CN110061868A - A kind of network security Measure Indexes system discrimination evaluation model - Google Patents
A kind of network security Measure Indexes system discrimination evaluation model Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/14—Network analysis or design
- H04L41/145—Network analysis or design involving simulating, designing, planning or modelling of a network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/50—Network service management, e.g. ensuring proper service fulfilment according to agreements
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/08—Network architectures or network communication protocols for network security for authentication of entities
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/10—Network architectures or network communication protocols for network security for controlling access to devices or network resources
Abstract
The invention discloses a kind of network security Measure Indexes system discrimination evaluation models, assuming that object Measure Indexes system to be evaluated has N grades, N is more than or equal to 2, then calculated since N-1 grades of index discriminations, then N-2 grades of index discriminations are calculated, ..., until two-level index discrimination, first class index discrimination, so that index system entirety discrimination be calculated.The present invention shows in particular the calculation method of every level-one discrimination.The present invention is to objectively evaluate object to establish metrics evaluation matrix, mathematical model is constructed based on factor of evaluation, and index discrimination is modified using index significance level as reasonability impact factor, to realize index system performance evaluation, embody subjective and objectively organically blend.
Description
Technical field
The present invention relates to a kind of network security Measure Indexes system discrimination evaluation models, belong to network safety filed.
Background technique
Network security Measure Indexes system is the working foundation of network security risk evaluation, normally comprises various information system
All kinds of indexs of various information resources, index system should objectively reflect the safety assurance ability for being evaluated information system in uniting.
It, should be in the key technology and management factors of analyzing influence information system security when in face of different assessment targets and assessment scene
On the basis of, selecting index is carried out using the method for science, objectively to reflect the safety guarantee of information system to the full extent
Ability.
Being chosen in the research of complication system for index is a critical issue.The problem have it is more highly difficult, index is not
Foot can make information content insufficient and impact analysis and evaluation result, index excessively can then generate redundancy, increase analysis and calculate
Difficulty.The determination of network security Measure Indexes system reference frame is to find one kind to eliminate redundancy from a large amount of index
Refer to calibration method, select the index minimal set for being able to reflect phylogeny situation, and to the whole discrimination of index system into
Row measuring and calculating, to measure the appropriate of different situations lower network security measure index system.
Currently, the method for domestic outer support evaluation index screening has very much, can specifically be divided into three categories, it may be assumed that fixed
Property analytic approach, quantitative analysis method and qualitative, quantitative combine analytic approach.Way of qualitative analysis is mainly the purpose and principle from evaluation
It sets out, the evaluation criterion system which index to be made of system is determined by systems analyst and policymaker's subjectivity.With Delphi
For method, overall merit is carried out by the experience of expert, advantage is the knowledge and experience for being effectively utilized expert, but subjectivity
Too strong, time cost is high.Quantitative analysis method mainly filters out required index with mathematical method according to the quantitative relation between index,
Its representative has Principal Component Analysis, gray relative analysis method, factor analysis, Analysis of Rough Set Theory method etc..Principal component point
" best to simplify " principle of analysis method application principal component analysis, the High Dimensional Systems of a multivariable are acquired most by dimension-reduction treatment
Representational several principal components carry out the evaluation index of approximate expression system to be evaluated.Gray relative analysis method is sent out according between factor
The similar or different degree of exhibition trend measures correlation degree between factor, is completed to calculate analysis by means of grey relation model
Work.Relevant dependence, is attributed to some variables with intricate relationship inside factor analysis research variable
A few multi-stress.Rough set theory establish on the basis of classification mechanism, by classification be interpreted as on particular space etc.
Valence relationship, main thought are using known knowledge base, by inaccurate or uncertain knowledge knowing in known knowledge base
Know to portray.Quantitative assessment overcomes the interference of human factor, but common problem based on rigorous data theory
It is that the numerical value of some quantizations does not have exact meaning, is not received by people in convention.It is mesh that qualitative, quantitative, which combines evaluation assessment,
The preceding common method of index screening.Qualitative evaluation is calculated using mathematical tool, and quantitative assessment is established on qualitative forecasting basis
On, quantitative will combine with qualitative, subjective factor will be applied in the constraint condition of Goal programming Model, realize it is subjective with
Objectively organically blending is more satisfactory index screening method.Many scholars at home and abroad sieve index with different theoretical methods
Select this problem to do a large amount of research work, also achieve many research achievements, still, up to the present it is most of research at
In terms of fruit is concentrated mainly on index screening, seldom consider whether the index screened has distinction.
