CN107832621A - The weighing computation method of Behavior trustworthiness evidence based on AHP - Google Patents
The weighing computation method of Behavior trustworthiness evidence based on AHP Download PDFInfo
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- CN107832621A CN107832621A CN201711136107.9A CN201711136107A CN107832621A CN 107832621 A CN107832621 A CN 107832621A CN 201711136107 A CN201711136107 A CN 201711136107A CN 107832621 A CN107832621 A CN 107832621A
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/50—Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
- G06F21/57—Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
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Abstract
The invention discloses a kind of weighing computation method of the Behavior trustworthiness evidence based on AHP, according to the grade of current information security environment, from suitable weighing computation method, in the case where meeting actual demand, speed up processing as far as possible, the computational space taken is reduced, preferably builds the networks congestion control characteristic model based on AHP.
Description
Technical field
The present invention relates to IDC/ISP information security fields, more particularly to the weight calculation of the Behavior trustworthiness evidence based on AHP
Method.
Background technology
Develop fast traffic lane with broadband is entered in China Internet, it is vulgar while network is brought convenience to people's lives
Increasingly spread unchecked with flame, society and the public are negatively affected.Networks and information security problem seems more and more prominent,
Event of network breaking laws and commit crime increases, and runs counter to the theme built a Harmonious Society, and strengthens monitoring to internet information, and gesture is must
OK.Centers of the IDC as internet information spreading, it dominates the acquisition of internet information and propagation, and interested regulatory authorities are compeled
Cut and want to set up Internet surveillance information base data storehouse, statistical analysis is carried out to violation information, there is provided efficient internet letter
Breath monitoring is with managing the technological means such as control, and under this demand, IDC/ISP suppliers start active construction IDC/ISP information
Safety management system.
In actual monitoring audit process, objective objects that safety management system faces are multi-user (natural person) to more industry
The various operation behaviors of business system, it, which exists, combines the features such as various, flow is complicated.Will be to so complicated and diversified user behavior
Carry out feature extraction and simultaneously establish one-to-one fingerprint base, the problems such as be difficult to extract, model is difficult to set up be present.
Analytic hierarchy process (AHP) (Analytia1 Hierarchy Process, abbreviation AHP) is Univ. of Pittsburgh professor
A kind of systematic analytic method that A.L.Saaty proposes the 1970s.AHP is that one kind can be by qualitative analysis and quantitative point
The systematic analytic method that phase separation combines.AHP be analyze multiple target, multiple criteria complex large system powerful.It, which has, thinks
The features such as road is clear, method is easy, widely applicable, systemic strong, is most appropriate to solve those to be difficult to quantitative approach be entered completely
The decision problem of row analysis, is easy to popularize, and can turn into people and work and pondered a problem in living, solve one kind side of problem
Method.
AHP algorithms can solve to be difficult to the problems such as extract, model is difficult to set up in the application that actual monitoring is audited, but such as
What, which combines to be actually needed, is better achieved AHP algorithms, is still a problem for needing to solve.
The content of the invention
In order to solve the above problems, the present invention proposes a kind of weighing computation method of the Behavior trustworthiness evidence based on AHP, its
It is characterised by, the weighing computation method is used to build the networks congestion control characteristic model based on AHP, builds based on AHP's
Networks congestion control characteristic model includes Judgement Matricies, Mode of Level Simple Sequence and total hierarchial sorting, the weighing computation method
Behavior trustworthiness evidence is provided using database mining technology, and evaluates the grade of current information security environment, is worked as based on described
The grade of preceding information security environment, the choosing of weighing computation method is carried out in the Mode of Level Simple Sequence and the total hierarchial sorting
Select.
Further, it is described to provide Behavior trustworthiness evidence using database mining technology, and evaluate current information security
The grade of environment specifically includes the internet content progress data mining analysis for a large number of users, for flame or improper visit
Ask and detected, detected for much information carrier, the auxiliary information with reference to caused by user's operation, database mining technology
The current information security issue mainly faced can be analyzed, obtained conclusion will be analyzed as important level highest behavior letter
Appoint evidence, and evaluate the grade of current information security environment.
Further, the flame or improper access include porns, gambling and drugs relevant information, sham publicity, rubbish harassing and wrecking letter
Breath, reaction publicity and violation Operational Visit record, the much information carrier includes word, picture, video and Streaming Media, described
Auxiliary information caused by user's operation includes service code, business code, reference address, access time and Subscriber Number.
Further, the grade of described information security context includes very good, good, normal, serious and very serious.
