Presented by: Vinay Amrit Agrim Nigam Gurusewak Kalra

1. Wireless Location Privacy ProtectionIn Vehicular Ad-hoc Networks(Based on research work of Joo-Han Song, Vincent W.S. Wong, and Victor C.M. Leung) Presented by: Vinay Amrit Agrim Nigam GurusewakKalra

2. What Is VANET? • Modern day vehicles are “Networks on the Wheel”. • Vehicular Communication System (VCS) • V2V and V2I are “ad-hoc" in nature. • Advantages of VCS: Information sharing, Co-operative driving, Navigation, Internet access etc. • Significant progress has been made in Intelligent Transportation System(ITS)which makes driving environment safe and efficient. • For ITS, each vehicle needs to periodically broadcast an authenticated safety message, which includes its verifiable identity, its current location, speed, and acceleration. • This Dedicated Short Range Communication System is Vehicular Ad-hoc Network.

3. Why Location Privacy Protection? • Broadcast messages may be used by the adversaries for unauthorized location tracking. • Broadcast messages can be used by attackers to determine the locations visited by the vehicles over a period of time using an external Wi-Fi network. • Protecting the location privacy of vehicles is important. • Lack of privacy may hinder the wide acceptance of VANET technology.

4. Privacy Protection Schemes • Policy-based scheme: • Vehicles specify their location privacy preferences as policies and trust that the third party location-based service (LBS) providers adhere to these policies. • Anonymity-based scheme: • Vehicle mitigates by using a randomly chosen and changing identifier, called the pseudonym. • Pseudonyms may be a set of public keys, network layer addresses or link layer addresses and has a predefined generation scheme. • A solution to protecting the privacy of VANET. • Changing pseudonym at only one layer pose as an attacker can link pseudonyms using the unchanged address at the other layer.

5. Amoeba • AMOEBA is a location privacy enhancement scheme. • Adds random silent period between update of pseudonyms for V2V communications. • Road networks are classified into Observed Zones & Unobserved Zones or Mix Zones. • Mix Zones are predetermined locations where the vehicles vary their directions, speedsand their pseudonyms. • Difficulty to trace the vehicles that emerge from the mix zone. • CMIX (Cryptographic MIX-zone), each vehicle obtains a public/private key pair from certificate authority (CA) via the road-side unit (RSU), to encrypt all messages while they are within the mix zone

6. k-anonymity • K-anonymity is the proposed location privacy enhancement scheme. • Protects location information through spatial and temporal cloaking. • Considers the neighboring vehicle density as the triggering factor for updating the pseudonym. • Vehicle updates its pseudonym only when there are at least k−1 distinct neighboring vehicles. • The beacon message will not be broadcast by the vehicle until a certain number of other vehicles have visited the same location. • The goal is to minimize the probability of successful location tracking of a target vehicle by an adversary.

7. System Model • The density zone consists of M ports and N intersections. • All vehicles can enter and exit the density zone only via these ports. • An intersection is a road junction where two or more roads either meet or cross. • k-density zone of vehicle v is the area where at least k−1 distinct neighboring vehicles always exist.

8. global passive adversary • GPA aims to locate and track the target vehicles by eavesdropping on their authenticated safety broadcast. • GPA leverages the deployed infrastructure and utilizes the adversarial RSU deployed to track the movement of the target. • GPA cannot distinguish the target vehicle from other vehicles within the density zone due to the change of pseudonym. • GPA can observe entering and exiting events of vehicles where an event is a pair consisting of a port number and a time stamp by installing radio receivers at opportune location. • GPA can attempt to link an entering vehicle and an exiting vehicle with certain success probability using delay distribution.

9. Road Traffic & Delay Model • After entering the density zone via port i, each vehicle travels at a distance di with constant speed Si which is chosen independently from a normal distribution. • From an empirical study on the real freeway traffic can can determine inter-arrival time of vehicles to port. • At the intersection, each vehicle chooses the output port j with a probability, which can also be estimated. • Similarly, using mathematical models the average signal delay can also be determined.

10. PARAMETER OVERVIEW

11. DENSITY-BASED LOCATION PRIVACY • Vehicles share information by broadcasting local beacon messages periodically. • A beacon message is a short packet with the current pseudonym and location information of the vehicle. • The default beacon interval in 802.11-based networks is 100 ms. • Δtis a configurable parameter for various speed of vehicles. • Each vehicle v determines its or neighboring vehicle countby listening for beacon messages from its neighbors. • This ensures that each vehicle triggers a pseudonym change only if there are at least k−1 neighboring vehicles. • Failure to detect transmission within a predefined timeout value,result in decrement of neighboring vehicle count.

12. OPERATIONS OF ADVERSARY • Adversary can observe the entering and exit events corresponding to vehicles entering and exiting the density zones respectively. • An entering event consists of the port where the vehicle entered the density zone, and the time when it happened. • An exit event consists of the port where the vehicle left the density zone, and the time when it happened. • The objective of an adversary is to relate exit events to entering events. • The adversary may select a target vehicle v and tracks its movement until it enters the density zone. • Within the density zone, the target vehicle may change its pseudonym if it satisfies the criteria in the DLP scheme.

13. Performance Evaluation • The metric used in proposed model is the probability of successful tracking of a target vehicle by an adversary when making its decision. • If the success probability is large, the density zone and changing pseudonyms are ineffective • If the success probability is small, then tracking is difficult and the system ensures location privacy. • The probability of successful tracking cannot be determined analytically due to the complexity of the model. • Simulated runs has been used to determine its empirical value in realistic situations.

14. topology and mobility model for the performance evaluation • Network Topology: A density zone is composed of one intersection and four road segments in each direction. • Mobility Pattern: All vehicles within the density zone are assumed to travel at a constant speed given at each segment. At the intersection, all vehicles experience the delay based on the signal logic of intersection. • For each exiting vehicle, the adversary chooses a vehicle which can minimize the time difference between the average delay. • Total delay is inversely proportional to the speed of vehicles. • With an increase in variance of vehicles speed increases, the variance of total delay decreases. • This makes it difficult to find a target vehicle with the highest probability as the variance of vehicles’ speed increases.

15. Performance Comparison

16. Conclusion • Effectiveness of changing pseudonyms to provide location privacy in VANETs. • Delay model of vehicles in the density zone to demonstrate the effectiveness of changing pseudonyms. • For evalution, an assumption was made that the adversary has sufficient knowledge of delay in density zone. • Based on this information, an adversary may try to select a vehicle which exits the density zone to the target vehicle that entered it earlier. • Extensive simulation result study shows the probability of successful tracking of a target vehicle by an adversary under different scenarios. • Proposed DLP scheme has a better performance than both Mix-Zone and AMOEBA with random silent period in terms of a lower probability of successful tracking by an adversary. • DLP scheme can mitigate the location tracking of vehicles by changing pseudonyms based on a threshold in neighboring vehicle count within a density zone.

17. Acknowledgement Based on research work of Joo-Han Song, Vincent W.S. Wong, and Victor C.M. Leung http://www.ece.ubc.ca/~vincentw/C/SWLcICC09.pdf Thank You!