The Optimization Method of Industrial Control System Functional Safety and Information Security Policy

doi:10.3969/j.issn.1671-1122.2022.11.009

Abstract

Abstract:

In view of the problem that is difficult to solve in current industrial control security compatibility, at the essential level of the competition between functional safety and information security resource consumption, a formal model supporting the conflict between functional safety and information security is proposed. The functional safety degree, information security degree, CPU occupation, and memory occupation of the security policy of the industrial control system are mathematically described. This paper took four mathematical functions as objective functions to measure the advantages and disadvantages of the security policy for multi-objective optimization. It fully considered the key factors of industrial control systems such as functional safety, information security, time delay, and resource consumption, constructed the parameter space of the objective function, and used the space interval to select the optimal strategy. This paper overcomes the limitation that the traditional contradiction shielding method can only be qualitatively configured without affecting functional safety, and provides a complete set of policy optimization schemes and algorithms for industrial control systems. The strategy optimization algorithm is applied to the train control system to obtain the optimal safety strategy scheme of the Automatic Train Protection (ATP) system.Experimental results show that the security strategy optimization method proposed in this paper can quantify the advantages and disadvantages of security strategies, and effectively select the optimal scheme of security strategy to ensure the security of industrial control systems.

Key words: information security, functional safety, time complexity, space complexity, genetic algorithm

CLC Number:

TP309

SONG Jing, DIAO Run, ZHOU Jie, QI Jianhuai. The Optimization Method of Industrial Control System Functional Safety and Information Security Policy[J]. Netinfo Security, 2022, 22(11): 68-76.

Figures/Tables 8

References 22

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策略名称	安全程度	数据	时间复杂度	空间复杂度
故障自诊断与报警	9	8	n	n
列车过程状态监测	7	8	n	con
防御性编程	5	0	con	con
错误检测码	9	6	nlogn	n
人工智能故障纠正	6	8	n²	n²

策略名称	安全程度	数据	时间复杂度	空间复杂度
病毒防护	7	6	n	n
访问控制	6	3	n²	con
数据加解密	9	6	n²	n²
用户行为监测	6	2	n²	n²
漏洞扫描	4	4	n	n
USB-key	9	1	n	con

策略编号	策略名称	方案1	方案2	方案3	方案4	方案5	方案6	方案7
1	故障自诊断与报警	1	1	1	1	1	1	1
2	列车过程状态监测	1	1	1	1	1	1	1
3	防御性编程	1	1	1	1	1	0	1
4	错误检测码	1	1	1	1	1	1	1
5	人工智能故障纠正	0	0	0	1	0	1	0
6	病毒防护	0	1	1	1	1	1	1
7	访问控制	1	1	1	1	1	1	1
8	数据加解密	1	1	1	0	0	0	1
9	用户行为监测	1	1	0	1	1	1	1
10	漏洞扫描	1	1	1	1	1	1	0
11	USB-key	1	1	1	1	1	1	1

方案编号	${{x}_{1}}$	${{x}_{2}}$	${{x}_{3}}$
1	30	34	137.67
2	30	41	149.67
3	30	35	139.67
4	36	32	205.67
5	30	32	77.67
6	31	32	203.67
7	30	37	141.67

方案编号	$X{}_{1}$	${{X}_{2}}$	${{X}_{3}}$
1	0.83	0.83	0.50
2	0.83	1.00	0.54
3	0.83	0.85	0.50
4	1.00	0.78	0.74
5	0.83	0.78	0.28
6	0.86	0.78	0.73
7	0.83	0.90	0.51