Malicious Wireless Communication Link Detection of Power Internet of Thing Devices
Xiao Yong1, Qian Bin1, Cai Ziwen1, Hong Liang2, Su Sheng2
1. Electric Power Research Institute of China Southern Power Grid Guangzhou 510663 China; 2. College of Electrical Engineering Changsha University of Science and Technology Changsha 410114 China
Abstract：The power internet of thing (IoT) devices dispersed around the user side and most of them communicate with general packet radio service (GPRS) via wireless virtual private network (VPN) provided by internet service provider (ISP). The Power Internet of Thing (IoT) devices could connect to malicious base station and suffer cyber-attack. Although 3G and 4G generation communication support two-way authentication and could prevent from connecting to malicious base station, threat of malicious base station will exist till all the IoT devices communicate with GPRS are replaced since existing IoT device are designed to be backward-compatible. Since IoT device and base station are deployed in fix location, the difference in signal strength profile of legitimate and malicious base station can be utilized as a fingerprinting to detect a malicious base station. Signal strength clustering based approach is proposed to identify malicious base station. Numerical simulation indicates that the proposed approach could adapt to IoT devices with limited computation resource and the malicious base station could be identified within the moving window at easy. The power IoT devices could be hardened with the proposed approach.
肖勇, 钱斌, 蔡梓文, 洪亮, 苏盛. 电力物联网终端非法无线通信链路检测方法[J]. 电工技术学报, 2020, 35(11): 2319-2327.
Xiao Yong, Qian Bin, Cai Ziwen, Hong Liang, Su Sheng. Malicious Wireless Communication Link Detection of Power Internet of Thing Devices. Transactions of China Electrotechnical Society, 2020, 35(11): 2319-2327.
[1] 薛禹胜, 朱洪波, 王琴, 等. 物联网对能源转型的支撑[J]. 物联网学报, 2019, 3(1): 1-7. Xue Yusheng, Zhu Hongbo, Wang Qin, et al.Support of the Internet of things for energy transformation[J]. Chinese Journal on Internet of Things, 2019, 3(1): 1-7. [2] 荆孟春, 王继业, 程志华, 等. 电力物联网传感器信息模型研究与应用[J].电网技术, 2014, 38(2): 532-537. Jing Mengchun, Wang Jiye, Cheng Zhihua, et al.Attacks and cyber security defense in cyber physical power system[J]. Power Systems Technology, 2014, 38(2): 532-537. [3] 刘念, 余星火, 王剑辉, 等. 泛在物联的配用电优化运行:信息物理社会系统的视角[J]. 电力系统自动化, 2020, 44(1): 1-12. Liu Nian, Yu Xinghuo, Wang Jianhui, et al.Optimal operation of power distribution and consumption system based on uUbiquitous internet of things: a cyber-physical-social system perspective[J]. Automation of Electric Power Systems, 2020, 44(1): 1-12. [4] 王赞, 陈光, 董晓, 等. 基于工业互联网的智慧能源服务系统架构研究[J]. 电力系统保护与控制, 2020, 48(3): 77-83. Wang Zan, Chen Guang, Dong Xiao, et al.Research on the architecture of smart energy service system based on industrial internet[J]. Power System Protection and Control, 2020, 48(3): 77-83. [5] 王一蓉, 邹颖, 王艳茹. 电力无线虚拟专网组网架构及IP地址分配研究[J]. 电力信息与通信技术, 2014, 12(6): 16-21. Wang Yirong, Zou Ying, Wang Yanru.Research on network architecture and IP address allocation of power wireless virtual private network[J]. Electric Power Information and Communication Technology, 2014, 12(6): 16-21. [6] 王一蓉, 佟大力, 邓伟. 电力无线虚拟专网应用分析及网络设计[J]. 电力信息与通信技术, 2013 11(12): 49-53. Wang Yirong, Tong Dali, Deng Wei.Application analysis and network design of power wireless virtual private network[J]. Electric Power Information and Communication Technology, 2013, 11(12): 49-53. [7] Spanish smart meters easy to hack[EB/OL]. [2020-03-10].https://eandt.theiet.org/content/articles/2014/10/ Spanish-smart-meters-easy-to-hack/ [8] 吴亦贝, 李俊娥, 陈汹, 等. 大规模可控负荷被恶意控制场景下配电网风险分析[J]. 电力系统自动化, 2018,42(10): 30-37. Wu Yibei, Li June, Chen Xiong, et al.Risk analysis of distribution network under massive controllable loads in malicious control[J]. Automation of Electric Power Systems, 2018, 42(10): 30-37. [9] 李昌超, 康忠健, 于洪国, 等. 考虑电力业务重要性的电力通信网关键节点识别[J]. 