Whether the established index system of evaluation is reasonable, science includes the integrity degree of inspection target system, discrimination, can grasp
The many aspects such as degree of work.The evaluation of index system refers to be compared between similar index system, according to index simplification and
Universality requires to select most effective index system.Domestic scholars are very few to the research of index system performance evaluation, lack to same
Class index system is preferably studied, and does not carry out the research of quantitative assessment to index system more.
Summary of the invention
Technology of the invention solves the problems, such as: overcoming the deficiencies of the prior art and provide a kind of network security Measure Indexes body
It is discrimination evaluation model.
The technical solution of the invention is as follows:
A kind of network security Measure Indexes system discrimination evaluation model, it is assumed that object Measure Indexes system to be evaluated has N
Grade, then calculate since N-1 grades of index discriminations, then calculates N-2 grades of index discriminations ... ..., until two-level index is distinguished
Degree, first class index discrimination, so that index system entirety discrimination be calculated；N is natural number, N >=1；
The discrimination of j-th of N-1 grades of indexWherein, n is the corresponding N grades of index of j-th of N-1 grades of index
Number, wiFor the entropy weight of corresponding i-th of N grades of indexs of j-th of N-1 grades of index, ηiIt is i-th of N grades corresponding for j-th of N-1 grades of index
The discrimination of index；kiFor the index discrimination corrected parameter of corresponding i-th of N grades of indexs of j-th of N-1 grades of index；
The discrimination of each N-2 grades of index be the corresponding all N-1 grades of indexs of the N-2 grades of index discrimination coordination value it
With divided by the corresponding N-1 grades of index number of the N-2 grades of index, wherein the discrimination coordination value of each N-1 grades of index is distinguished for it
The product of degree and index discrimination corrected parameter；
The discrimination of each N-3 grades of index be the corresponding all N-2 grades of indexs of the N-3 grades of index discrimination coordination value it
With divided by the corresponding N-2 grades of index number of the N-3 grades of index, wherein the discrimination coordination value of each N-2 grades of index is distinguished for it
The product of degree and index discrimination corrected parameter；
The rest may be inferred, and the discrimination of each first class index is that the discrimination of the corresponding all two-level index of the first class index is assisted
The sum of tone pitch is divided by the corresponding two-level index number of the first class index, wherein the discrimination coordination value of each two-level index is its area
The product of indexing and index discrimination corrected parameter；
The whole discrimination η of object Measure Indexes system to be evaluatedIt is wholeFor the sum of the discrimination coordination value of all first class index
Divided by the corresponding all first class index numbers of index system, the discrimination coordination value of each first class index is its discrimination and index
The product of discrimination corrected parameter.
The discrimination η of i-th of N grades of indexiMeet:
Wherein, HiFor the entropy of i-th of N grades of index, wiFor the entropy weight of i-th of N grades of index.
The entropy weight w of i-th of N grades of indexiMeet:
Wherein,
The entropy H of i-th of N grades of indexiIt determines as follows:
WhereinfimIndicate the probability of every kind of uncertainty event ,-ln fimIndicate that every kind of uncertainty event includes
The uncertainty function of information content, q are object total number to be evaluated, HiValue range be 0 < Hi≤1。
fimMethod of determination is as follows:
(s1) assume there are q objects to be evaluated, q objects to be evaluated are as follows about the evaluations matrix R' of n N grades of index:
r'ipFor value of p-th of object to be evaluated in i-th of N grades of index, i=1,2 ..., n；P=1,2 ..., q；
(s2) standardization is made according to following formula to each element in R', the evaluations matrix R after being standardized；
R=(rip)n×q
Wherein, ripFor value of p-th of object to be evaluated in i-th of N grades of index after normalized, rip∈[0,1]；
(s3)
The method of determination for marking discrimination corrected parameter is as follows:
(6.1) index discrimination-significance level representing matrix D is established:
mabIndicate its index discrimination of index and important journey that index discrimination grade is a, index significance level grade is b
The relationship of degree；mab=(qab,zab), wherein qabFor the index discrimination financial value of the index, zabIt is important for the index of the index
Degree financial value；D is total grade of index discrimination, and e is the total grade of index significance level；
(6.2) the index discrimination grade and index significance level grade for determining index to be solved, the selection pair from matrix D
The element answered determines the index discrimination corrected parameter of index to be solved using following formula according to the element:
Element m in matrix DabIt is determined according to following formula:
As a=b, mab=(1,1)
As a <b, mab=(1,0.2 (a-b)+1.1)
As a > b, mab=(0.2 (b-a)+1.1,1)
Compared with prior art, the invention has the following beneficial effects:
(1) present invention establishes metrics evaluation matrix based on objective goal programming object, is constructed based on factor of evaluation
Mathematical model calculates index discrimination and index system overall performance, realizes index system performance evaluation, so as to
Quantitative assessment is carried out to index system performance.
