TR2019-023

GPS Spoofing Detection and Mitigation in PMUs Using Distributed Multiple Directional Antennas


    •  Bhamidipati, S., Kim, K.J., Sun, H., Orlik, P.V., "GPS Spoofing Detection and Mitigation in PMUs Using Distributed Multiple Directional Antennas", IEEE International Conference on Communications (ICC), DOI: 10.1109/ICC.2019.8761208, June 2019, pp. 1-7.
      BibTeX TR2019-023 PDF
      • @inproceedings{Bhamidipati2019jun,
      • author = {Bhamidipati, Sriramya and Kim, Kyeong Jin and Sun, Hongbo and Orlik, Philip V.},
      • title = {GPS Spoofing Detection and Mitigation in PMUs Using Distributed Multiple Directional Antennas},
      • booktitle = {IEEE International Conference on Communications (ICC)},
      • year = 2019,
      • pages = {1--7},
      • month = jun,
      • doi = {10.1109/ICC.2019.8761208},
      • url = {https://www.merl.com/publications/TR2019-023}
      • }
  • MERL Contacts:
  • Research Areas:

    Communications, Information Security, Signal Processing

In power distribution networks, microgrids utilize Phasor Measurement Units (PMUs), to assess the voltage stability at critical nodes in the network. PMUs rely on precise time-keeping sources, such as GPS, to obtain synchronization. However, GPS signals are vulnerable to external spoofing attacks due to their unencrypted signal structure and low received power. To detect the spoofing-induced timing anomaly, an innovative geographically Distributed Multiple Directional Antennas (DMDA) setup is proposed, which is triggered using a common clock. Utilizing the configuration of the proposed DMDA, a Belief-Propagation (BP)-based Extended Kalman Filter (EKF) algorithm is developed to estimate the timing errors caused by spoofing. The BP-EKF algorithm analyzes the single difference pseudorange residuals across each pair of antennas in a probabilistic graphical framework not only to detect the spoofed antennas in the DMDA setup but also to estimate the timing errors associated with the spoofed antennas. Based on the BP estimate of timing error at each antenna and the known baseline distances across antennas, the pseudoranges are corrected, and then adaptive EKF is employed to estimate the GPS timing. The performance of the BP-EKF algorithm is assessed by subjecting the simulated authentic GPS signals to a simulated meaconing attack, which induces a time delay of 60 microseconds. Both successful detection of meaconing, and also accurate estimation of GPS timing that complies with the IEEE-C37.118 standards, is validated using the experimental results. At a critical node in the simulated microgrid, as compared to scalar tracking, an increased voltage stability is demonstrated using the BP-EKF by assessing a metric, namely, voltage stability index.

 

  • Related News & Events

    •  AWARD   MERL Researchers Won IEEE ICC Best Paper Award
      Date: May 22, 2019
      Awarded to: Siriramya Bhamidipati, Kyeong Jin Kim, Hongbo Sun, Philip Orlik
      MERL Contacts: Kyeong Jin (K.J.) Kim; Hongbo Sun
      Research Areas: Artificial Intelligence, Communications, Machine Learning, Signal Processing, Information Security
      Brief
      • MERL researchers, Kyeong Jin Kim, Hongbo Sun, Philip Orlik, along with lead author and former MERL intern Siriramya Bhamidipati were awarded the Smart Grid Symposium Best Paper Award at this year's International Conference on Communications (ICC) held in Shanghai, China. There paper titled "GPS Spoofing Detection and Mitigation in PMUs Using Distributed Multiple Directional Antennas," described a technique to rapidly detect and mitigate GPS timing attacks/errors via hardware (antennas) and signal processing (Kalman Filtering).
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