Fast Sequence Component Analysis for Attack Detection in Synchrophasor Networks

Modern power systems have begun integrating synchrophasor technologies into part of daily operations. Given the amount of solutions offered and the maturity rate of application development it is not a matter of "if" but a matter of "when" in regards to these technologies becoming ubiquitous in control centers around the world. While the benefits are numerous, the functionality of operator-level applications can easily be nullified by injection of deceptive data signals disguised as genuine measurements. Such deceptive action is a common precursor to nefarious, often malicious activity. A correlation coefficient characterization and machine learning methodology are proposed to detect and identify injection of spoofed data signals. The proposed method utilizes statistical relationships intrinsic to power system parameters, which are quantified and presented. Several spoofing schemes have been developed to qualitatively and quantitatively demonstrate detection capabilities.Comment: 8 pages, 4 figures, submitted to IEEE Transaction

Integrity and attack-resilience of GPS-based positioning and timing: a Bayesian and measurement fusion approach

Robust Position, Velocity, and Timing (PVT) are essential for the safe operations of critical infrastructure sectors, such as transportation systems and power grids. Different transportation systems, both human-operated and autonomous vehicles, navigate using accurate position and velocity information. On the other hand, precise timing is crucial for various economic activities worldwide, such as banking, stock markets, and the power grid. GPS serves as a backbone for many state-of-the-art applications related to these crucial infrastructures. GPS provides sub-microsecond accurate timing and meter level of accurate positioning. It has global coverage and is free for all users. The GPS positioning and timing service has some limitations. The positioning accuracy degrades in urban environments due to tall structures that block and reflect satellite signals. Degraded positioning is not safe for the operation of autonomously driving vehicles. Furthermore, GPS signals are susceptible to external attacks due to their low signal power and unencrypted signal structures. Researchers have shown that GPS Spoofing Attacks (GSAs) are feasible, and GSA for timing is able to alter timing without modifying the positioning solution. Such attacks create unsafe operating conditions for the modern power grid, which will use GPS timing for monitoring the wide-area network. The contribution of this work is to develop algorithms to mitigate the above limitations. We develop Bayesian algorithms that utilize multiple sensors and receivers. For improving positioning, first, we design an adaptive filter based on Bayesian algorithms to augment GPS with the additional vision sensor. Second, we develop an integrity monitoring algorithm for Direct Positioning (DP), which is an advanced GPS receiver architecture that directly works on the position domain and is robust to signal blockage and multipath effects. To monitor integrity, we estimate vertical protection levels using a Bayesian approach. We further generate GPS datasets simulating open, semi-urban, and urban environments for validating DP with multiple receivers. For mitigating GSAs for timing, we design static and dynamic state estimators for the power grid. The static state estimator utilizes measurement residuals to correct power grid states. In the dynamic state estimator, we fuse GPS and power grid measurements to provide resiliency against GSAs. We create a virtual power grid testbed and generate datasets for a power grid network under different GSAs. These are the first datasets that contain both power grid and GPS measurements under GSAs, and we make them openly available. Our estimators are validated on various power grid networks and on the generated datasets

Data Analytics and Wide-Area Visualization Associated with Power Systems Using Phasor Measurements

As power system research becomes more data-driven, this study presents a framework for the analysis and visualization of phasor measurement unit (PMU) data obtained from large, interconnected systems. The proposed framework has been implemented in three steps: (a) large-scale, synthetic PMU data generation: conducted to generate research-based measurements with the inclusion of features associated with industry-grade PMU data; (b) error and event detection: conducted to assess risk levels and data accuracy of phasor measurements, and furthermore search for system events or disturbances; (c) oscillation mode visualization: conducted to present wide-area, modal information associated with large-scale power grids. To address the challenges due to real data confidentiality, the creation of realistic, synthetic PMU measurements is proposed for research use. First, data error propagation models are generated after a study of some of the issues associated with the unique time-synchronization feature of PMUs. An analysis of some of the features of real PMU data is performed to extract some of the statistics associated with data errors. Afterwards, an approach which leverages on existing, large-scale, synthetic networks to model the constantly-changing dynamics often observed in real measurements is used to generate an initial synthetic dataset. Further inclusion of PMU-related data anomalies ensures the production of realistic, synthetic measurements fit for research purposes. An application of different techniques based on a moving-window approach is suggested for use in the detection of events in real and synthetic PMU measurements. These fast methods rely on smaller time-windows to assess fewer measurement samples for events, classify disturbances into global or local events, and detect unreliable measurement sources. For large-scale power grids with complex dynamics, a distributed error analysis is proposed for the isolation of local dynamics prior any reliability assessment of PMU-obtained measurements. Finally, fundamental system dynamics which are inherent in complex, interconnected power systems are made apparent through a wide-area visualization of large-scale, electric grid oscillation modes. The approach ensures a holistic interpretation of modal information given that large amounts of modal data are often generated in these complex systems irrespective of the technique that is used

