Research on security resource allocation optimization of critical infrastructure

doi:10.16265/j.cnki.issn1003-3033.2026.02.0519

Abstract

Abstract:

In order to improve the rationality and effectiveness of critical infrastructure security resource allocation, and solve the shortcomings of traditional methods in the balance of security resource allocation and protection effectiveness, an optimization model of critical infrastructure security resource allocation was constructed based on PT, ASD and Stackelberg game theory. Firstly, the ASD-Stackelberg game model was constructed to solve the optimal spatial allocation of security resources within critical infrastructure. Secondly, the PT theory was introduced to describe the bounded rationality characteristics of both attack and defense sides, and the optimal security resource investment threshold was determined. Finally, the nuclear power plant security system was taken as a case study. The verification and analysis results show that compared with the traditional empirical configuration method, the optimal resource allocation scheme output by this model has significantly improved the overall security effectiveness of nuclear power plants by 25.9%, and can accurately identify the optimal amount of security resource investment. This result not only confirms the effectiveness and feasibility of the model in solving the optimal configuration scheme, but also quantitatively establishes its significant superiority in enhancing security protection capabilities.

Key words: critical infrastructure, security resource allocation, prospect theory(PT), adversary intrusion sequence diagram (ASD), Stackelberg game model

CLC Number:

X956生活安全

HUANG Jicheng, CHEN Wenjing, JIA Nan. Research on security resource allocation optimization of critical infrastructure[J]. China Safety Science Journal, 2026, 36(2): 218-226.

Figures/Tables 11

Fig.1

Fig.2

Fig.3

Table 1

Fig.4

Table 2

Table 3

Table 4

Optimal security resource allocation and shortest path cost with different security resource inputs

策略	Z+z	x₁	x₂	x₃	x₄	x₅		x₆	x₇	x₈	路径代价
$S d 0$	800	157.0	165.0	169.0	25.0	56.0		25.0	32.0	169.0	214.0
$S d 1$	880	183.9	188.0	188.0	27.5	27.5		27.5	49.6	188.0	238.0
$S d 2$	960	200.3	205.0	205.0	30.0	33.2		30.0	50.8	205.2	259.6
$S d 3$	1 040	214.3	222.1	222.1	32.5	52.0		32.5	42.4	222.1	281.1
$S d 4$	1 120	219.8	231.6	237.3	35.0	78.7		35.0	45.3	237.3	300.5
$S d 5$	1 200	247.4	256.3	256.3	37.5	59.0		37.5	49.8	256.3	322.5
$S d 6$	1 280	251.2	264.7	271.2	40.0	90.0		40.0	51.9	271.2	343.4
$S d 7$	1 360	282.0	291.0	291.0	42.5	66.2		42.5	51.0	291.9	367.6
$S d 8$	1 440	296.9	307.6	307.6	45.0		71.0	45.0	59.3	307.6	389.3
$S d 9$	1 520	313.2	324.6	324.6	47.5		76.0	47.5	62.0	324.6	410.9
$S d 10$	1 600	329.9	341.7	341.7	50.0		78.7	50.0	66.4	341.7	432.5

Table 4

Table 5

Attacker prospect utility value under different security resource input

防御策略	$S d 0$	$S d 1$	$S d 2$	$S d 3$	$S d 4$	$S d 5$
效用价值	155.0	126.7	101.0	76.8	54.9	27.6
防御策略	$S d 6$	$S d 7$	$S d 8$	$S d 9$	$S d 10$	—
效用价值	6.0	-22.1	-45.6	-68.9	-94.4	—

Table 5

Table 6

Defender prospect utility value under different security resource input

防御策略	$S d 0$	$S d 1$	$S d 2$	$S d 3$	$S d 4$	$S d 5$
效用价值	414.5	426.4	430.4	430.6	423.2	427.4
防御策略	$S d 6$	$S d 7$	$S d 8$	$S d 9$	$S d 10$	—
效用价值	427.7	0	0	0	0	—

Table 6

Fig.5

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策略	路径	路径代价
S_a1	x₀→x₂→x₅→x₇→x₈/T	170
S_a2	x₀→x₂→x₅→x₆→x₈/T	175
S_a3	x₀→x₁→x₅→x₇→x₈/T	185
S_a4	x₀→x₃→x₄→x₇→x₈/T	185
S_a5	x₀→x₁→x₅→x₆→x₈/T	190
S_a6	x₀→x₃→x₅→x₇→x₈/T	195
S_a7	x₀→x₃→x₄→x₆→x₈/T	200
S_a8	x₀→x₃→x₅→x₆→x₈/T	200
S_a9	x₀→x₂→x₄→x₇→x₈/T	220
S_a10	x₀→x₁→x₄→x₇→x₈/T	235
S_a11	x₀→x₂→x₄→x₆→x₈/T	235
S_a12	x₀→x₁→x₄→x₆→x₈/T	250