12-08 Cytegic Ltd. System and method for cyber attacks analysis and decision support
CN107360188A (en) * 2017-08-23 2017-11-17 杭州安恒信息技术有限公司 Website value-at-risk appraisal procedure and device based on cloud protection and cloud monitoring system
CN109005168A (en) * 2018-07-25 2018-12-14 安徽三实信息技术服务有限公司 A kind of network security warning system and method for early warning
CN109543025A (en) * 2018-12-04 2019-03-29 雄商网络科技(上海)有限公司 A kind of enterprise web site construction information displaying delivery system

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160359899A1 (en) * 2012-02-29 2016-12-08 Cytegic Ltd. System and method for cyber attacks analysis and decision support
CN103092739A (en) * 2013-01-18 2013-05-08 浪潮电子信息产业股份有限公司 Memory error checking and correcting (ECC) error reporting and alarm mechanism
CN103118036A (en) * 2013-03-07 2013-05-22 上海电机学院 Cloud end based intelligent security protection system and method
CN104065622A (en) * 2013-03-20 2014-09-24 腾讯科技(深圳)有限公司 Security early warning method and apparatus of network equipment
CN105376222A (en) * 2015-10-30 2016-03-02 四川九洲电器集团有限责任公司 Intelligent defense system based on cloud computing platform
CN107360188A (en) * 2017-08-23 2017-11-17 杭州安恒信息技术有限公司 Website value-at-risk appraisal procedure and device based on cloud protection and cloud monitoring system
CN109005168A (en) * 2018-07-25 2018-12-14 安徽三实信息技术服务有限公司 A kind of network security warning system and method for early warning
CN109543025A (en) * 2018-12-04 2019-03-29 雄商网络科技(上海)有限公司 A kind of enterprise web site construction information displaying delivery system

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
A.S.SENDI 等: ""Cloud Computing: A Risk Assessment Model,"", 《2014 IEEE INTERNATIONAL CONFERENCE ON CLOUD ENGINEERING》 *
张华杰: ""基于大数据的网络安全防护系统设计与应用"", 《信息通信》 *
晏裕生: ""基于等级保护的云计算IaaS安全评估研究"", 《中国优秀硕士学位论文全文数据库 信息科技辑》 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110798484A (en) * 2019-11-13 2020-02-14 珠海市鸿瑞信息技术股份有限公司 Industrial control protocol characteristic attack filtering and analyzing system
CN110798484B (en) * 2019-11-13 2021-10-01 珠海市鸿瑞信息技术股份有限公司 Industrial control protocol characteristic attack filtering and analyzing system
CN113722573A (en) * 2020-05-26 2021-11-30 中国电信股份有限公司 Method, system and storage medium for generating network security threat data set
CN113722573B (en) * 2020-05-26 2024-02-09 中国电信股份有限公司 Method, system and storage medium for generating network security threat data set

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