Sriramya Bhamidipati

Bio: Sriramya Bhamidipati is an academic researcher from University of Illinois at Urbana–Champaign. The author has contributed to research in topics: Global Positioning System & Spoofing attack. The author has an hindex of 7, co-authored 23 publications receiving 120 citations. Previous affiliations of Sriramya Bhamidipati include Indian Institute of Technology Bombay & Mitsubishi Electric Research Laboratories.

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

Abstract: 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 μs. 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.

GPS Multireceiver Joint Direct Time Estimation and Spoofer Localization

Abstract: We propose a novel algorithm for the joint estimation of spoofer location (LS) and GPS time using multireceiver direct time estimation (MRDTE). To achieve this, we utilize the geometry and known positions of multiple static GPS receivers distributed within the power substation. The direct time estimation computes the most likely clock parameters by evaluating a range of multipeak vector correlations, each of which is constructed via different pregenerated clock candidates. Next, we compare the time-delayed similarity in the identified peaks across the receivers to detect and distinguish the spoofing signals. Later, we localize the spoofer and estimate the GPS time using our joint particle and Kalman filter. Furthermore, we characterize the probability of spoofing detection and false alarm using Neyman Pearson decision rule. Later, we formulate the theoretical Cramer Rao lower bound for estimating the localization accuracy of the spoofer. We validate the robustness of our LS-MRDTE by subjecting the authentic open-sky GPS signals to various simulated spoofing attack scenarios. Our experimental results demonstrate precise localization of the spoofer while simultaneously estimating the GPS time to within the accuracy specified by the power community (IEEE C37.118 standard for synchrophasors).

GPS time authentication against spoofing via a network of receivers for power systems

Abstract: Due to the unencrypted structure of civil GPS signals, the timing information supplied to the PMUs in the power grid is vulnerable to spoofing attacks. We propose our GPS time authentication algorithm using a network of widely dispersed static receivers and their known positions. Without requiring the knowledge of the exact P(Y) code sequences, we cross-check for the presence of these encrypted codes across the receivers to detect spoofing attacks. First, we perform pair-wise cross-correlation of the conditioned quadrature-phase, carrier wiped-off incoming signal across the receivers. Later, we utilize position-information aiding to estimate the expected time offset between the received P(Y) codes at different receivers. Thereafter, we authenticate each receiver by analyzing the weighted summation of the pair-wise cross-correlation peak offset and magnitude across the receivers and their common satellites. To validate our networked spoofing detection algorithm, we utilize four GPS receivers located in Idaho, Illinois, Colorado and Ohio. Under the presence of simulated spoofing attacks, namely signal-level spoofing and a record-and-replay attack, we demonstrate that our networked approach successfully detects these spoofing events with high probability.

Locating Multiple GPS Jammers Using Networked UAVs

Abstract: Recent technologies, such as, Internet of Things and cloud services, increases the usage of small and low-cost networked unmanned aerial vehicles (UAVs), which needs to be robust against malicious global positioning system (GPS) attacks. Due to the availability of low-cost GPS jammers in the commercial market, there has been a rising risk of multiple jammers and not just one. However, it is challenging to locate multiple jammers because the traditional jammer localization via multilateration is applicable for only a single jammer case. Also, during a jamming attack, the positioning capability of an on-board GPS receiver is compromised given its inability to track GPS signals. We propose a simultaneous localization of multiple jammers and receivers (SLMR) algorithm by analyzing the variation in the front-end signal power recorded by the GPS receivers on-board a network of UAVs. Our algorithm not only locates multiple jammers but also utilizes these malicious sources as additional navigation signals for positioning the UAVs. We design a Gaussian mixture probability hypothesis density filter over a graph framework, which is optimized using a Levenberg–Marquardt minimizer. Using a simulated experimental setup, we validate the convergence and localization accuracy of our SLMR algorithm for various cases, including attacks with a single jammer, multiple jammers, and a varying number of jammers. We also demonstrate that our SLMR algorithm is able to simultaneously locate multiple jammers and UAVs, even for a larger transmitted power of the jammers.

Artificial-Intelligence-Based Distributed Belief Propagation and Recurrent Neural Network Algorithm for Wide-Area Monitoring Systems

Abstract: To monitor the power grid over a wide area, the wide area monitoring systems (WAMSs) has been developed. At each substation, the Global Positioning System (GPS) receiving system resides to provide trusted timing. Thus, it is critical for the WAMS to maintain authentic GPS timing over a wide area. However, GPS timing is susceptible to spoofing due to the unencrypted signal structure and its low signal power. Thus, to obtain trusted GPS timing from spoofing, a new wide-area monitoring algorithm, which comprises distributed belief propagation (BP) and a bidirectional recurrent neural network (RNN), is developed under the framework of artificial intelligence (AI). This joint BP-RNN algorithm authenticates each power substation by evaluating the estimated GPS timing error by its distributed processing capability. Specifically, the bidirectional RNN provides fast timing error estimation under the framework of AI. Simulation results demonstrate a fast detection time over the Kullback-Leibler divergence-based approach, and timing error estimation accuracy over the limit provided by the IEEE C37.118.1-2011 standard.

