基于联合熵隐私保护的自适应动态Mix-zone方案

doi:10.11959/j.issn.1000-436x.2018038

Abstract

Abstract:

Aiming at the weak flexibility and lack of users’ transparency existing in the current Mix-zone schemes for Internet of vehicle (IoV),a dynamic was proposed for Mix-zone construction with traffic adaption,which could construct a Mix-zone for the vehicles dynamically according to the traffic conditions for changing pseudonym at anytime and anywhere.This kind of Mix-zone could achieve privacy-preserving based on the identity and location.In addition,a novel traffic-adaptive metric was presented for classifying the privacy leveled in Mix-zone,which applied the normalization quantitation to measure the degree of Mix-zone’s privacy demanding by the current region.It was verified that the joint entropy-based privacy measuring model and the Mix-zone construction scheme by utilizing the trajectory data of taxis in certain district in Shenzhen city.The experimental shows that the proposed combination entropy-based model could depict the proportional relationship between the traffic scene parameters and the privacy-preserving degrees.The scheme is better in performance over the related methods,and strikes a good balance between location privacy and service usability.

Key words: Internet of vehicle, Mix-zone, joint-entropy, privacy-preserving

CLC Number:

TP391

Xia FENG,Yawei LIU. Dynamic Mix-zone scheme with joint-entropy based metric for privacy-perserving in IoV[J]. Journal on Communications, 2018, 39(3): 76-85.

Figures/Tables 7

References 23

[1]	LIU X , ZHAO H , PAN M ,et al. Traffic-aware multiple mix zone placement for protecting location privacy[C]// IEEE INFOCOM. 2012: 972-980.
[2]	ZHANG L , WU Q , QIN B ,et al. Practical secure and privacy-preserving scheme for value-added applications in VANETs[J]. Computer Communications, 2015,71: 50-60.
[3]	刘怡良, 石亚丽, 冯蒿 ,等. 车联网中基于神经网络的入侵检测方案[J]. 通信学报, 2014,72(35): 233-239.
	LIU Y L , SHI Y L , FENG G . Intrusion detection scheme based on neural network in vehicle network[J]. Journal of Communications, 2014,72(35): 233-239.
[4]	FERRAG M , MAGLARAS L , AHMIM A . Privacy-preserving schemes for Ad Hoc social networks:a survey[J]. IEEE Transaction on Communications Surveys ＆ Tutorials, 2017,19(4): 3015-3045.
[5]	LU R , LIN X , LUAN T H ,et al. Pseudonym changing at social spots:an effective strategy for location privacy in VANETs[J]. IEEE Transactions on Vehicular Technology, 2012,61(1): 86-96.
[6]	LIU Y , WANG L , CHEN H H . Message authentication using proxy vehicles in vehicular ad hoc networks[J]. IEEE Transactions on Vehicular Technology, 2015,64(8): 3697-3710.
[7]	BERESFORD A R , STAJANO F . Mix zones:user privacy in location-aware services[C]// IEEE Conference on Pervasive Computing and Communications Workshops. 2004: 127-132.
[8]	BUTTYAN L , HOLCZER T , VAJDA I . On the effectiveness of changing pseudonyms to provide location privacy in VANETs[C]// European Conference on Security and Privacy in Ad-Hoc and Sensor Networks. 2007: 129-141.
[9]	YING B , MAKRAKIS D . Pseudonym changes scheme based on candidate-location-list in vehicular networks[C]// IEEE International Conference on Communications. 2015: 7292-7297.
[10]	LU R , LIN X , LUAN T H ,et al. Pseudonym changing at social spots:an effective strategy for location privacy in VANETs[J]. IEEE Transactions on Vehicular Technology, 2012,61(1): 86-96.
[11]	BUTTYAN L , HOLCZER T , WEIMERSKIRCH A ,et al. SLOW:a practical pseudonym changing scheme for location privacy in VANETs[C]// IEEE Vehicular Networking Conference. 2010: 1-8.
[12]	DAHL M , DELAUNE S , STEEL G . Formal analysis of privacy for vehicular mix-zones[C]// European Symposium on Research in Computer Security Computer Security(ESORICS2010). 2010: 55-70.
[13]	GUO N , MA L , GAO T . Independent mix zone for location privacy in vehicular networks[J].IEEE Access,doi:10.1109/ACCESS.2018.2800907. IEEE Access,doi:10.1109/ACCESS. 2018.2800907.
[14]	SCHEUER F , FUCHS K P , FEDERRATH H . A safety-preserving mix zone for VANETs[C]// International Conference on Trust,Privacy and Security. 2011: 37-48.
[15]	PALANISAMY B , LIU L . Attack-resilient mix-zones over road networks:architecture and algorithms[J]. IEEE Transactions on Mobile Computing, 2014,14(3): 495-508.
[16]	PALANISAMY B , LIU L . MobiMix:protecting location privacy with mix-zones over road networks[C]// International Conference on Data Engineering. 2011: 494-505.
[17]	SAMPIGETHAYA K , LI M Y , HUANG L P ,et al. Amoeba:robust location privacy scheme for VANET[J]. IEEE Journal on Selected Areas in Communications, 2007,25(8): 1569-1589.
[18]	EMARA K . Safety-aware location privacy in VANET:evaluation and comparison[J]. IEEE Transactions on Vehicular Technology, 2017,66(12): 10718-10731.
[19]	ZENG S , CHEN Y , TAN S ,et al. Concurrently deniable ring authentication and its application to LBS in VANETs[J]. Peer-to-Peer Networking and Applications, 2016,10(4): 1-13.
[20]	HOSMA M . A study of the source traffic generator using poisson distribution for ABR service[J]. Modelling and Simulation in Engineering. 2012(1): 1-6.
[21]	JAYNES E T . Information theory and statistical mechanics[J]. Physical Review, 1957,106(4): 620-630.
[22]	DAN B , BOYEN X , SHACHAM H . Short group signatures[J]. Advances in Cryptology-CRYPTO, 2004,22(6): 41-55.
[23]	刘亚伟 . VANETs中安全认证与隐私保护的研究[D]. 合肥:安徽大学, 2017.
	LIU Y W . Research on security authentication and privacy preservation in VANETs[D]. Hefei:Anhui University, 2017.