Further, the grade based on the current information security environment, in the Mode of Level Simple Sequence and the layer
The selection that weighing computation method is carried out in secondary total sequence specifically includes：
If the rating of current information security environment is very good, used in Mode of Level Simple Sequence and total hierarchial sorting
Specification column average method calculates characteristic vector；
If the rating of current information security environment is good or normal, selected in Mode of Level Simple Sequence and total hierarchial sorting
Select code requirement column average method or geometric average method calculates characteristic vector；
If the rating of current information security environment is serious, geometric average method meter can only be selected in Mode of Level Simple Sequence
Characteristic vector is calculated, selects code requirement column average method or geometric average method to calculate characteristic vector in total hierarchial sorting；
If the rating of current information security environment is very serious, selected in Mode of Level Simple Sequence and total hierarchial sorting
Select and characteristic vector is calculated using geometric average method.
Embodiment
In order to which technical characteristic, purpose and the effect of the present invention is more clearly understood, now to the specific reality of the present invention
The mode of applying is specifically described.
Using AHP solve problem thinking be：First, it is to be solved the problem of layered serial, i.e., according to the property of problem
Matter and the target to be reached, are different compositing factors by PROBLEM DECOMPOSITION, according to influencing each other between factor and membership
Its hierarchical cluster is combined, one is formed and passs rank, orderly hierarchy Model；Then, to each level factor in model
Relative importance, give quantificational expression to extension judgement according to people, then mathematically determine that each level is complete
The weights of portion's factor relative importance order；Finally, by the weights of each layer factor relative importance of COMPREHENSIVE CALCULATING, obtain minimum
Layer (solution layer) in this, as evaluation and selects relative to the Combining weights of the relative importance order of top (general objective)
The foundation of decision scheme.
According to the guidance of above-mentioned thinking, build the networks congestion control characteristic model based on AHP and mainly include the following steps that：
1) hierarchy Model is established
After the problem of studying is analysed in depth, the factor included in problem is divided into different levels and (such as forbidden
Behavior, abnormal behaviour, non-fulfilling behavior etc.), and draw hierarchical chart expression hierarchical structure and adjacent two layers factor from
Category relation.
2) Judgement Matricies
The value of matrix element represents policymaker to understanding of each factor on the relative importance of target.At adjacent two
In level, high-level is target, and low level is factor.Policymaker does ratio with tournament method to the significance level of multiple evidences
Compared with.
3) Mode of Level Simple Sequence and consistency check
The characteristic vector W of judgment matrix is the weight order value of the relative importance of each factor after normalization.Root
Corresponding consistency check is carried out according to concrete condition.
4) total hierarchial sorting and consistency check
The weight order value that each factor of a certain level is calculated with respect to the relative importance of all factors of last layer time is referred to as layer
Secondary total sequence.Because total hierarchial sorting process is to be carried out from top to lowermost layer, and top is general objective, so, layer
Secondary total sequence is also to calculate relative importance sequencing weight of each factor with respect to your lip-syncing high-rise (general objective).As the case may be
Carry out corresponding consistency check.
It can see from the step of AHP solution problems, the root problem that analytic hierarchy process (AHP) calculates is to ask judgment matrix corresponding
Characteristic vector, i.e., the weight order value of the relative importance of each factor.
The method of calculating weighted value is in the present embodiment：
(1) judgment matrix constructed using database mining technology for policymaker is adjusted.For a large number of users
Internet content carries out data mining analysis, is detected for flame or improper access, such as porns, gambling and drugs relevant information, void
False advertisement, rubbish harassing and wrecking information, reaction publicity, violation Operational Visit record etc., the information carrier detected includes word, figure
Piece, video, Streaming Media etc., with reference to auxiliary informations such as service code, business code, reference address, access time, Subscriber Numbers,
Database mining technology can analyze the current main information safety problem mainly faced.The conclusion obtained analyzing is as weight
Want grade highest Behavior trustworthiness evidence to submit to policymaker, be easy to policymaker to optimize and revise judgment matrix, at the same time, be based on
Current information security environment is assessed as very good, good, normal, serious or very serious by the conclusion that analysis obtains.
