Jason Haas, Global Revocation for the Intersection Collision Warning Safety Application
Identifying and removing malicious insiders from a network is a topic ofactive research. Vehicular ad hoc networks (VANETs) may suffer frominsider attacks; that is, an attacker may use authorized vehicles toattack other vehicles. Specifically, attackers may use their vehicles tobroadcast specially formed packets that will trigger warnings in targetvehicles. This malicious behavior could have a significant detrimentaleffect on cooperative safety applications (SAs), one of the driving forcesbehind VANET deployment.We propose modifications to the intersection collision warning (ICW) SAthat enable a certificate authority (CA) to be offline and yet to decideto revoke a vehicle's certificates using retransmitted information thatcannot repudiated. Our approach differs from previous proposals in thatit is SA specific, and it is resilient to Sybil attacks. We simulate andmeasure the resources an attacker requires to attack a vehicle using theICW SA without our modifications and demonstrate that our additions reducethe false positive rate arising from errors in estimated vehicle dynamics. About the speaker: Jason J. Haas graduated from the University of Wisconsin-Madison with hisB.S. in Electrical and Computer Engineering (ECE) and Physics. Hereceived his M.S. in 2007 and his PhD in 2010 in ECE from the Universityof Illinois at Urbana-Champaign. His dissertation was on security andprivacy for vehicular ad hoc networks supportingrevocation. Jason has worked on defining security mechanisms forvehicular ad hoc networks, participating in the Crash Avoidance MetricsPartnership's (CAMP) Vehicular Safety Communications (VSC) program as acontractor. Jason has also done work on commercial vehicle controlsystems and cyber security for commercial vehicles. Currently, Jason is aSenior Member of the Technical Staff at Sandia National Laboratories inAlbuquerque, New Mexico, where he continues to conduct research onsecurity for vehicular ad hoc networks.
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