Robust GPS-Based Timing for Phasor Measurement Units October 3, - - PowerPoint PPT Presentation

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Robust GPS-Based Timing for Phasor Measurement Units October 3, - - PowerPoint PPT Presentation

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TRUSTWORTHY CYBER INFRASTRUCTURE FOR THE POWER GRID | TCIPG.ORG Robust GPS-Based Timing for Phasor Measurement Units October 3, 2014 Grace Xingxin Gao University of Illinois at Urbana-Champaign UNIVERSITY OF ILLINOIS | DARTMOUTH COLLEGE |

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TRUSTWORTHY CYBER INFRASTRUCTURE FOR THE POWER GRID | TCIPG.ORG

UNIVERSITY OF ILLINOIS | DARTMOUTH COLLEGE | UC DAVIS | WASHINGTON STATE UNIVERSITY

FUNDING SUPPORT PROVIDED BY DOE-OE AND DHS S&T

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Robust GPS-Based Timing for Phasor Measurement Units

October 3, 2014

Grace Xingxin Gao

University of Illinois at Urbana-Champaign

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How to Make GPS-based Timing Robust?

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Facts about GPS

– GPS provides timing for many applications, such as PMUs – GPS civil signals are unencrypted

  • Only GPS military signals are encrypted
  • Civil users (e.g. PMUs) do not have access to the military codes

– GPS civil signal structures are completely open

  • GPS civil signal definition is published in its Interface Control

Documents (ICD) – GPS received signals are extremely weak

  • GPS satellites are 20,200 km (12,550 miles) away

– GPS is operational

  • Satellites in orbits
  • Signals being broadcast
  • Billions of GPS receivers in use
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Outline

– GPS Cooperative Authentication

  • Pairwise check
  • Decision aggregation

– Position-Information-Aided Vector Tracking

  • Approach
  • Implementation
  • Experimental Results

– Conclusions

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Outline

– GPS Cooperative Authentication

  • Pairwise check
  • Decision aggregation

– Position-Information-Aided Vector Tracking

  • Approach
  • Implementation
  • Experimental Results

– Conclusions

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Cooperative Authentication: Architecture

I got my location. Can you guys check if I was spoofed?

A snippet of baseband GNSS signal

Your snippet matches mine. You are not spoofed! A high correlation! You are good, bro. It doesn’t match mine. You might be spoofed. User receiver Cross-check receiver #1 Cross-check receiver #2 Cross-check receiver #N

Merits: network and geographical redundancy

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Pair-wise Checking: Cross-correlation of P(Y) Code

Psiaki, Humphreys et al., 2013 Lo et al., 2009

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Outline

– GPS Cooperative Authentication

  • Pairwise check
  • Decision aggregation

– Position-Information-Aided Vector Tracking

  • Approach
  • Implementation
  • Experimental Results

– Conclusions

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Pairwise Check

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Pairwise Check – Ideal Results

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Not Spoofed Spoofed 40 ms 40 Correlation peaks Single Correlation peak No Correlation peak Spoofer cannot generate In-phase Baseband Correlation (C/A) Quadrature- phase Baseband Correlation (P(Y))

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Modeling Pairwise Check

P(Y) codes don’t match

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Experiments with Different Scenarios

3000km 22km

San Francisco CA and Champaign IL, static Rantoul IL, moving at ~45 mph and Champaign IL, static

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Experiments: San Francisco & UIUC Everitt Lab

–

  • –
  • – SiGe Sampler
  • –
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3000km separation 22km separation

Near ideal Correlation Could detect spoofing Could detect spoofing Some Residual Correlation Almost no Residual Correlation

Pairwise Results for Different Separations

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SNR Affects Pair-wise Check Performance

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Outline

– GPS Cooperative Authentication

  • Pairwise check
  • Decision aggregation

– Position-Information-Aided Vector Tracking

  • Approach
  • Implementation
  • Experimental Results

– Conclusions

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Modeling Unreliable Cross-Check Receivers

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Authentication Performance, Theoretical Results

  • Authentication performance improves exponentially with

increasing number of cross-check receivers.

  • PSS causes twice as great performance deterioration as PSD

does. – Choose a cross-check receiver far from the user receiver.

Pair-wise false alarm rate Pair-wise missed detection rate Probability of being spoofed by the same spoofer Probability of being spoofed by a different spoofer

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Receiver Operating Characteristic (ROC) Curves

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Performance of Cooperative Authentication

2 3 4 5 6 7 8 10

  • 4

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  • 1

10 PMD = 0.15 Number of cross-check receivers (N) Probability of missed detection (PMD = 1 - PD) PSS = 0, PSD = 0 PSS = 0.02, PSD = 0.18 PSS = 0.1, PSD = 0.1 PSS = 0.18, PSD = 0.02 2 3 4 5 6 7 8 10

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10

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  • 1

PFA = 0.001 Number of cross-check receivers (N) Probability of false alarm (PFA) PSS = 0, PSD = 0 PSS = 0.02, PSD = 0.18 PSS = 0.1, PSD = 0.1 PSS = 0.18, PSD = 0.02

Assume 20% of the cross-check receivers are spoofed (an extremely challenging assumption) Probability of false alarm Probability of missed detection

  • Robustness grows exponentially with the number of

cross-check receivers

  • A small number of unreliable cross-check receivers are
  • n par with a reliable cross-check receiver.
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Outline

