A Survey on Privacy-Preserving Electronic Toll Collection Schemes for Intelligent Transportation Systems

被引:6
作者
Jolfaei, Amirhossein Adavoudi [1 ]
Boualouache, Abdelwahab [1 ]
Rupp, Andy [1 ]
Schiffner, Stefan [2 ]
Engel, Thomas [1 ]
机构
[1] Univ Luxembourg, Fac Sci Technol & Med FSTM, Dept Comp Sci, L-4365 Esch sur Alzette, Luxembourg
[2] Univ Munster, Inst Informat, D-48149 Munster, Germany
关键词
Vehicles; Security; Pricing; Roads; Privacy; Intelligent transportation systems; Consumer electronics; electronic toll collection schemes; privacy; security; MISBEHAVIOR DETECTION; SECURITY; VANETS; AUTHENTICATION; ENCRYPTION; ANONYMITY; ATTACKS; NETWORK; PAY;
D O I
10.1109/TITS.2023.3266828
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
As part of Intelligent Transportation Systems (ITS), Electronic toll collection (ETC) is a type of toll collection system (TCS) which is getting more and more popular as it can not only help to finance the government's road infrastructure but also it can play a crucial role in pollution reduction and congestion management. As most of the traditional ETC schemes (ETCS) require identifying their users, they enable location tracking. This violates user privacy and poses challenges regarding the compliance of such systems with privacy regulations such as the EU General Data Protection Regulation (GDPR). So far, several privacy-preserving ETC schemes have been proposed. To the best of our knowledge, this is the first survey that systematically reviews and compares various characteristics of these schemes, including components, technologies, security properties, privacy properties, and attacks on ETCS. This survey first categorizes the ETCS based on two technologies, GNSS and DSRC. Then under these categories, the schemes are classified based on whether they provide formal proof of security and support security analysis. We also demonstrate which schemes specifically are/are not resistant to collusion and physical attacks. Then, based on these classifications, several limitations and shortcomings in privacy-preserving ETCS are revealed. Finally, we identify several directions for future research.
引用
收藏
页码:8945 / 8962
页数:18
相关论文
共 86 条
[11]   Driving Behavior Analysis Guidelines for Intelligent Transportation Systems [J].
Azadani, Mozhgan Nasr ;
Boukerche, Azzedine .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (07) :6027-6045
[12]  
Balasch J., 2010, PROC USENIX SECUR S, V10, P63
[13]  
Balasch J, 2010, DES AUT TEST EUROPE, P867
[14]  
Baldimtsi F., 2012, PROC WORKSHOP HOT TO, P1
[15]   A hybrid machine learning model for intrusion detection in VANET [J].
Bangui, Hind ;
Ge, Mouzhi ;
Buhnova, Barbora .
COMPUTING, 2022, 104 (03) :503-531
[16]   Private eCash in Practice (Short Paper) [J].
Barki, Amira ;
Brunet, Solenn ;
Desmoulins, Nicolas ;
Gambs, Sebastien ;
Gharout, Said ;
Traore, Jacques .
FINANCIAL CRYPTOGRAPHY AND DATA SECURITY, FC 2016, 2017, 9603 :99-109
[17]   Pay as You Go: A Generic Crypto Tolling Architecture [J].
Bartolomeu, Paulo C. ;
Vieira, Emanuel ;
Ferreira, Joaquim .
IEEE ACCESS, 2020, 8 :196212-196222
[18]   An anonymous and unlinkable electronic toll collection system [J].
Borges, Ricard ;
Sebe, Francesc ;
Valls, Magda .
INTERNATIONAL JOURNAL OF INFORMATION SECURITY, 2022, 21 (05) :1151-1162
[19]  
Boualouache A., 2023, IEEE COMMUN SURVEYS, DOI [10.1109/COMST.2023.3236448, DOI 10.1109/COMST.2023.3236448]
[20]   A Survey on Pseudonym Changing Strategies for Vehicular Ad-Hoc Networks [J].
Boualouache, Abdelwahab ;
Senouci, Sidi-Mohammed ;
Moussaoui, Samira .
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2018, 20 (01) :770-790