(2) present invention is modified index discrimination using index significance level as reasonability impact factor, makes safety
Measure Indexes system optimization model is with more scientific and reasonability.
Detailed description of the invention
Fig. 1 is evaluation model index system schematic diagram of the present invention.
Specific embodiment
The invention proposes a kind of network security Measure Indexes system discrimination evaluation model, particular content is as follows:
As shown in Figure 1, it is assumed that object Measure Indexes system to be evaluated has N grades, and N is the natural number more than or equal to 1, then from N-
1 grade of index discrimination starts to calculate, and then calculates N-2 grades of index discriminations ... ..., until two-level index discrimination, level-one refer to
Discrimination is marked, so that index system entirety discrimination be calculated；
The discrimination of j-th of N-1 grades of indexWherein, n is the corresponding N grades of index of j-th of N-1 grades of index
Number, wiFor the entropy weight of corresponding i-th of N grades of indexs of j-th of N-1 grades of index, kiIt is i-th of N grades corresponding for j-th of N-1 grades of index
The index discrimination corrected parameter of index, ηiFor the discrimination of corresponding i-th of N grades of indexs of j-th of N-1 grades of index.
The discrimination of each N-2 (if N >=2) grade index is the differentiation of the corresponding all N-1 grades of indexs of the N-2 grades of index
The sum of coordination value is spent divided by the corresponding N-1 grades of index number of the N-2 grades of index, wherein the discrimination of each N-1 grades of index is coordinated
Value is the product of its discrimination and index discrimination corrected parameter；
The discrimination of each N-3 (if N >=2) grade index is the differentiation of the corresponding all N-2 grades of indexs of the N-3 grades of index
The sum of coordination value is spent divided by the corresponding N-2 grades of index number of the N-3 grades of index, wherein the discrimination of each N-2 grades of index is coordinated
Value is the product of its discrimination and index discrimination corrected parameter；
The rest may be inferred, and the discrimination of each first class index is that the discrimination of the corresponding all two-level index of the first class index is assisted
The sum of tone pitch is divided by the corresponding two-level index number of the first class index, wherein the discrimination coordination value of each two-level index is its area
The product of indexing and index discrimination corrected parameter；
The whole discrimination η of object Measure Indexes system to be evaluatedIt is wholeFor the sum of the discrimination coordination value of all first class index
Divided by the corresponding all first class index numbers of index system, the discrimination coordination value of each first class index is its discrimination and index
The product of discrimination corrected parameter.
The entropy weight w of i-th of N grades of indexiAnd discrimination ηiIt determines as follows:
(s1) assume there are q objects to be evaluated, q objects to be evaluated are as follows about the evaluations matrix R' of n N grades of index:
r'ipFor value of p-th of object to be evaluated in i-th of index, i=1,2 ..., n；P=1,2 ..., q；
(s2) since the measurement unit of each index and disunity first will be to them before calculating overall target with them
Be standardized, i.e., the absolute value of index is converted into relative value, to solve the homogeneity of every not homogeneity index value
Change problem.Standardization is made according to following formula to each element in R', the evaluations matrix R after being standardized；
R=(rip)n×q
Wherein, ripFor value of p-th of object to be evaluated in i-th of index after normalized, rip∈[0,1]；
(s3) the entropy H of i-th of indexiIs defined as:
Wherein:
Wherein, fimIndicate the probability of every kind of uncertainty event ,-ln fimIndicate the information content that every kind of uncertainty event includes
Uncertainty function；HiValue range be 0 < Hi≤ 1, in a practical situation, HiWhen=1, indicate the evaluation index to evaluation
Object does not provide any valuable information；HiWhen=0, it is meant that only need evaluation index m that can cover all information content
The assessment of evaluation object is completed, this shows that remaining index does not have any effective information, therefore H in a practical situationi=0 is not
Reasonably, Hi≠0。
(s4) the entropy weight w of i-th of N grades of indexiMeet:
From the definition of entropy weight it can be seen that when value of the object to be evaluated in i-th of index is identical, the index
Entropy reaches maximum value 1, entropy weight 0.Illustrate that the index fails to provide useful information, it may be considered that remove.When evaluation object exists
Value difference in i-th of index is larger, and entropy is smaller, and entropy weight is larger.Illustrate that mark sense policymaker provides useful information, together
When also teach that in the problem, each object has notable difference in the index, and emphasis is answered to consider.Index entropy is bigger, entropy
Weigh it is smaller, and meet:
(s5) if the entropy of i-th of index is Hi, entropy weight wi, then the discrimination η of the evaluation indexiAre as follows:
If N=1, i.e., index system only has level-one, then the whole discrimination η of object Measure Indexes system to be evaluatedIt is wholeFor
The sum of discrimination coordination value of all first class index is divided by the corresponding all first class index numbers of index system, each first class index
Discrimination coordination value be its discrimination and index discrimination corrected parameter product.At this time, it is only necessary to first order calculation index
Discrimination and index discrimination corrected parameter, the discrimination of first class index also utilize above method to calculate.