(2) calculating of characteristic vector can select geometric average method, and this method calculates space money that is accurate, but needing more
Source, calculating speed is slower, or specification column average method, this method carry out approximate calculation, it is necessary to space resources it is less, calculating speed
Faster.According to the rating of current information security environment, specific algorithms selection is carried out, selection rule is as follows：
If the rating of current information security environment is very good, it is contemplated that now safety coefficient is very high, calculation error
Policymaker will not be caused to ignore more serious safety problem, can simplify calculating, speed up processing, in Mode of Level Simple Sequence and
Equal code requirement column average method calculates characteristic vector in total hierarchial sorting；
If the rating of current information security environment is good or normal, it is contemplated that now safety coefficient is in general water
Flat, calculation error may cause policymaker to ignore more serious safety problem, but this possibility is relatively small, and policymaker can
To consider according to the risk of itself, code requirement column average method or geometric average are selected in Mode of Level Simple Sequence and total hierarchial sorting
Method calculates characteristic vector；
If the rating of current information security environment is serious, it is contemplated that now safety coefficient is in less optimistic water
Flat, calculation error may cause policymaker to ignore serious safety problem, and this possibility is relatively large, single in level
Geometric average method can only be selected to calculate characteristic vector in sequence, itself can be considered according to policymaker in total hierarchial sorting, choosing
Select code requirement column average method or geometric average method calculates characteristic vector；
If the rating of current information security environment is very serious, it is contemplated that now safety coefficient is in very severe
Level, calculation error is likely to result in policymaker and ignores more serious safety problem, total in Mode of Level Simple Sequence and level
Selection calculates characteristic vector using geometric average method in sequence.
If judgment matrix is the positive reciprocal matrix A=(α of n ranksij)n×n, then maximal eigenvector is sought with specification column average method
It is as follows with the method for characteristic root：
Row specification is pressed to A
Judgment matrix after standardization is added by row
To vectorStandardization
Then W=(w1,w2,...,wn)TThe as approximation of maximal eigenvector.
Judgment matrix is that policymaker compares to obtain with tournament method to the significance level of multiple evidences, when user's row
When more for the evidence of trust, it may occur that judge inconsistent situation.Because judgment matrix is provided according to expertise
Subjective judgement, so inconsistency can hardly be avoided, consistency check is exactly to judge the method for inconsistent degree.
The relevant coherency index that AHP algorithms provide is as follows：
Coincident indicator is defined asWherein λmaxFor the Maximum characteristic root of maximal eigenvector.When complete
When consistent, CI=0.When inconsistent, general CIBigger, uniformity is also poorer, so introducing Aver-age Random Consistency Index RI
With random index rate
Average homogeneity index RI：For specific n, the positive and negative matrix A of random configuration n ranks, wherein αijIt is from 1,2 ...,
Randomly selected in 9,1/2,1/3 ..., 1/9, the A so obtained is probably inconsistent.Take fully big increment (such as 1000
Sample), obtain the average value of A Maximum characteristic root.Define Aver-age Random Consistency IndexRIIntroducing exist
Consistency check index C is overcome to a certain extentIThe drawbacks of increasing with matrix exponent number and significantly increasing.
When carrying out the consistency check of total hierarchial sorting, CrComputational methods it is otherwise varied, it is assumed that B level a number of factors
For a certain factor Aj of last layer time single sequence consistency check index CI, corresponding random index is RI, then B layers
The secondary random Consistency Ratio that always sorts is
In view of passing through random index rate CrCheck consistency is relatively harsh, it is necessary to could expire by repeatedly adjustment
Foot requires, and by level of significance α check consistency relative loose, can meet the requirement under particular case, in this programme
By random index rate CrIt is combined with level of significance α, realizes the flexible judgement of uniformity, specific judgment rule is such as
Under：
If the rating of current information security environment is very good, it is contemplated that now safety coefficient is very high, does not meet one
The defects of cause property is brought will not cause policymaker to ignore more serious safety problem, can be with processing procedure, speed up processing,
Consistency check is abandoned after Mode of Level Simple Sequence and after total hierarchial sorting；
If the rating of current information security environment is good or normal, it is contemplated that now safety coefficient is in general water
Flat, not meeting the defects of uniformity is brought may cause policymaker to ignore more serious safety problem, but this possibility phase
To smaller, policymaker can consider according to the risk of itself, can be selected after Mode of Level Simple Sequence and after total hierarchial sorting
Using coincident indicator rate CrCarry out consistency check or using coincident indicator rate CrCarry out one is combined with level of significance α
Cause property is examined；
If the rating of current information security environment is serious, it is contemplated that now safety coefficient is in less optimistic water
Flat, not meeting the defects of uniformity is brought may cause policymaker to ignore serious safety problem, and this possibility is relative
It is larger, coincident indicator rate C can only be used after Mode of Level Simple SequencerConsistency check is carried out, can after total hierarchial sorting
With itself considering according to policymaker, selection uses coincident indicator rate CrCarry out consistency check or use coincident indicator rate
CrCarry out consistency check is combined with level of significance α；
If the rating of current information security environment is very serious, it is contemplated that now safety coefficient is in very severe
Level, calculation error is likely to result in policymaker and ignores more serious safety problem, total in Mode of Level Simple Sequence and level
Selection uses coincident indicator rate C after sequencerCarry out consistency check.
