不完全信息下的威胁处置效果模糊评估

doi:10.11959/j.issn.1000-436x.2019078

Abstract

Abstract:

In order to appropriately select and adjust response countermeasures,it is necessary to evaluate response effectiveness.Although a large amount of effort has been spent on the evaluation of risk and threat situations,the existing schemes are not suitable to evaluate response effectiveness,because the sechems require that all the information used for evaluation is complete,which is difficult to implement in the real environment.To address the problem,a fuzzy scheme was proposed to deal with incomplete information (i.e.,missing elements of judgment matrix and missing data of indicators) and the response effectiveness was evaluate.Firstly,a hierarchical indicator tree was design to characterize the effectiveness from the perspectives of both attack and defense.Then,the fuzzy analytic hierarchy process (FAHP) was used to calculate the comprehensive weight of each indicator.Finally,the response effectiveness was calculated using fuzzy comprehensive evaluation.In particular,to deal with the problem of incompleteness of fuzzy judgment matrix in the process of FAHP,the missing elements were completed based on the transitivity of elements.And to deal with the problem of loss data in the comprehensive evaluation,the missing data was completed based on matrix completion.The experimental results show that the proposed scheme can accurately recover the missing data and can effectively evaluate the effectiveness of response.

Key words: incomplete information, response effectiveness, fuzzy evaluation, matrix completion

CLC Number:

TP302

Fenghua LI,Yongjun LI,Zhengkun YANG,Han ZHANG,Lingcui ZHANG. Fuzzy evaluation for response effectiveness in cases of incomplete information[J]. Journal on Communications, 2019, 40(4): 117-127.

Figures/Tables 11

References 14

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评价等级	偏离值
优	0～a
良	a～b
中	b～c
差	＞c

评价等级	负相关类指标的值	正相关类指标的值
优	0～p₁	＞r₂
良	p₁～q₁	q₂～r₂
中	q₁～r₁	p₂～q₂
差	＞r₁	0～p₂

	1	2	3	4	5	6	7	8	9	10
d_0,1	—	0.1,0.3,0.4	0.2,0.3,0.5	—	0.1,0.2,0.3	0.1,0.3,0.5	—	0.1,0.2,0.3	—	—
d_0,2	—	0.5,0.7,0.8	0.6,0.7,0.9	0.5,0.6,0.7	0.5,0.6,0.7	—	0.7,0.8,0.9	0.5,0.6,0.7	—	0.6,0.8,0.9
d_0,3	0.7,0.8,0.9	0.6,0.8,0.9	—	0.6,0.7,0.8	0.6,0.7,0.8	0.6,0.8,0.9	0.7,0.8,0.9	—	0.7,0.8,0.9	0.7,0.8,0.9

	1	2	3	4	5	6	7	8	9	10
d_1,1	—	0.1,0.3,0.4	0.2,0.3,0.5	0.2,0.4,0.5	0.1,0.2,0.3	—	0.3,0.4,0.5	0.1,0.2,0.3	0.2,0.3,0.4	0.2,0.3,0.4
d_1,2	0.6,0.7,0.8	—	0.6,0.7,0.9	—	0.5,0.6,0.7	0.6,0.7,0.8	0.7,0.8,0.9	—	0.6,0.7,0.8	0.6,0.8,0.9
d_1,3	0.7,0.8,0.9	0.6,0.8,0.9	—	0.6,0.7,0.8	0.6,0.7,0.8	0.6,0.8,0.9	0.7,0.8,0.9	0.6,0.8,0.9	0.7,0.8,0.9	—

	1	2	3	4	5	6	7	8	9	10
d_2,1	0.2,0.3,0.4	—	0.2,0.3,0.5	0.2,0.4,0.5	0.1,0.2,0.3	0.1,0.3,0.5	—	0.1,0.2,0.3	0.2,0.3,0.4	0.2,0.3,0.4
d_2,2	—	0.5,0.7,0.8	—	0.5,0.6,0.7	—	0.6,0.7,0.8	0.7,0.8,0.9	—	0.6,0.7,0.8	0.6,0.8,0.9
d_2,3	0.7,0.8,0.9	0.6,0.8,0.9	0.7,0.8,0.9	—	0.6,0.7,0.8	0.6,0.8,0.9	0.7,0.8,0.9	0.6,0.8,0.9	0.7,0.8,0.9	0.7,0.8,0.9
d_2,4	0.2,0.3,0.4	0.1,0.3,0.4	0.2,0.3,0.5	0.2,0.4,0.5	0.1,0.2,0.3	0.1,0.3,0.5	0.3,0.4,0.5	0.1,0.2,0.3	0.2,0.3,0.4	—
d_2,5	0.6,0.7,0.8	0.5,0.7,0.8	0.6,0.7,0.9	0.5,0.6,0.7	0.5,0.6,0.7	0.6,0.7,0.8	0.7,0.8,0.9	0.5,0.6,0.7	0.6,0.7,0.8	0.6,0.8,0.9
d_2,6	0.7,0.8,0.9	—	0.7,0.8,0.9	—	0.6,0.7,0.8	—	0.7,0.8,0.9	0.6,0.8,0.9	—	0.7,0.8,0.9

Fuzzy evaluation for response effectiveness in cases of incomplete information

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Figures/Tables 11

References 14

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	1	2	3	4	5	6	7	8	9	10
d_3,1	0.7,0.8,0.9	0.6,0.8,0.9	0.7,0.8,0.9	0.6,0.7,0.8	0.6,0.7,0.8	0.6,0.8,0.9	0.7,0.8,0.9	0.6,0.8,0.9	0.7,0.8,0.9	0.7,0.8,0.9
d_3,2	0.2,0.3,0.4	0.1,0.3,0.4	0.2,0.3,0.5	0.2,0.4,0.5	0.1,0.2,0.3	0.1,0.3,0.5	0.3,0.4,0.5	0.1,0.2,0.3	0.2,0.3,0.4	0.2,0.3,0.4

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