The discrimination of network security Measure Indexes mutually closes during index screening with two factors of index significance level
Connection again mutually restrict, rely on merely certain factor building index system be it is inappropriate, two kinds of factors should be comprehensively considered and taken
Obtain the balance of the two.The present invention regard the ratio between each index discrimination financial value and the index significance level financial value as the index
Discrimination corrected parameter, when index discrimination financial value is greater than index significance level financial value, illustrate index not and be it is especially important,
Index, which is selected in probability, to be turned down, and index discrimination needs are turned down, i.e. corrected parameter < 1；Refer to when index discrimination financial value is less than
Significance level financial value is marked, illustrates that Indexes Comparison is important, needs to increase its selected probability, therefore index discrimination needs to be turned up,
That is corrected parameter > 1；In the case that index discrimination financial value is equal with index significance level financial value, index discrimination without
It needs to adjust, i.e. revision parameter=1.
Assuming that index discrimination is divided into d grades, index significance level is divided into e grades, it is important to establish index discrimination-
The representing matrix D of degree is as follows:
Wherein, element mabIndicate that its index of index that index discrimination grade is a, index significance level grade is b is distinguished
The relationship of degree and significance level, mab=(qab,zab), wherein qabFor the index discrimination financial value of the index, zabFor the index
Index significance level financial value；D is total grade of index discrimination, and e is the total grade of index significance level；
Element mabIt is determined according to following formula:
As a=b, mab=(1,1)
As a <b, mab=(1,0.2 (a-b)+1.1)
As a > b, mab=(0.2 (b-a)+1.1,1)
The method of determination of the index discrimination corrected parameter of index v is as follows:
The index discrimination grade and index significance level grade for determining index v first, select corresponding member from matrix D
Element determines the index discrimination corrected parameter of index v using following formula according to the element:
Embodiment (calculating process for first class index discrimination of only illustrating):
If certain evaluation object index system T includes first class index 3, two-level index 16.It is specific as shown in table 1.
1 index system T of table
According to the true detection data in certain project scene, evaluations matrix, and first order calculation index " identity identification ", " visit are constructed
Ask control " under each two-level index index entropy weight, discrimination.Calculated result such as table 2:
Index entropy weight, the discrimination of each two-level index of table 2
Index corrected parameter calculates:
If index discrimination is divided into 6 grades altogether, index significance level is divided into 6 grades altogether, then according to the method for the present invention, builds
The representing matrix of vertical index discrimination-significance level is as follows:
Using the ratio between index discrimination financial value and index significance level financial value as index discrimination corrected parameter.
By taking the two-level index T11, T12, T13 in index system T as an example, it is assumed that its significance level grade point be respectively (2,
1,3), discrimination grade point is respectively (3,2,1), therefore tables look-up and calculate, and obtains two-level index T11, the Index areas of T12, T13
Index corrected parameter k11=0.9/1, k12=0.9/1, k13=1/0.7.
Two-level index discrimination corrected parameter result is as follows: k=(0.9,0.9,1/0.7,1；1/0.7,0.7,1/0.7,
0.5,1；1/0.9,1/0.7,1,0.5,1,1) for the first class index T1, T2, T3 in index system T, it is assumed that its significance level
Grade point is respectively (1,1,1), and discrimination grade point is respectively (1,1,1), and a note index discrimination corrected parameter result is as follows:
K=(1；1；1)
In the present invention, N=2 can be according to the discrimination for finding out each first class index, according to every according to the method for the present invention
The discrimination of a first class index and the product of index discrimination corrected parameter, obtain the discrimination coordination value of each first class index,
The whole discrimination η of object Measure Indexes system to be evaluatedIt is wholeThe sum of discrimination coordination value for all first class index is divided by 3.
The present invention gives the quantitative evaluating methods of index system performance, establish metrics evaluation square to objectively evaluate object
Battle array, based on factor of evaluation construct mathematical model, and using index significance level as reasonability impact factor to index discrimination into
Row amendment, to realize index system performance evaluation, embody subjective and objectively organically blend.
The content that description in the present invention is not described in detail belongs to the well-known technique of professional and technical personnel in the field.