It is so-called to use coincident indicator rate CrIt is when carrying out consistency checking, if correction value C to carry out consistency checkr<
0.1, then it is assumed that inconsistency can be received, if Cr>=0.1, it is believed that inconsistent to receive, it is necessary to change judgment matrix.
It is so-called to use coincident indicator rate CrIt is to carry out uniformity to be combined with level of significance α and carry out consistency check
During judgement, if correction value Cr<0.1, then it is assumed that inconsistency can be received, if Cr>=0.1, continue conspicuousness water
Flat α is examined, if α<0.1, then it is assumed that inconsistency can be received, if α >=0.1, now CrIt is all higher than being equal to 0.1 with α, then recognizes
It can not receive, it is necessary to change judgment matrix to be inconsistent.
One of ordinary skill in the art will appreciate that realize all or part of flow in above-described embodiment method, being can be with
The hardware of correlation is instructed to complete by computer program, described program can be stored in computer read/write memory medium
In, the program is upon execution, it may include such as the flow of the embodiment of above-mentioned each method.Wherein, described storage medium can be magnetic
Dish, CD, ROM, RAM etc..
Above disclosure is only preferred embodiment of present invention, can not limit the right model of the present invention with this certainly
Enclose, therefore the equivalent variations made according to the claims in the present invention, still belong to the scope that the present invention is covered.
Claims (5)
1. a kind of weighing computation method of the Behavior trustworthiness evidence based on AHP, it is characterised in that the weighing computation method is used for
The networks congestion control characteristic model based on AHP is built, the networks congestion control characteristic model based on AHP is built and sentences including construction
Disconnected matrix, Mode of Level Simple Sequence and total hierarchial sorting, the weighing computation method provide Behavior trustworthiness using database mining technology
Evidence, and the grade of current information security environment is evaluated, based on the grade of the current information security environment, in the level
The selection of weighing computation method is carried out in single sequence and the total hierarchial sorting.
2. weighing computation method according to claim 1, it is characterised in that described to provide row using database mining technology
To trust evidence, and the internet content that the grade for evaluating current information security environment is specifically included for a large number of users enters line number
According to mining analysis, detect for flame or improper access, detected for much information carrier, grasped with reference to user
Auxiliary information caused by work, database mining technology can analyze the current information security issue mainly faced, will analyze
The conclusion arrived evaluates the grade of current information security environment as important level highest Behavior trustworthiness evidence.
3. weighing computation method according to claim 2, it is characterised in that the flame or improper access include Huang
Malicious relevant information, sham publicity, rubbish harassing and wrecking information, reaction publicity and violation Operational Visit record, the much information is gambled to carry
Body includes word, picture, video and Streaming Media, auxiliary information caused by user's operation include service code, business code,
Reference address, access time and Subscriber Number.
4. weighing computation method according to claim 2, it is characterised in that the grade of described information security context includes non-
It is Chang Hao, good, normal, serious and very serious.
5. weighing computation method according to claim 4, it is characterised in that described to be based on the current information security environment
Grade, in the Mode of Level Simple Sequence and the total hierarchial sorting carry out weighing computation method selection specifically include：
If the rating of current information security environment is very good, the equal code requirement in Mode of Level Simple Sequence and total hierarchial sorting
Column average method calculates characteristic vector；
If the rating of current information security environment is good or normal, select to adopt in Mode of Level Simple Sequence and total hierarchial sorting
Characteristic vector is calculated with specification column average method or geometric average method；
If the rating of current information security environment is serious, geometric average method can only be selected to calculate in Mode of Level Simple Sequence special
Sign vector, code requirement column average method or geometric average method is selected to calculate characteristic vector in total hierarchial sorting；
If the rating of current information security environment is very serious, selection is adopted in Mode of Level Simple Sequence and total hierarchial sorting
Characteristic vector is calculated with geometric average method.
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| CN111859377A (en) * | 2020-07-27 | 2020-10-30 | 成都安恒信息技术有限公司 | In-business safety auditing method based on user behavior analysis |
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