– GPS Cooperative Authentication

  • Pairwise check
  • Decision aggregation

– Position-Information-Aided Vector Tracking

  • Approach
  • Implementation
  • Experimental Results

– Conclusions

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Approach: Position-Information-Aided (P.I.A.) Vector Tracking

Approach: – Vector tracking – Reduces the search space

  • Aided by the true position

– Kalman filtering

  • Recursively predict and update the errors

– Narrowband loop filter

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Scalar Tracking

GPS Front-end Correlator Code and Carrier Discriminators Navigation Processing Incoming Signal NCO Channel 1-N 𝑔

𝑒

, 𝜚 Position and Time Solutions (𝑦, 𝑧, 𝑨, 𝑢)

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Implementation: P.I.A. Vector Tracking

GPS Front-end Correlator Code and Carrier Discriminators Kalman Filter: Navigation Prediction Position analysis Incoming Signal Known True Position (𝑦, 𝑧, 𝑨) Position, Velocity, Timing, Code, and Carrier Correction Navigation Prediction LOS Projection Code and Carrier Predictions NCO Timing Errors Channel 1-N 𝑔

𝑒

, 𝜚 Time Solution (𝑢)

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Implementation: Kalman Filter

– States: 𝜀𝑌, 𝜀𝑊, 𝜀𝑢 , 𝜀𝑢 – State Transition Matrix – Predictions: – 𝜀𝑌 = 𝑌 − (𝑌 + 𝑊 Δ 𝑢) – 𝜀𝑊 = 𝑊 − 𝑊 – Calculation of receiver clock bias: 𝑢 = 1 ∑ 𝜕 𝜕 (𝜍 − 𝑦 − 𝑦 )

𝐺 = Δ 𝑢 Δ 𝑢 Δ 𝑢 Δ 𝑢 Psuedorange Satellite Position Known true position 1/𝑤𝑏𝑠 𝜗 𝑌 = 𝜀𝑦 𝜀𝑧 𝜀𝑨 𝜀𝑤 𝜀𝑤 𝜀𝑤 𝜀𝑢 𝜀𝑢

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P.I.A. Vector Tracking Improves Accuracy

– Loop filter bandwidth of 5Hz for both scalar and P.I.A tracking loops. – 9 satellites in view Maximum errors: – Traditional tracking

  • ~50ns

– Proposed vector tracking

  • ~15ns

No Noise Added

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P.I.A. Tracking Increases Noise Tolerance

– Increased noise leads to loss of lock in scalar tracking. – At 4 dB of additional noise, the scalar tracking was able to produce navigation bits for 4 satellites.

1 dB Noise Added 4 dB Noise Added

Noise Added # of Satellites Tracked 0 dB 9 1 dB 8 3 dB 5 4 dB 4

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P.I.A. Tracking is Robust Against Jamming

– Scalar tracking fails at 5 dB of added noise. – P.I.A. Vector Tracking continued to operate up until 9 dB of additional noise (5 dB more noise tolerance over scalar tracking) – Reduces a jammer’s effective radius.

5 dB Noise Added 9 dB Noise Added

Scalar tracking fails P.I.A. still tracking Scalar tracking fails P.I.A. still tracking

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P.I.A. Tracking Detects Meaconing

– Meaconing: record and replay legitimate GPS signal. – Meaconing attack simulated. – P.I.A. Vector Tracking loop fails to converge in the event of a meaconing attack. – 200 meter difference in known position and meaconing position.

Meaconing attack begins

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Outline

– GPS Cooperative Authentication

  • Pairwise check
  • Decision aggregation

– Position-Information-Aided Vector Tracking

  • Approach
  • Implementation
  • Experimental Results

– Conclusions

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Conclusions

– GPS cooperative authentication

  • A modest number of low-reliable cross-check receivers
  • utperform a high-quality reliable receiver.
  • Robustness grows exponentially with the number of cross-check

receivers. – Position-Information-Aided Vector

  • Robust against jamming (5dB more noise tolerance compared

with scalar tracking);

  • Successfully detects meaconing attacks;
  • Improves the accuracy of the timing solutions (15 ns vs 50 ns).
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Acknowledgement

– Prof. Jonathan Makela – TCIPG

References

– Daniel Chou, Liang Heng, and Grace Xingxin Gao , “Robust GPS-Based Timing for Phasor Measurement Units: A Position-Information-Aided Vector Tracking Approach,” ION GNSS+ 2014, Tampa FL, Sep 2014, Best Presentation of the Session Award. – Liang Heng, Daniel Chou, and Grace Xingxin Gao , “Cooperative GPS Signal Authentication from Unreliable Peers,” ION GNSS+ 2014, Tampa FL, Sep 2014, Best Presentation of the Session Award. – Liang Heng, Jonathan Makela, Alejandro Dominguez-Garcia, Rakesh Bobba, William Sanders, and Grace Xingxin Gao, “Reliable GPS-based Timing for Power System Applications: A multi-Layered Multi- receiver Approach,” the 2014 IEEE Power and Energy Conference at Illinois (IEEE PECI 2014), Champaign, IL, Feb 2014. – Liang Heng, Daniel B. Work, and Grace Xingxin Gao, “Reliability from Unreliable Peers: Cooperative GNSS Authentication,” Inside GNSS Magazine, September–October 2013. – Liang Heng, Daniel B. Work, and Grace Xingxin Gao, “GNSS Signal Authentication from Cooperative Peers,” IEEE Transactions on Intelligent Transportation Systems, submitted.

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Backup Slides

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Multi-layer Countermeasures