Mix-Zones for Location Privacy in Vehicular Networks

1. Mix-Zones for Location Privacy in Vehicular Networks Julien Freudiger Maxim Raya, Márk Félegyházi, Panos Papadimitratos, and Jean-Pierre Hubaux August 14, 2007 WiN-ITS, Vancouver, BC, Canada

2. Motivation Safety messages • Position (p) • Speed (s) • Acceleration (a) Authenticated • Digital Signature • Certificate

3. No location privacy

4. Outline • System and Threat Model • Mix-Zones • Vehicular Mix-Networks • Simulation Results

5. Vehicular Networks • Safety Messages • (p,s,a) • Timestamp • Authenticated • Certification Authority (CA) • CA distributes public/private key pairs (Ki,j,Ki,j-1) with j=1,…,F to each vehicle i • F is the size of the set of key pairs • Public keys certificates are referred to as pseudonyms => Vehicles are preloaded with a large set of pseudonyms and key pairs • Vehicles have tamper proof devices that guarantee the • Correct execution of cryptographic operations • Non-disclosure of private keying material

6. Adversary We assume an external, global, and passive adversary • Installs its own radio receivers • Collects GPS coordinates and pseudonyms of safety messages • Links pseudonym changes using GPS coordinates • WiFi operator (e.g., Google, EarthLink) • WiFicommunity network (e.g.,FON) [http://www.earthlink.net/wifi/cities/]

7. Mix-Zone Definition (1) A mix-zone is a restricted region where users cannot be located Entering event k = (n,) i.e., from road n at time  Exiting event l = (e,’) i.e., from road e at time ’ • Adversary has statistical information about mix-zones • pn,e = Prob(“Vehicle enters from road n and exits from road e”) • qn,e(t) = Prob(“Time spent between road n and e is t”) • Statistical information depends on • The geometry of the mix-zone • The location of the mix-zone in the network topology

8. Mix-Zone Definition (2) • Mix-zones obscure the relation of incoming and outgoing vehicles • Unlinkability • An adversary estimates the mapping of entering and exiting events • With two vehicles • The probability of a mapping depends on the geometry of the mix-zone

9. Mix-Zone Effectiveness Entropy measures uncertainty of mapping • N models the mix-zone density • (pn,e, qn,e(t)) models the unpredictability of vehicles’ whereabouts where N= # of mobiles in the mix-zone

10. Where to create Mix-Zones? Best mix-zone • High N • High vehicle whereabouts unpredictability (pn,e, qn,e(t)) Road intersections

11. High Uncertainty

12. How to create a mix-zone? • Cryptographic Mix-zone (CMIX) • Encrypt Safety Messages (with a symmetric key SK) • Computational security

13. CMIX Protocol(1) Key Establishment Rely on presence of RSU at road intersection to establish a symmetric key Request, Ts, Signi(Request,Ts), Certi,k EKi,j(vi, SK, Ts, SignRSU(vi, SK, Ts)), CertRSU Ack, Ts, Signi(Ack,Ts), Certi,k SK = Symmetric Key Ts = Time stamp Signi = Signature of i Certi,k = Certificate of i

14. CMIX Protocol(2) Key Forwarding • V2 unable to obtain key directly from RSU, thus to decrypt messages from V1 • RSU leverages on vehicles already in the mix-zone to forward symmetric key • V2 broadcasts key requests until any vehicle in the mix-zone replies • Vehicles do not encrypt their messages before entering the mix-zone EK2,j(v2, v1, SK,Ts, SignRSU(v1, SK, Ts))

15. CMIX Protocol(3) Key Update • RSU initiates key update to • renew keys • revoke keys • Update is triggered when • Mix-zone is empty • CA is informed of new SK for liability issues • Asynchronous key updates across mix-zones improve system security

16. Vehicular Mix-Network Mix-network cumulative entropy for vehicle v where L= Length of the path in the mix-network

17. Simulation Setup • 10X10 Manhattan network with 4 roads/intersection • N ~ Poisson() vehicles per intersection at network initialization • Vehicle inter arrival time  ~ Uniform[0,T] models • High traffic congestion • Low traffic congestion • Intersection characteristics • qn,e(t) ~ N(n,e, n,e) for each intersection • pn,e randomly chosen for each intersection

18. Vehicular Mix-Zone • Both network density and congestion affect the achievable location privacy • Confidence intervals are small because there is low variability within one mix-zone

19. Vehicular Mix-Network • Larger confidence interval due to varying number of vehicles and varying set of traversed mix-zones • Tracking probability is quickly insignificant Mix-zones effectiveness is high

20. Conclusions • Mix-zone effectiveness depends on • Intersection’s congestion • Vehicle’s density • Vehicles’ whereabouts unpredictability • Vehicular mix-network effectiveness • Has large variance • But is overall high • Need more simulations • With realistic traffic traces • Efficiency of vehicular mix-network is independent of CMIX protocol • Alternative CMIX protocols could exploit location

21. References • L. Buttyán, T. Holczer, and I. Vajda. On the Effectiveness of Changing Pseudonyms to Provide Location Privacy in VANETs. ESAS 2007 • A. R. Beresford. Mix-zones: User privacy in location-aware services. PerSec 2004 • L. Huang, K. Matsuura, H. Yamane, and K. Sezaki. Silent cascade: Enhancing location privacy without communication QoS degradation. SPC 2005 • M. Li, K. Sampigethaya, L. Huang, and R. Poovendran. Swing & Swap: User-centric Approaches Towards Maximizing Location Privacy. WPES 2006 • M. Raya, P. Papadimitratos, and J.-P. Hubaux. Securing Vehicular Communications. IEEE Wireless Communications magazine, 2006

22. CMIX Protocol Analysis • Transmission Complexity • Key requests scale with network condition • Avoid key reply flooding by backoff mechanism and key acknowledgement • Computational Complexity • The number of exponentiations is manageable • Load is shared among vehicles in the CMIX • Security • Impersonation/Instantiation attacks are unfeasible • Denial of service attacks are hard • Cost to become internal adversary is high