John W. Tukey and data analysis

Abstract: From the time that John W. Tukey started to do serious work in statistics, he was interested in problems and techniques of data analysis. Some people know him best for exploratory data analysis, which he pioneered, but he also made key contributions in analysis of variance, in regression and through a wide range of applications.This paper reviews illustrative contributions in these areas.

Factor graph optimization for GNSS/INS integration: A comparison with the extended Kalman filter

Abstract: Factor graph optimization (FGO) recently has attracted attention as an alternative to the extended Kalman filter (EKF) for GNSS-INS integration. This study evaluates both loosely and tightly coupled integrations of GNSS code pseudorange and INS measurements for real-time positioning, using both conventional EKF and FGO with a dataset collected in an urban canyon in Hong Kong. The FGO strength is analyzed by degenerating the FGO-based estimator into an “EKF-like estimator.” In addition, the effects of window size on FGO performance are evaluated by considering both the GNSS pseudorange error models and environmental conditions. We conclude that the conventional FGO outperforms the EKF because of the following two factors: (1) FGO uses multiple iterations during the estimation to achieve a robust estimation; and (2) FGO better explores the time correlation between the measurements and states, based on a batch of historical data, when the measurements do not follow the Gaussian noise assumption.

A Comprehensive Survey on Phasor Measurement Unit Applications in Distribution Systems

Abstract: Synchrophasor technology opens a new window for power system observability. Phasor measurement units (PMUs) are able to provide synchronized and accurate data such as frequency, voltage and current phasors, vibration, and temperature for power systems. Thus, the utilization of PMUs has become quite important in the fast monitoring, protection, and even the control of new and complicated distribution systems. However, data quality and communication are the main concerns for synchrophasor applications. This study presents a comprehensive survey on wide-area monitoring systems (WAMSs), PMUs, data quality, and communication requirements for the main applications of PMUs in a modern and smart distribution system with a variety of energy resources and loads. In addition, the main challenges for PMU applications as well as opportunities for the future use of this intelligent device in distribution systems will be presented in this paper.

Map-Aided Integrity Monitoring of a Land Vehicle Navigation System

Abstract: The concept of user-level integrity monitoring has been successfully applied to air transport navigation systems mainly focusing on the errors associated with space (satellite system) data processing chain. However, little research effort has been devoted to the study of land vehicle navigation system integrity monitoring. The primary difference is that one needs to consider the errors associated with a spatial map, and the map-matching process when monitoring the integrity of a land vehicle navigation system. To date research has focused on either the integrity of raw positioning information obtained from a satellite system or the integrity of the map-matching process and digital map errors. Here, for the first time all these errors are considered together, and additionally, road network complexity is also taken into account. Therefore, the main contribution of this paper is to develop user-level integrity monitoring by taking into account all the errors associated with a navigation system simultaneously; and to consider the operational environment (i.e., road complexity) to further improve the performance. The errors associated with a spatial road map are given special attention. Two knowledge-based fuzzy inference systems are developed to measure the integrity scale. The performance of the integrity method is checked using field data collected in Nottingham, UK. The integrity method can give 98.4% valid warnings. This is superior to existing integrity methods for land vehicle navigation, and has the potential to support real-time ITS applications.

Requirements for Secure Clock Synchronization

Abstract: This paper establishes a fundamental theory of secure clock synchronization. Accurate clock synchronization is the backbone of systems managing power distribution, financial transactions, telecommunication operations, database services, etc. Some clock synchronization (time transfer) systems, such as the global navigation satellite systems, are based on one-way communication from a master to a slave clock. Others, such as the network transport protocol, and the IEEE 1588 precision time protocol (PTP), involve two-way communication between the master and slave. This paper shows that all one-way time transfer protocols are vulnerable to replay attacks that can potentially compromise timing information. A set of conditions for secure two-way clock synchronization is proposed and proved to be necessary and sufficient. It is shown that IEEE 1588 PTP, although a two-way synchronization protocol, is not compliant with these conditions, and is therefore insecure. Requirements for secure IEEE 1588 PTP are proposed, and a second example protocol is offered to illustrate the range of compliant systems.