Computer Science ›› 2019, Vol. 46 ›› Issue (4): 177-182.doi: 10.11896/j.issn.1002-137X.2019.04.028

• Information Security • Previous Articles     Next Articles

Security Analysis on VANETs Authentication Schemes:CPAV and ABV

WANG Qing-long, QIAO Rui, DUAN Zong-tao   

  1. School of Information Engineering,Chang’an University,Xi’an 710064,China
  • Received:2018-02-26 Online:2019-04-15 Published:2019-04-23

Abstract: Recently,many different anonymous authentication schemes have been proposed for privacy protection of vehicles in vehicular ad hoc networks (VANETs).In 2018,Vijayakumar et al.proposed a computationally efficient privacy preserving anonymous authentication scheme for VANETs (CPAV) and anonymous batch authentication scheme for VANETs (ABV).The schemes can achieve anonymous mutual authentication between the vehicle and the road side unit(RSU),as well as anonymous batch authentication of vehicle by the RSU,and resist bogus attacks,forgery attack,and associated attacks.TA (Trusted Agency) can track the true identity of registered vehicles when necessary.This paper deeply analyzed the security of CPAV and ABV.In CPAV scheme,the external attackers are fully able to successfully conduct bogus attack and forgery attack,which proves that this scheme does not satisfy non-repudiation,nor can it conduct conditional tracking for vehicles.In addition,because the anonymous identity used in the scheme is unique,the scheme cannot resist the associated attacks,which indicates that this scheme doesn’t possess the so-calledunlinkability.At last,it’s also proved that the anonymous batch authentication (ABV) scheme can’t resist forgery attack.

Key words: Anonymous authentication, Associated attack, Bogus attack, Conditional tracking, Forgery attack, Privacy preserving, Vehicular ad hoc networks (VANETs)

CLC Number: 

  • TP309.7
[1]AZIMI R,BHATIA G,RAJKUMAR R,et al.Vehicular networks for collision avoidance at intersections[C]∥SAE world congress & exhibition.Carnegie Mellon University:Priyantha Mudalige,2011:406-416.
[2]TANGADE S S,MANVI S S.A survey on attacks,security and trust management solutions in VANETs[C]∥4th IEEE International Conference on Computing,Communications nad Networking Technologies.Tiruchengode:IEEE Computer Society,2013:105-112.
[3]JIANG S R,ZHU X Y,WANG L M.An Efficient Anonymous Batch Authentication Scheme Based on HMAC for VANETs.IEEE Transactions on Intelligent Transportation Systems,2016,17(8):2193-2205.
[4]AI-SULTAN S M,AI-DOORI M H,AI-BAYATTI A,et al.A comprehensive survey on vehicular ad hoc network. Journal of Network and Computer Applications,2014,37(1):380-392.
[5]QU F Z,WU Z H,WANG F Y,et al.A security and privacy review of VANETs.IEEE Transactions on Intelligent Transportation Systems,2015,16(6):2985-2996.
[6]ZENG S K,HUANG Y,LIU X W.Privacy-preserving Communication for VANETs with Conditionally Anonymous Ring Signature[J].International Journal of Network Security,2015,9(12):135-141.
[7]JIANG Y C,JI Y,LIU T H.An Anonymous Communication Scheme based on Ring Signature in VANETs[OL].
[8]LIN X,SUN X,HO P H,et al.GSIS:A secure and privacy pre- serving protocol for vehicular communications[J].IEEE Tran-sactions on Vehicular Technology,2007,56(6):3442-3456.
[9]ZHANG L,WU Q,SOLANS A,et al.A scalable robust authentication protocol for secure vehicular communications[J].IEEE Transactions On Vehicular Technology,2009,59(4):1606-1617.
[10]ZHANG C X,LU R X,LIN X D,et al.An efficient identity based batch verification scheme for vehicular sensor networks[C]∥International Conference on Computer Communications-2008.Phoenix:IEEE Press,2008:816-824.
[11]KILTZ E,PIETRZAK K.Leakage resilient elgamalencryption∥International Conference on the Theory and Application of Cryptology and Information Security.Springer:Computer Science,2010:595-612.
[12]ZHANG L,WU Q H,QIN B,et al.APPA:Aggregate privacy-preserving authentication in vehicular ad hoc networks∥International Conference on Information Security.Springer:Computer Science,2011:293-308.
[13]ZHANG L,WU Q H,DOMINGO-FERRER J,et al.Distributed Aggregate Privacy-Preserving Authentication in VANETs[J].IEEE Transactions on Intelligent Transportation Systems,2017,18(3):516-526.
[14]ZHU X Y,JIANG S R,WANG L G,et al.Efficient Privacy-Preserving Authentication for Vehicular Ad Hoc Networks[J].IEEE Transactions on Vehicular Technology,2014,63(2):907-918.
[15]JIANG S R,ZHU X Y,WANG L M.An Efficient Anonymous Batch Authentication Scheme Based on HMAC for VANETs[J].IEEE Transactions on Intelligent Transportation Systems,2016,17(8):2193-2204.
[16]LO N W,TSAI J L.An Efficient Conditional Privacy-Preserving Authentication Scheme for Vehicular Sensor Networks Without Pairings[J].IEEE Transactions on Intelligent Transportation Systems,2016,17(5):1319-1328.
[17]LU R,LIN X,ZHU H,et al.ECPP:Efficient conditional privacy-preservation protocol for secure vehicular communications[C]∥IEEE Conference on Computer Communications INFOCOM 2008.Phoenix:IEEE Press,2008:1229-1237.
[18]MARA M,HUBAUX J P.Securing vehicular ad hoc networks[J].Journal of Computer Security,2007,15(1):39-68.
[19]STUDER A,SHI E,BAI F,et al.Tacking together Efficient Authentication,Revocation,and Privacy in VANETs[C]∥Proceedings of the 6th Annual IEEE Communications Society Conference on Sensor,Mesh,and Ad Hoc Communications and Networks (SECON 2009).Rome:IEEE Press,2009:22-26.
[20]VIJAYAKUMAR P,CHANG V,JEGATHA DEBORAH L,et al.Computationally efficient privacy preserving anonymous mutual and batch authentication schemes for vehicular ad hoc networks[J].Future Generation Computer System,2018,78(3):943-995.
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