A survey of attacks and detection mechanisms on intelligent transportation systems: VANETs and IoV

Vehicular ad hoc networks (VANETs) have become one of the most promising and fastest growing subsets of mobile ad hoc networks (MANETs). They are comprised of smart vehicles and roadside units (RSU) which communicate through unreliable wireless media. By their very nature, they are very susceptible to attacks which may result in life-endangering situations. Due to the potential for serious consequences, it is vital to develop security mechanisms in order to detect such attacks against VANETs. This paper aims to survey such possible attacks and the corresponding detection mechanisms that are proposed in the literature. The attacks are classified and explained along with their effects, and the solutions are presented together with their advantages and disadvantages. An evaluation and summary table which provides a holistic view of the solutions surveyed is also presented.

[1]  Xinlei Zhang,et al.  Using trust model to ensure reliable data acquisition in VANETs , 2017, Ad Hoc Networks.

[2]  Sidi-Mohammed Senouci,et al.  An accurate and efficient collaborative intrusion detection framework to secure vehicular networks , 2015, Comput. Electr. Eng..

[3]  David Kotz,et al.  AnonySense: Opportunistic and Privacy-Preserving Context Collection , 2009, Pervasive.

[4]  Suresh Limkar,et al.  Performance Investigation of DMV (Detecting Malicious Vehicle) and D&PMV (Detection and Prevention of Misbehave/Malicious Vehicles): Future Road Map , 2013, FICTA.

[5]  John R. Douceur,et al.  The Sybil Attack , 2002, IPTPS.

[6]  Lars C. Wolf,et al.  Using Cluster Analysis to Detect Attackers in Vehicular Delay Tolerant Networks , 2013, ADHOCNETS.

[7]  Mihai Dimian,et al.  A survey on the usage of DSRC and VLC in communication-based vehicle safety applications , 2014, 2014 IEEE 21st Symposium on Communications and Vehicular Technology in the Benelux (SCVT).

[8]  Mikhail Nesterenko,et al.  Secure Location Verification Using Radio Broadcast , 2004, IEEE Transactions on Dependable and Secure Computing.

[9]  Karan Verma,et al.  Bloom-filter based IP-CHOCK detection scheme for denial of service attacks in VANET , 2015, Secur. Commun. Networks.

[10]  Ashok Kumar,et al.  Prevention of DoS Attacks in VANET , 2013, Wireless Personal Communications.

[11]  Carlos Miguel Tavares Calafate,et al.  TFDD: A trust-based framework for reliable data delivery and DoS defense in VANETs , 2017, Veh. Commun..

[12]  Bin Xiao,et al.  Detection and localization of sybil nodes in VANETs , 2006, DIWANS '06.

[13]  Xin Zhang,et al.  VANET alert endorsement using multi-source filters , 2010, VANET '10.

[14]  Vimal Bibhu,et al.  Performance Analysis of Black Hole Attack in Vanet , 2012 .

[15]  Xin Wang,et al.  A Robust Detection of the Sybil Attack in Urban VANETs , 2009, 2009 29th IEEE International Conference on Distributed Computing Systems Workshops.

[16]  Tim Leinmüller,et al.  Vehicle Behavior Analysis to Enhance Security in VANETs , 2008 .

[17]  Sherali Zeadally,et al.  Security attacks and solutions for vehicular ad hoc networks , 2010, IET Commun..

[18]  David Chaum,et al.  Distance-Bounding Protocols (Extended Abstract) , 1994, EUROCRYPT.

[19]  Jelena V. Misic,et al.  A Cross-Layer Approach to Privacy-Preserving Authentication in WAVE-Enabled VANETs , 2013, IEEE Transactions on Vehicular Technology.

[20]  Kpatcha M. Bayarou,et al.  Intrusion detection in VANETs through verification of vehicle movement data , 2010, 2010 IEEE Vehicular Networking Conference.

[21]  Peng Ning,et al.  How to misuse AODV: a case study of insider attacks against mobile ad-hoc routing protocols , 2003, Ad Hoc Networks.

[22]  Bo Yu,et al.  Detecting Sybil attacks in VANETs , 2013, J. Parallel Distributed Comput..

[23]  Peng Ning,et al.  P2DAP — Sybil Attacks Detection in Vehicular Ad Hoc Networks , 2011, IEEE Journal on Selected Areas in Communications.

[24]  Phillip A. Porras,et al.  Highly Predictive Blacklisting , 2008, USENIX Security Symposium.

[25]  Peter Mell,et al.  Intrusion Detection Systems , 2001 .

[26]  Panagiotis Papadimitratos,et al.  Eviction of Misbehaving and Faulty Nodes in Vehicular Networks , 2007, IEEE Journal on Selected Areas in Communications.

[27]  Zhiyi Fang,et al.  Securing Vehicular Ad Hoc Networks , 2007, 2007 2nd International Conference on Pervasive Computing and Applications.

[28]  Pietro Manzoni,et al.  Evaluating the Usefulness of Watchdogs for Intrusion Detection in VANETs , 2010, 2010 IEEE International Conference on Communications Workshops.

