车联网中基于攻防博弈的蜜罐防御及传输策略

doi:10.11959/j.issn.2096-109x.2022050

Abstract

Abstract:

With the rapid development of the Internet of Vehicles, service providers can efficiently provide caching services for vehicle users by deploying 5G base station-type RSUs adjacent to vehicles.However, due to the presence of malicious attackers, the controlled base station is turned to be malicious for the purpose of identity forgery attack.When messages are sent in the name of malicious base stations to interfere with the communication link between vehicles and the trusted base stations, it is easy to cause serious driving safety problems.To solve the above problem, an efficient transmission and honeypot defense strategy was proposed, which was based on the offensive and defensive game in the Internet of Vehicles to reduce the risk of identity forgery attacks and improve the security of data transmission.The interaction between trusted base stations and malicious base stations in the Internet of Vehicles scenario was modeled as an attack-defense game model.On this basis, trusted base stations and honeypot base stations were jointly used as defenders to defend against malicious attacks.Then, the trusted base station and the malicious base station, as the two sides of the offensive and defensive game, chose their respective strategies to construct a model of the benefit function of both sides.Combined with the vehicle delay feedback mechanism, the defender and the malicious base station dynamically adjusted their respective strategies.By adjusting the interaction between the honeypot base station and the vehicle, and also the degree of IP randomization, the overall benefit of the defender was effectively improved.Besides, the optimal solution was obtained by using the mixed strategy Nash equilibrium theory.Simulation experimental results show that the proposed strategy can improve the secure transmission performance of the Internet of Vehicles service in the presence of malicious attackers, and the defender’s expected benefit is improved by 48.9% and the data transmission delay is reduced by 57.1% compared to the no-honeypot defense scheme.

Key words: Internet of vehicles, game theory, honeypot strategy, offensive and defensive games

CLC Number:

TP393

Jie YI, Tengfei CAO, Shuai GAO, Jianqiang HUANG. Honeypot defense and transmission strategy based on offensive and defensive games in vehicular networks[J]. Chinese Journal of Network and Information Security, 2022, 8(4): 157-167.

Figures/Tables 9

References 17

[1]	任沁沁 . 全国机动车保有量达3.95亿辆,驾驶人达4.81亿人[N]. 新华每日电讯,2022-01-12(2).
	REN Q Q . There are 395 million motor vehicles in China and 481 million drivers[N]. Xinhua Daily Telegraph,2022-01-12(2).
[2]	杨德全, 刘卫民, 俞宙 . 基于蜜罐的主动防御应用研究[J]. 网络与信息安全学报, 2018,4(1): 57-62.
	YANG D Q , LIU W M , YU Z . Research on active defense application based on honeypot[J]. Chinese Journal of Network and Information Security, 2018,4(1): 57-62.
[3]	胡永进, 马骏, 郭渊博 . 基于博弈论的网络欺骗研究[J]. 通信学报, 2018,39(S2): 9-18.
	HU Y J , MA J , GUO Y B . Research on cyber deception based on game theory[J]. Journal of Communication, 2018,39(S2): 9-18.
[4]	JAJODIA S . A probabilistic logic of cyber deception[J]. IEEE Transactions on Information Forensics and Security, 2017,12(11): 2532-2544.
[5]	石乐义, 赵俊楠, 李芹 ,等. 基于信令博弈的网络诱骗防御策略分析与仿真[J]. 系统仿真学报, 2016,28(2): 348-353.
	SHI L Y , ZHAO J N , LI Q ,et al. Signaling game analysis and simulation on network decoy defense strategies[J]. Journal of System Simulation, 2016,28(2): 348-353.
[6]	刘小虎, 张恒巍, 马军强 ,等. 基于攻防博弈的网络防御决策方法研究综述[J]. 网络与信息安全学报, 2022,8(1): 1-14.
	LIU X H , ZHANG H W , MA J Q ,et al. Research review of network defense decision-making methods basedon attack and defense game[J]. Chinese Journal of Network and Information Security, 2022,8(1): 1-14.
[7]	LA Q D , QUEK T Q S , LEE J ,et al. Deceptive attack and defense game in honeypot-enabled networks for the internet of things[J]. IEEE Internet of Things Journal, 2016,3(6): 1025-1035.
[8]	XU Q , SU Z , ZHANG K . Game theoretical secure caching scheme in multi-homing heterogeneous networks[C]// 2018 IEEE International Conference on Communications (ICC). 2018: 1-6.
[9]	YAO R , ZHANG G , FAN Y , RABIE KM , KAIWARTYA O ,et al. Untrusted relay selection and secure transmission optimization based on stack-elberg game[C]// 2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP). 2021: 534-539.
[10]	MAKARFIET A U , RABIE KM , KAIWARTYA O ,et al. Toward physical-layer security for internet of vehicles:interference-aware modeling[J]. IEEE Internet of Things Journal, 2021,8(1): 443-457.
[11]	SEDJELMACI H , BRAHMI I H , ANSARI N ,et al. M.Cyber security framework for vehicular network based on a Hierarchical Game[J]. IEEE Transactions on Emerging Topics in Computing, 2021,9(1): 429-440.
[12]	LIU B , SU Z , XU Q . Game theoretical secure wireless communication for UAV-assisted vehicular Internet of Things[J]. China Communications, 2021,18(7): 147-157.
[13]	曹腾飞, 江翠丽, 刘志强 ,等. 基于信息中心 5G 车联网中社会感知的流媒体缓存与转发策略[J]. 电信科学, 2019,35(12): 90-98.
	CAO T F , JIANG C L , LIU Z Q ,et al. Social-aware caching and forwarding for video streaming in information-centric 5G VANET[J]. Telecommunications Science, 2019,35(12): 90-98.
[14]	CAO T , XUET C . Reliable and efficient multimedia service optimization for edge computing-based 5g networks:game theoretic approaches[J]. IEEE Transactions on Network and Service Management, 2020,17(3): 1610-1625.
[15]	SUN J , SUN K . DESIR:decoy-enhanced seamless IP randomiza-tion[C]// IEEE INFOCOM 2016 - The 35th Annual IEEE Interna-tional Conference on Computer Communications. 2016.
[16]	XIE L , SU Z , CHEN N ,et al. A game theory based scheme for secure and cooperative UAV communication[C]// ICC 2021- IEEE International Conference on Communications. 2021: 1-6.
[17]	XU Q , SU Z , YU S ,et al. Trust based incentive scheme to allocate big data tasks with mobile social cloud[J]. IEEE Transactions on Big Data, 2022,8(1): 113-124.