Claims (7)
1. a kind of network security Measure Indexes system discrimination evaluation model, it is characterised in that: assuming that object to be evaluated measurement refers to
Mark system has N grades, then calculates since N-1 grades of index discriminations, then calculates N-2 grades of index discriminations ... ..., until second level
Index discrimination, first class index discrimination, so that index system entirety discrimination be calculated；N is natural number, N >=1；
The discrimination of j-th of N-1 grades of indexWherein, n is the corresponding N grades of index number of j-th of N-1 grades of index,
wiFor the entropy weight of corresponding i-th of N grades of indexs of j-th of N-1 grades of index, ηiFor j-th corresponding i-th of N grades of N-1 grades of indexs refer to
Target discrimination；kiFor the index discrimination corrected parameter of corresponding i-th of N grades of indexs of j-th of N-1 grades of index；
The discrimination of each N-2 grades of index is that the sum of the discrimination coordination value of the corresponding all N-1 grades of indexs of the N-2 grades of index removes
With the corresponding N-1 grades of index number of the N-2 grades of index, wherein the discrimination coordination value of each N-1 grades of index be its discrimination with
The product of index discrimination corrected parameter；
The discrimination of each N-3 grades of index is that the sum of the discrimination coordination value of the corresponding all N-2 grades of indexs of the N-3 grades of index removes
With the corresponding N-2 grades of index number of the N-3 grades of index, wherein the discrimination coordination value of each N-2 grades of index be its discrimination with
The product of index discrimination corrected parameter；
The rest may be inferred, and the discrimination of each first class index is the discrimination coordination value of the corresponding all two-level index of the first class index
The sum of divided by the corresponding two-level index number of the first class index, wherein the discrimination coordination value of each two-level index is its discrimination
With the product of index discrimination corrected parameter；
The whole discrimination η of object Measure Indexes system to be evaluatedIt is wholeThe sum of discrimination coordination value for all first class index divided by
The corresponding all first class index numbers of index system, the discrimination coordination value of each first class index are that its discrimination and index are distinguished
Spend the product of corrected parameter.
2. a kind of network security Measure Indexes system discrimination evaluation model according to claim 1, it is characterised in that: the
The discrimination η of i N grades of indexsiMeet:
Wherein, HiFor the entropy of i-th of N grades of index, wiFor the entropy weight of i-th of N grades of index.
3. a kind of network security Measure Indexes system discrimination evaluation model according to claim 2, it is characterised in that: the
The entropy weight w of i N grades of indexsiMeet:
Wherein,
4. a kind of network security Measure Indexes system discrimination evaluation model according to claim 3, it is characterised in that: the
The entropy H of i N grades of indexsiIt determines as follows:
WhereinfimIndicate the probability of every kind of uncertainty event ,-lnfimIndicate the information that every kind of uncertainty event includes
The uncertainty function of amount, q are object total number to be evaluated, HiValue range be 0 < Hi≤1。
5. a kind of network security Measure Indexes system discrimination evaluation model according to claim 4, it is characterised in that: fim
Method of determination is as follows:
(s1) assume there are q objects to be evaluated, q objects to be evaluated are as follows about the evaluations matrix R' of n N grades of index:
r′ipFor value of p-th of object to be evaluated in i-th of N grades of index, i=1,2 ..., n；P=1,2 ..., q；
(s2) standardization is made according to following formula to each element in R', the evaluations matrix R after being standardized；
R=(rip)n×q
Wherein, ripFor value of p-th of object to be evaluated in i-th of N grades of index after normalized, rip∈[0,1]；
(s3)
6. a kind of network security Measure Indexes system discrimination evaluation model according to claim 1, it is characterised in that: refer to
The method of determination for marking discrimination corrected parameter is as follows:
(6.1) index discrimination-significance level representing matrix D is established:
mabIndicate index discrimination grade be a, its index discrimination of index that index significance level grade is b and significance level
Relationship；mab=(qab,zab), wherein qabFor the index discrimination financial value of the index, zabFor the index significance level of the index
Financial value；D is total grade of index discrimination, and e is the total grade of index significance level；
(6.2) the index discrimination grade and index significance level grade for determining index to be solved, select corresponding from matrix D
Element determines the index discrimination corrected parameter of index to be solved using following formula according to the element:
7. a kind of network security Measure Indexes system discrimination evaluation model according to claim 6, it is characterised in that: square
Element m in battle array DabIt is determined according to following formula:
As a=b, mab=(1,1)
As a <b, mab=(1,0.2 (a-b)+1.1)
As a > b, mab=(0.2 (b-a)+1.1,1).
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