Metrics

Recommended 0

No Suggested Reading articles found!

标识符	描述
P_r[X\|t]	t_a 时刻车辆进入Mix-zone的概率
Γ_v	车辆的存续时间
C	Mix-zone的等级域
Δ	车辆隐私保护影响因子向量
M_ij	车辆节点隐私评估概率矩阵
Al_×n	Mix-zone指标标准化矩阵
Δt	Mix-zone存续时长
H	Mix-zone联合熵
C(Mix-zone)	Mix-zone隐私等级

Dynamic Mix-zone scheme with joint-entropy based metric for privacy-perserving in IoV

RichHTML

PDF

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 7

References 23

Related Articles 15

Metrics

Recommended 0

[1]	Haibo ZHANG, Yukun CAO, Kaijian LIU, Ruyan WANG. Distributed trust management scheme based on blockchain in Internet of vehicles [J]. Journal on Communications, 2023, 44(5): 148-157.
[2]	Xuejiao LIU, Qiang ZHONG, Yingjie XIA. Efficient authentication scheme for cross-trust domain of IoV based on double-layer shard blockchain [J]. Journal on Communications, 2023, 44(5): 213-223.
[3]	Yingjie XIA, Siyu ZHU, Xuejiao LIU. Research on efficient cross trust-domain group authentication with conditional privacy of vehicle platoon under blockchian architecture [J]. Journal on Communications, 2023, 44(4): 111-123.
[4]	Lei ZHANG, Yu WANG, Jianjie TIAN, Lin ZHANG, Tianjiao ZHANG. Joint beam forming design for IRS-aided MIMO Internet of vehicles system [J]. Journal on Communications, 2023, 44(2): 59-69.
[5]	Shengxing YU, Zhong CHEN. Efficient secure federated learning aggregation framework based on homomorphic encryption [J]. Journal on Communications, 2023, 44(1): 14-28.
[6]	Rong ZENG, Xiao HANG. Reconfigurable intelligent surface assist wireless channel estimation algorithm in Internet of vehicles environment [J]. Journal on Communications, 2022, 43(8): 142-150.
[7]	Xiang CHENG, Haotian ZHANG, Zonghui YANG, Ziwei HUANG, Sijiang LI, Anlan YU. Integrated sensing and communications for Internet of vehicles：current status and development trend [J]. Journal on Communications, 2022, 43(8): 188-202.
[8]	Peng QIN, Haoting HE, Xiongwen ZHAO, Yang FU, Yu ZHANG, Miao WANG, Shuo WANG, Xue WU. Efficient resource allocation with context-awareness for parked car road side unit-based Internet of vehicles [J]. Journal on Communications, 2022, 43(7): 113-125.
[9]	Yanfei SUN, Jiazheng YIN, Jin QI, Xiaoxuan HU, Mengting CHEN, Zhenjiang DONG. Topology control based on dynamic graph embedding in Internet of vehicles [J]. Journal on Communications, 2022, 43(6): 133-142.
[10]	Sifeng ZHU, Jianghao CAI, Zhengyi CHAI, Enlin SUN. Multi-objective optimal offloading decision for cloud-edge collaborative computing scenario in Internet of vehicles [J]. Journal on Communications, 2022, 43(6): 223-234.
[11]	Haining YU, Hongli ZHANG, Xiangzhan YU, Jiaxing QU, Mengmeng GE. Privacy-preserving trajectory similarity computation method [J]. Journal on Communications, 2022, 43(11): 1-13.
[12]	Tao PENG, Wentao ZHONG, Guojun WANG, Entao LUO, Jinbo XIONG, Yining LIU, Wang Hao. Privacy-preserving precise profile matching in mobile social network [J]. Journal on Communications, 2022, 43(11): 90-103.
[13]	Rui SHI, Huamin FENG, Huiqin XIE, Guozhen SHI, Biao LIU, Yang YANG. Privacy-preserving attribute ticket scheme based on mobile terminal with smart card [J]. Journal on Communications, 2022, 43(10): 26-41.
[14]	Yuliang CONG, Wenxi SUN, Ke XUE, Zhihong QIAN, Mianshu CHEN. Research on task offloading strategy of Internet of vehicles based on improved hybrid genetic algorithm [J]. Journal on Communications, 2022, 43(10): 77-85.
[15]	Jinbo XIONG, Yongjie ZHOU, Renwan BI, Liang WAN, Youliang TIAN. Towards edge-collaborative, lightweight and privacy-preserving classification framework [J]. Journal on Communications, 2022, 43(1): 127-137.