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Detection of On-Road Vehicles Emanating GPS Interference
Gorkem KarHossen Mustafa
Yan WangYingying ChenWenyuan Xu
Marco GruteserTam Vu
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Winlab Winter Research ReviewACM CCS 2014
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GPS in Critical Infrastructures
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GPS Jammers
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Newark Airport Incident
• In 2010, ground GPS receivers did not work for a few minutes repeatedly over couple of months.
• It took 3 months to locate the problem.
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Current Solutions
• Handheld devices
– Works only in static scenarios
– Used manually for a short time
• Standard wireless localization techniques
– Not sufficient to pinpoint a
vehicle in dense traffic
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What is needed?
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What is Needed?
• A detection and identification system that is;
– automated, with high accuracy, and at a low cost,
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Overview of Jamming Detection System
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Jammer
Monitoring Point
Mobile Phone
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Multiple Monitoring Points
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Jammer is detected with MP1 @ time t1
MP 2 MP 1
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Multiple Monitoring PointsJammer is detected with MP2 @ time t2
MP 2 MP 1
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Monitoring Points
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Experimental Setup
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USRP
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MP Location
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Camera
Monitoring Point
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Detection Zone
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Identified Vehicle Positions at tm
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(m)
(m)
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Single Monitoring Point Case
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@ MP 1 @ MP 2
We could uniquely identify the transmitting car with 65% @ MP 1 and 35% @ MP 2 with NO false positive rate.
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Multiple Monitoring Case
• The detection rate can be improved by combining the information collected from both zones.
– Intersect the candidate vehicle sets @ MP1 and MP2.
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This resulted in only a single detected vehicle and a correct identification of our transmitter vehicle in all cases.
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Passive Roadside Monitoring
• 5 locations are chosen in NJ and SC; 200 hours of monitoring passively,– a major highway, – one of the busiest toll road, – and an urban road
• Two suspicious interference incidents are detected.
• May not come from real jammer, but still proves the interference exist @ L1 frequency band(which is GPS band, 1.5 GHz).
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Mobile Detectors
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How to Detect the Interference via Mobile Phones?
Profiling– Use Android API to get the current
SNR(Signal-to-Noise Ratio) value of the
location
– Create a SNR profile of a sample route
by matching SNR with GPS position
(expected SNR)
Anomaly Detection– Compare current reading(SNR) of the mobile detector with the
expected SNR from profiling stage
– If current reading of SNR is lower than the expected SNR, there should be an interference at L1 freq., central office should be notified.
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Ave
rage
SN
R (
dB
)
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Conclusion
• Presented a low-cost jammer identification system that can be mass deployed in roadways to automatically detect and identify the vehicles with GPS jammers.
• The key components of the system are monitoring stations and mobile detectors.
• Our mobile detector can detect interfering signals based on measurements that are readily available in most GPS receivers– Thus, it is possible to detect jammers via
crowdsourcing.
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THANKS!
• Any questions?