[29]  Ch. Ramesh Babu,et al.  Internet of Vehicles: From Intelligent Grid to Autonomous Cars and Vehicular Clouds , 2016 .

[30]  John A. Clark,et al.  Intrusion Detection in Mobile Ad Hoc Networks , 2009, Guide to Wireless Ad Hoc Networks.

[31]  Ivan Stojmenovic,et al.  On Data-Centric Misbehavior Detection in VANETs , 2011, 2011 IEEE Vehicular Technology Conference (VTC Fall).

[32]  Athanasios V. Vasilakos,et al.  Mobile Crowd Sensing for Traffic Prediction in Internet of Vehicles , 2016, Sensors.

[33]  Bertrand Ducourthial,et al.  On the Sybil attack detection in VANET , 2007, 2007 IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems.

[34]  Gongjun Yan,et al.  General Active Position Detectors Protect VANET Security , 2011, 2011 International Conference on Broadband and Wireless Computing, Communication and Applications.

[35]  Adrian Perrig,et al.  Efficient mechanisms to provide convoy member and vehicle sequence authentication in VANETs , 2007, 2007 Third International Conference on Security and Privacy in Communications Networks and the Workshops - SecureComm 2007.

[36]  Peng Ning,et al.  Privacy-Preserving Detection of Sybil Attacks in Vehicular Ad Hoc Networks , 2007, 2007 Fourth Annual International Conference on Mobile and Ubiquitous Systems: Networking & Services (MobiQuitous).

[37]  Sanjay Silakari,et al.  Detection of Malicious Nodes (DMN) in Vehicular Ad-Hoc Networks☆ , 2015 .

[38]  T. Leinmüller,et al.  Greedy Routing in Highway Scenarios : The Impact of Position Faking Nodes , 2006 .

[39]  Stefan Axelsson,et al.  Intrusion Detection Systems: A Survey and Taxonomy , 2002 .

[40]  Markus Jakobsson,et al.  Stealth attacks on ad-hoc wireless networks , 2003, 2003 IEEE 58th Vehicular Technology Conference. VTC 2003-Fall (IEEE Cat. No.03CH37484).

[41]  Yih-Chun Hu,et al.  Packet leashes: a defense against wormhole attacks in wireless networks , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[42]  Bo Sun.  Intrusion detection in mobile ad hoc networks , 2004 .

[43]  Vijay Laxmi,et al.  Misbehavior Detection Based on Ensemble Learning in VANET , 2011, ADCONS.

[44]  Akbar Ghaffar Pour Rahbar,et al.  Detection of malicious vehicles (DMV) through monitoring in Vehicular Ad-Hoc Networks , 2011, Multimedia Tools and Applications.

[45]  Omar Abdel Wahab,et al.  VANET QoS-OLSR: QoS-based clustering protocol for Vehicular Ad hoc Networks , 2013, Comput. Commun..

[46]  ByungKwan Lee,et al.  A DTSA (Detection Technique against a Sybil Attack) Protocol using SKC (Session Key based Certificate) on VANET , 2013 .

[47]  Juan-Carlos Cano,et al.  T-VNets: A novel trust architecture for vehicular networks using the standardized messaging services of ETSI ITS , 2016, Comput. Commun..

[48]  Nai-Wei Lo,et al.  Illusion Attack on VANET Applications - A Message Plausibility Problem , 2007, 2007 IEEE Globecom Workshops.

[49]  Iftikhar Ahmad,et al.  Classes of attacks in VANET , 2011, 2011 Saudi International Electronics, Communications and Photonics Conference (SIECPC).

[50]  Frank Stajano,et al.  The Resurrecting Duckling: security issues for ubiquitous computing , 2002, S&P 2002.

[51]  Sevil Sen,et al.  A Survey of Intrusion Detection Systems Using Evolutionary Computation , 2015 .

[52]  C. N. Brorn,et al.  WHO? , 1896 .

[53]  Azzam Mourad,et al.  Detecting attacks in QoS-OLSR protocol , 2013, 2013 9th International Wireless Communications and Mobile Computing Conference (IWCMC).

[54]  Alejandro Quintero,et al.  VANET security surveys , 2014, Comput. Commun..

[55]  Gongjun Yan,et al.  Providing VANET security through active position detection , 2007, VANET '07.

[56]  Peter Friess,et al.  Internet of Things Strategic Research Roadmap , 2011 .

[57]  Jie Wu,et al.  Thwarting Blackhole Attacks in Disruption-Tolerant Networks using Encounter Tickets , 2009, IEEE INFOCOM 2009.

[58]  Xia Feng,et al.  A method for defensing against multi-source Sybil attacks in VANET , 2017, Peer-to-Peer Netw. Appl..

[59]  Naveen K. Chilamkurti,et al.  Collaborative trust aware intelligent intrusion detection in VANETs , 2014, Comput. Electr. Eng..

[60]  David Antolino Rivas,et al.  Security on VANETs: Privacy, misbehaving nodes, false information and secure data aggregation , 2011, J. Netw. Comput. Appl..

