ABSTRACT
We propose a security model for Vehicular Ad-hoc Networks (VANETs) to distinguish spurious messages from legitimate messages. In this paper, we explore the information available in a VANET environment to enable vehicles to filter out malicious messages which are transmitted by a minority of misbehaving vehicles. More specifically, we introduce a message filtering model that leverages multiple complementary sources of information to construct a multi-source detection model such that drivers are only alerted after some fraction of sources agree. Our filtering model is based on two main components: a threshold curve and a Certainty of Event (CoE) curve. A threshold curve implies the importance of an event to a driver according to the relative position, and a CoE curve represents the confidence level of the received messages. An alert is triggered when the event certainty surpasses a threshold. We analyze our model and provide some initial simulation results to demonstrate the benefits.
- }}F. Bai, T. Elbatt, G. Hollan, H. Krishnan, and V. Sadekar. Towards Characterizing and Classifying Communication-based Automotive Applications from a Wireless Networking Perspective. In IEEE AutoNet, 2006.Google Scholar
- }}F. Bai and B. Krishnamachari. Spatio-temporal Variations of Vehicle Traffic in VANETs: Facts and Implications. In ACM VANET, 2009. Google ScholarDigital Library
- }}Cambridge Systematics, Inc. Crashes vs. Congestion: What's the cost to society? http://www.aaanewsroom.net/Assets/Files/20083591910.CrashesVsCongestionFullReport2.28.08.pdf.Google Scholar
- }}K. Chang and K. Chon. A Car-Following Model Applied Reaction Times Distribution and Perceptual Threshold. Journal of the Eastern Asia Society for Transportation Studies, 6:1888--1903, 2005.Google Scholar
- }}L. Eschenauer, V. D. Gligor, and J. Baras. On Trust Establishment in Mobile Ad-Hoc Networks. In Proceedings of the Security Protocols Workshop, 2002.Google Scholar
- }}M. Ghosh, A. Varghese, A. Gupta, and A. A. Kherani. Distributed misbehavior detection in VANETs. In WCNC, 2009. Google ScholarDigital Library
- }}M. Ghosh, A. Varghese, A. Gupta, A. A. Kherani, and S. N. Muthaiah. Detecting Misbehaviors in VANET With Integrated Root-Cause Analysis. Ad Hoc Networks, 2010. Google ScholarDigital Library
- }}P. Golle, D. Greene, and J. Staddon. Detecting and Correcting Malicious Data in VANETs. In ACM VANET, 2004. Google ScholarDigital Library
- }}Y.-C. Hu and K. P. Laberteaux. Strong VANET Security on a Budget. In ESCAR, 2006.Google Scholar
- }}IBM. IBM 4764 PCI-X cryptographic coprocessor. http://www-03.ibm.com/security/cryptocards/pcixcc/order4764.shtml.Google Scholar
- }}IEEE. 1609.2: Trial-use standard for wireless access in vehicular environments-security services for applications and management messages. IEEE Standards, 2006.Google Scholar
- }}National Highway Traffic Safety Administration (NHTSA). Fatality Analysis Reporting System. http://www-fars.nhtsa.dot.gov/.Google Scholar
- }}M. Raya and J.-P. Hubaux. The security of vehicular ad hoc networks. In ACM SASN, 2005. Google ScholarDigital Library
- }}M. Raya, P. P. Papadimitratos, V. Gligor, and J.-P. Hubaux. On Data-Centric Trust Establishment in Ephemeral Ad Hoc Networks. In IEEE Infocom, 2008.Google ScholarCross Ref
- }}R. K. Schmidt, T. Leinmuller, E. Schoch, A. Held, and G. Schafer. Vehicle Behavior Analysis to Enhance Security in VANETs. In V2VCOM, 2008.Google Scholar
- }}A. Studer, F. Bai, B. Bellur, and A. Perrig. Flexible, Extensible, and Efficient VANET Authentication. In ESCAR, 2008.Google Scholar
- }}A. Studer, M. Luk, and A. Perrig. Efficient Mechanisms to Provide Convoy Member and Vehicle Sequence Authentication in VANETs. In SecureComm, 2007.Google ScholarCross Ref
- }}A. Studer, E. Shi, F. Bai, and A. Perrig. TACKing Together Efficient Authentication, Revocation, and Privacy in VANETs. In IEEE SECON, 2009. Google ScholarDigital Library
- }}Texas Transportation Institute. Urban Mobility Report. http://mobility.tamu.edu/ums/report/.Google Scholar
- }}G. Theodorakopoulos and J. S. Baras. On Trust Models and Trust Evaluation Metrics for Ad-Hoc Networks. IEEE Journal on Selected Areas in Communications, 24(2):318--328, 2006. Google ScholarDigital Library
- }}Y. Zang, L. Stibor, H.-J. Reumerman, and H. Chen. Wireless Local Danger Warning Using Inter-vehicle Communications in Highway Scenarios. In 14th European Wireless Conference, 2008.Google Scholar
Index Terms
- VANET alert endorsement using multi-source filters
Recommendations
A Probabilistic Routing Protocol in VANET
The key attribute that distinguishes Vehicular Ad hoc Networks VANET from Mobile Ad hoc Networks MANET is scale. While MANET networks involve up to one hundred nodes and are short lived, being deployed in support of special-purpose operations, VANET ...
SE-AOMDV: secure and efficient AOMDV routing protocol for vehicular communications
AbstractThe Vehicular Ad hoc Networks (VANETs) are emerging networks that provide essential services to drivers on the road. To exchange data, vehicles as network nodes route information between source and destination using the V-to-V infrastructure. To ...
Collaborative Dynamic Source Routing using transitional trust filters
The DSR protocol is frequently used to establish communication in mobile ad-hoc wireless networks. For effective functioning of the protocol it is essential that no malicious nodes should participate in its execution. In this paper, we present a novel ...
Comments