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Virtual Trip Lines for Distributed Privacy-Preserving Traffic Monitoring Baik Hoh, Marco Gruteser WINLAB / ECE Dept., Rutgers University Ryan Herring,

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Presentation on theme: "Virtual Trip Lines for Distributed Privacy-Preserving Traffic Monitoring Baik Hoh, Marco Gruteser WINLAB / ECE Dept., Rutgers University Ryan Herring,"— Presentation transcript:

1 Virtual Trip Lines for Distributed Privacy-Preserving Traffic Monitoring Baik Hoh, Marco Gruteser WINLAB / ECE Dept., Rutgers University Ryan Herring, Jeff Bana, Dan Work, Juan-Carlos Herrera, Alexandre Bayen Civil Engineering Dept., UC Berkeley Murali Annavaram, Quinn Jacobson Nokia Research Center Presentation By: Saurabh Hukerikar 30 th March 2009

2 Introduction Virtual trip lines  Geographic markers that indicate where vehicles should provide location updates  Aggregating and cloaking several location updates based on trip line identifiers for privacy by preventing updates from VTL’s deemed private.  Distributed architecture

3 The Conventions  Eye witness reports  Traffic cameras  Loop detectors  Cellular base station hand-off  In-Vehicle Transponders (IVTs) and License Plate Readers (LPRs).

4 Privacy risks & threat model Preserving privacy in GPS traces via uncertainty-aware path cloaking [B. Hoh, M. Gruteser, H. Xiong, and A. Alrabady]  Spatio-temporal characteristics of the data allows tracking and re- identification of anonymous vehicles when user density is low.  Consecutive location samples from a vehicle exhibit temporal and spatial correlation, paths of individual vehicles can be reconstructed from a mix of anonymous samples belonging to several vehicles  Process can be formalized and automated through target tracking algorithms  Algorithms generally predict the target position using the last known speed and heading information and then decide which next sample to link to the same vehicle through Maximum Likelihood Detection

5 Privacy Metrics  Mean Time To Confusion (MTTC)  Mean Distance To Confusion (MDTC)  Tracking Uncertainity

6 Traffic Monitoring With Virtual Trip Lines Virtual trip line (VTL): [id; x1; y1; x2; y2; d] Handset VTL generator ID proxy server Traffic monitoring service provider Virtual trip lines control disclosure of location by sampling in space

7 VTL Placement: Minimum Spacing Speed variation Penetration & Speed – impact on Minimum spacing

8 If trip lines are placed immediately before or after intersections, an adversary may be able to follow vehicles paths based on speed differences VTL Placement: Road Layout

9 VTL Placement: Minimum Spacing – Speed consideration

10 Experimental Evaluation Travel time of each link is computed with the length of a link and the mean speed that is obtained by averaging out speed readings from probe vehicles during an aggregation interval. RMS error of about 80 seconds

11 Distance-to-confusion with two different sets of anonymous flow updates from both o The evenly spaced VTLs (with exclusion area) and o The evenly spaced VTLs (without exclusion area) o 1 – 2 % penetration o 500 meters exclusion area o Sets of equidistant trip lines with minimum spacing varying from 333 ft (100 meters) to 1670 ft (500 meters) o Uncertainty threshold of 0.2 Experimental Evaluation – Privacy v Accuracy Trade-Off

12  Two successive anonymous updates that are sampled longer than 800 feet apart experience high tracking uncertainty.  Existence of the exclusion area  The travel time estimation generally improves with an increasing number of VTLs Privacy v Accuracy Trade-Off

13 Source: Experimental Evaluation

14 Critique  Energy requirements - dash board charger  Processing and Communication overhead on Client phone  Real time? - Distributed architecture  Exclusion of VTLs - Generic exclusion risks undercoverage - Individualized exclusion processing overhead or configuration

15 Source: “The TomTom devices with HD Traffic all use a built-in receiver including a SIM-card. Does this mean that I can be traced? TomTom takes privacy of personal information very seriously, and the information retreived is entirely anonymous. TomTom only uses information about the speed and direction travelled of TomTom device users. We don't know anything about the devices themselves, nor who owns them” “Data generated from the mobile phones is completely anonymous. TomTom, and has information about user direction and speed only - not the type of device, nor the owner of the mobile phone.” WEBLINK:TomTom High DefinitionTomTom High Definition

16 WEBLINK:

17 Questions?

18 Thank-you


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