Network attack association analysis and attack protection strategy for smart park systems

doi:10.3969/j.issn.2097-0706.2022.07.001

Abstract

Abstract:

Control system of smart parks at all levels are vulnerable to network attacks. In order to improve the system's coping capacities to network attacks and the identification accuracy and efficiency of malicious attack events,a network attack association analysis method for smart park systems is proposed. The method takes Frequent Pattern-Growth（FP-Growth） algorithm to detect the association rules of abnormal network attack events. FP-Growth algorithm can quickly mine the frequent item sets of abnormal events and train the association rules. Grey correlation analysis algorithm generates the abnormal manifestation set of real-time abnormal network attack events. Then, following the association rules,the network attack scenarios can be recognized on-line. Network attack protection strategy is made according to the links corresponding to the different attack scenarios to eliminate the impact of the attack. Finally,the efficiency of the proposed method in training association rules is verified by data of different volumes,and the feasibility of the network attack protection strategy is verified by the Load Frequency Control module of the smart park system.

Key words: smart park, integrated energy system, micro-grid, network attack, association rule analysis and matching, grey correlation analysis, attack protection strategy, control on load and frequency

CLC Number:

TK01：TM73：TP393.08

LI Huijun, LU Jianqiang, ZHOU Xia, XIE Xiangpeng, WAN Lei. Network attack association analysis and attack protection strategy for smart park systems[J]. Integrated Intelligent Energy, 2022, 44(7): 1-9.

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攻击环节	攻击场景	异常表现形式
主站侧	修改配置参数	电压异常、电流异常、切负荷量异常、设备拒动/误动、电价异常
	会话劫持
	伪造控制指令
终端侧	篡改量测数据
	设备重启动
	设备锁控制	网络流量异常、终端违规外联、业务应用拒绝服务、用户数据泄露
通信侧	非法监听报文
	恶意控制通信
	拒绝服务攻击

区域	T_g_i	T_SL_i	T_ch_i	T_E_i	K_E	D_i	H_i	β_i	R_i	T_ij
1	0.10	1.30	0.30	0.30	5.00	1.00	10.00	21.00	0.05	0.50
2	0.08	1.30	0.32	0.30	5.00	1.00	11.00	18.00	0.05	0.50