Metrics

Recommended 0

No Suggested Reading articles found!

Honeypot defense and transmission strategy based on offensive and defensive games in vehicular networks

RichHTML

PDF下载

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 9

References 17

Related Articles 9

Metrics

Recommended 0

[1]	Bao ZHANG, Youliang TIAN, Sheng GAO. Global randomized consensus algorithm resist collusion attack based on game theory [J]. Chinese Journal of Network and Information Security, 2022, 8(4): 98-109.
[2]	Baoqin ZHAI, Jian WANG, Lei HAN, Jiqiang LIU, Jiahao HE, Tianhao LIU. Hierarchical proxy consensus optimization for IoV based on blockchain and trust value [J]. Chinese Journal of Network and Information Security, 2022, 8(3): 142-153.
[3]	Ziwen ZHAO,Ayong YE,Junlin JIN,Lingyu MENG. Trajectory privacy protection mechanism of obfuscating paths based on vehicles cooperation [J]. Chinese Journal of Network and Information Security, 2019, 5(4): 52-62.
[4]	Xinglan ZHANG,Wei ZHENG. Research on security multi-party computing based on game theory [J]. Chinese Journal of Network and Information Security, 2018, 4(1): 52-56.
[5]	Meng-hui LI,You-liang TIAN,Jin-ming FENG. Constant-round fair rational secret sharing scheme [J]. Chinese Journal of Network and Information Security, 2017, 3(1): 61-67.
[6]	Liang-min WANG,Xiao-long LIU,Chun-xiao LI,Jing YANG,Wei-dong YANG. Overview of Internet of vehicles for 5G [J]. Chinese Journal of Network and Information Security, 2016, 2(6): 1-12.
[7]	Jian-ming ZHU,Bo GAO. Social financial information security risk analysis and prevention [J]. Chinese Journal of Network and Information Security, 2016, 2(3): 46-51.
[8]	Liang-min WANG,Ting-ting LI,Long CHEN. Security issues and system structure of internet of vehicles [J]. Chinese Journal of Network and Information Security, 2016, 2(2): 41-54.
[9]	Jian-ming ZHU,Qin WANG. Analysis of cyberspace security based on game theory [J]. Chinese Journal of Network and Information Security, 2015, 1(1): 43-49.