电工技术学报, 2019, 34(11): 2384-2394. Li Changchao, Zhou Zhongjian, Yu Hongguo, et al.Identification of key nodes in power communication network considering the importance of power businesses[J]. Transactions of China Electrotechnical Society, 2019, 34(11): 2384-2394. [10] 金东勋. GSM网络安全协议漏洞研究[D]. 北京: 北京邮电大学, 2015. [11] Haddad Z, Mahmoud M, Taha S, et al.Secure and privacy-preserving AMI-utility communications via LTE-A networks[C]//11th IEEE International Conference on Wireless and Mobile Computing, Networking and Communications, Abu Dhabi, 2015: 748-755. [12] Syed Rafiul Hussain, Omar Chowdhury, Shagufta Mehnaz, et al.LTE inspector: a systematic approach for adversarial testing of 4G LTE[C]//Network and Distributed Systems Security Symposium, 2018: 18-21. [13] 何奉禄, 陈佳琦, 李钦豪, 等. 智能电网中的物联网技术应用与发展[J]. 电力系统保护与控制, 2020, 48(3): 58-69. He Fenglu, Chen Jiaqi, Li Qinhao, et al.Application and development of internet of things in smart grid[J]. Power System Protection and Control, 2020, 48(3): 58-69. [14] Chen C M, Chen Y H, Lin Y H, et al.Eliminating rouge femtocells based on distance bounding protocol and geographic information[J]. Expert Systems with Applications, 2014, 41(2): 426-433. [15] 罗军舟, 杨明, 凌振, 等. 网络空间安全体系与关键技术[J]. 中国科学: 信息科学, 2016, 46: 939-968. Luo Junzhou, Yang Ming, Ling Zhen, et al.Architecture and key technologies of cyberspace security[J]. Scientia Sinica Informationis, 2016, 46: 939-968. [16] Chouchane A, Rekhis S, Boudriga N.Defending against rogue base station attacks using wavelet based fingerprinting[C]//IEEE/ACS International Conference on Computer Systems and Applications, Rabat, 2009: 523-530. [17] Patel H J, Temple M A, Baldwin R O.Improving ZigBee device network authentication using ensemble decision tree classifiers with radio frequency distinct native attribute fingerprinting[J]. IEEE Transactions on Reliability, 2015, 64(1): 221-233. [18] Reising D R, Temple M A, Mendenhall M J.Improved wireless security for GMSK-based devices using RF fingerprinting[J]. International Journal of Electronic Security and Digital Forensics, 2010, 3(1): 41-59. [19] Chen S, Pande A, Mohapatra P.Sensor-assisted facial recognition: an enhanced biometric authentication system for smartphones[C]//12th International Conference on Mobile Systems, Applications, and Services, Bretton Woods, 2014: 109-122. [20] Wang Wei, Yang Lin, Zhang Qian, et al.Securing on-body IoT devices by exploiting creeping wave propagation[J]. IEEE Journal on Selected Areas in Communications, 2018, 36(4): 696-703. [21] 方震, 赵湛, 郭鹏, 等. 基于RSSI测距分析[J]. 传感技术学报, 2007, 20(11): 2526-2530. Fang Zhen, Zhao Zhan, Guo Peng, et al.Analysis based on RSSI ranging[J]. Journal of Transduction Technology, 2007, 20(11): 2526-2530. [22] 王毅, 张宁, 康重庆, 等. 电力用户行为模型:基本概念与研究框架[J]. 电工技术学报, 2019, 34(10): 2056-2068. Wang Yi, Zhang Ning, Kang Chongqing, et al.Electrical consumer behavior model: basic concept and research framework[J]. Transactions of China Electrotechnical Society, 2019, 34(10): 2056-2068. [23] 杨德昌, 赵肖余, 何绍文, 等. 面向海量用户用电数据的集成负荷预测[J]. 电网技术, 2018, 42(9): 2923-2929. Yang Dechang, Zhao Xiaoyu, He Shaowen, et al.Aggregated load forecasting based on massive household smart meter data[J]. Power System Technology, 2018, 42(9): 2923-2929. [24] 李恩文, 王力农, 宋斌, 等. 基于改进模糊聚类算法的变压器油色谱分析[J]. 电工技术学报, 2018, 33(19): 4594-4602. Li Enwen, Wang Linong, Song Bin, et al.Transformer oil chromatography based on improved fuzzy clustering algorithm[J]. Transactions of China Electrotechnical Society, 2018, 33(19): 4594-4602. [25] 周贤正, 陈玮, 郭创新. 考虑供能可靠性与风光不确定性的城市多能源系统规划[J]. 电工技术学报, 2019, 34(17): 3672-3686. Zhou Xianzheng, Chen Wei, Guo Chuangxin.An urban multi-energy system planning method incorporating energy supply reliability and wind-photovoltaic generators uncertainty[J]. Transactions of China Electrotechnical Society, 2019, 34(17): 3672-3686. [26] 陈皓, 冀敏杰, 郭紫园, 等. 一种时间序列数据的动态密度聚类算法[J]. 控制理论与应用, 2019, 36(8): 1304-1314. Chen Hao, Jü Minjie, Guo Ziyuan, et al.A dynamic density clustering algorithm for time series data[J]. Control Theory & Applications, 2019, 36(8): 1304-1314.
2020, Vol. 35 