[61]  Jizhong Zhao,et al.  Footprint: Detecting Sybil Attacks in Urban Vehicular Networks , 2012, IEEE Transactions on Parallel and Distributed Systems.

[62]  Lars C. Wolf,et al.  A Misbehavior Detection System for Vehicular Delay Tolerant Networks , 2012, GI-Jahrestagung.

[63]  Srdjan Capkun,et al.  The security and privacy of smart vehicles , 2004, IEEE Security & Privacy Magazine.

[64]  Aikaterini Mitrokotsa,et al.  Evaluation of classification algorithms for intrusion detection in MANETs , 2012, Knowl. Based Syst..

[65]  Sami Muhaidat,et al.  Novel cross layer detection schemes to detect blackhole attack against QoS-OLSR protocol in VANET , 2016, Veh. Commun..

[66]  Mary Baker,et al.  Mitigating routing misbehavior in mobile ad hoc networks , 2000, MobiCom '00.

[67]  Al-Sakib Khan Pathan.  Security of Self-Organizing Networks: MANET, WSN, WMN, VANET , 2010 .

[68]  Tarek Saadawi,et al.  DoS attack detection in Internet-connected vehicles , 2013, 2013 International Conference on Connected Vehicles and Expo (ICCVE).

[69]  Vijay Laxmi,et al.  Machine Learning Approach for Multiple Misbehavior Detection in VANET , 2011, ACC.

[70]  Sidi-Mohammed Senouci,et al.  A distributed detection and prevention scheme from malicious nodes in vehicular networks , 2016, Int. J. Commun. Syst..

[71]  Peng Yue,et al.  VANET 2.0: Integrating Visible Light with Radio Frequency Communications for Safety Applications , 2016, ICCCS.

[72]  Jessica Staddon,et al.  Detecting and correcting malicious data in VANETs , 2004, VANET '04.

[73]  Omar Abdel Wahab,et al.  A Dempster–Shafer Based Tit-for-Tat Strategy to Regulate the Cooperation in VANET Using QoS-OLSR Protocol , 2014, Wirel. Pers. Commun..

[74]  Tim Leinmüller,et al.  POSITION VERIFICATION APPROACHES FOR VEHICULAR AD HOC NETWORKS , 2006, IEEE Wireless Communications.

[75]  Edward W. Knightly,et al.  Denial of service resilience in ad hoc networks , 2004, MobiCom '04.

[76]  Wolfgang Banzhaf,et al.  The use of computational intelligence in intrusion detection systems: A review , 2010, Appl. Soft Comput..

[77]  Vijay Laxmi,et al.  A sybil attack detection approach using neighboring vehicles in VANET , 2011, SIN '11.

[78]  Mina Rahbari,et al.  Efficient Detection of Sybil Attack Based on Cryptography in Vanet , 2011, ArXiv.

[79]  Yu Cheng,et al.  Cooperative Sybil Attack Detection for Position Based Applications in Privacy Preserved VANETs , 2011, 2011 IEEE Global Telecommunications Conference - GLOBECOM 2011.

[80]  C. Adjih,et al.  Attacks Against OLSR : Distributed Key Management for Security , 2022 .

[81]  Jie Zhang,et al.  A Survey on Trust Management for VANETs , 2011, 2011 IEEE International Conference on Advanced Information Networking and Applications.

[82]  Panagiotis Papadimitratos,et al.  Fast Exclusion of Errant Devices from Vehicular Networks , 2008, 2008 5th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks.

[83]  Lars C. Wolf,et al.  Detecting blackhole and greyhole attacks in vehicular Delay Tolerant Networks , 2013, 2013 Fifth International Conference on Communication Systems and Networks (COMSNETS).

[84]  Jelena V. Misic,et al.  DDoS attack on WAVE-enabled VANET through synchronization , 2012, 2012 IEEE Global Communications Conference (GLOBECOM).

[85]  Damla Turgut,et al.  Defense against Sybil attack in vehicular ad hoc network based on roadside unit support , 2009, MILCOM 2009 - 2009 IEEE Military Communications Conference.

[86]  Sami Muhaidat,et al.  Cooperative cross layer detection for blackhole attack in VANET-OLSR , 2014, 2014 International Wireless Communications and Mobile Computing Conference (IWCMC).

[87]  Muttukrishnan Rajarajan,et al.  Host-Based Intrusion Detection for VANETs: A Statistical Approach to Rogue Node Detection , 2016, IEEE Transactions on Vehicular Technology.

[88]  Jamal Bentahar,et al.  CEAP: SVM-based intelligent detection model for clustered vehicular ad hoc networks , 2016, Expert Syst. Appl..

[89]  Preeti Nagrath,et al.  Protocols for mitigating blackhole attacks in delay tolerant networks , 2016, Wirel. Networks.

[90]  Adrian Perrig,et al.  Challenges in Securing Vehicular Networks , 2005 .

[91]  Mauro Biagi,et al.  Smart Vehicles, Technologies and Main Applications in Vehicular Ad hoc Networks , 2013 .

[92]  Arobinda Gupta,et al.  Detecting misbehaviors in VANET with integrated root-cause analysis , 2010, Ad Hoc Networks.