Robust GPS-based timing for phasor measurement units based on single-receiver and multi-receiver position-information-aided vector tracking

In recent years there has been a major push by the power industry to utilize phasor measurement units (PMUs) for wide area monitoring and control. PMUs are considered to be one of the most critical technologies for the future and modernization of the power grid. This technology produces time-stamped voltage and current phasor measurements, allowing measurements from any point in the power infrastructure to be synchronized. Widely regarded as one of the most vital devices in monitoring and control for the future of power systems, PMUs rely on the Global Positioning System (GPS) to provide the absolute time reference necessary to synchronize phasor measurements. The security and reliability of PMUs are essential to the future of the power grid and so in this work we aim to provide robust GPS timing for PMUs. Since power systems are considered part of the civil sector, PMUs must utilize the civil GPS signals to obtain the time reference. However, the low received signal strength and unencrypted nature of the civil GPS signal leaves PMU reliability susceptible to both non-malicious and malicious interference. Most notably, jamming and spoofing attacks on PMU GPS receivers can pose a risk to the position, velocity, and timing (PVT) solutions. Our goals are to provide robust GPS time transfer for PMUs and to rapidly detect malicious spoofing attacks. We achieve these goals by leveraging the inherent properties of PMU GPS receivers. We propose and implement the position-information-aided (PIA) vector tracking loop and the multi-receiver PIA vector tracking loop. To evaluate the effectiveness of the algorithms presented in this thesis, we also conduct field experiments which showed improve tracking capabilities and continued operation through various attacks of both algorithms. Our experiments show that the proposed PIA and multi-receiver PIA vector tracking approaches 1) improve the robustness of GPS receivers used in PMUs against jamming and interference; 2) are robust against spoofing attacks; and 3) can detect various spoofing attacks. Finally, we conducted tests using a real-time digital simulator (RTDS) which demonstrate the impacts of an attack on a PMU's time source

GPS spoofing detection for the power grid network via a multi-receiver hierarchical architecture

In the process of modernizing the North American electric power grid with the creation of the Smart Grid, thousands of devices called phasor measurement units (PMUs) have been deployed across the U.S. continent to continuously monitor the power grid state in real-time. Each PMU measures voltage and current phasors at its local substation, then synchronizes these measurements across the continental network using the Global Positioning System (GPS) as a common timing reference. GPS serves as an excellent timing source due to its global coverage as well as its precise, sub-microsecond level timing accuracy. However, because civilian GPS signals are unencrypted with a publicly available signal structure, any individual with the appropriate equipment can mimic these signals in order to establish a false timing solution at the PMU sites. This type of attack, commonly known as GPS spoofing, presents a major concern to our future power grid infrastructure. Indeed, even minor timing manipulations can cause inaccurate power flow representations and corresponding corrective measures, potentially inducing large-scale power disruptions, instability within the power grid, and/or damage to generators and other power equipment. In this thesis, we present a multi-receiver spoofing detection algorithm for PMU devices, utilizing a hierarchical architecture framework. For the received GPS signal at each PMU station, we create conditioned signal fragments containing the military P(Y) GPS signal, which bears a binary spreading code sequence that is unavailable to civilian users and thus cannot be forged by an attacker. As a result, the military P(Y) signal establishes an encrypted signature in the background of all authentic GPS signals. The presence of the authentic signature can be verified, without knowledge of the precise bit sequence, by correlating amongst conditioned signal fragments obtained from other PMU sites in a sub-network of cross-check receivers, thereby leveraging the secure communication network available within the power grid infrastructure. We further defend against coordinated spoofing attacks conducted against the sub-network of PMU devices by comparing condensed, representative signals generated for each sub-network within the power grid. Using real-world data recorded during a government-sponsored, live-sky spoofing event, we demonstrate that our algorithm successfully evaluates the authenticity of each receiver in a widely dispersed network

GNSS Related Threats to Power Grid Applications

As power grid environments are moving towards the smart grid vision of the future, the traditional schemes for power grid protection and control are making way for new applications. The advancements in this field have made the requirements for power grid’s time synchronization accuracy and precision considerably more demanding. So far, the signals provided by Global Navigation Satellite Systems have generally addressed the need for highly accurate and stable reference time in power grid applications. These signals however are highly susceptible to tampering as they are being transmitted. Since electrical power transmission and distribution are critical functions for any modern society, the risks and impacts affiliated with satellite-based time synchronization in power grids ought to be examined. This thesis aims to address the matter. The objective is to examine how Global Navigation Satellite Systems are utilized in the power grids, how different attacks would potentially be carried out by employing interference and disturbance to GNSS signals and receivers and how the potential threats can be mitigated. A major part of the research is done through literature review, and the core concepts and different implementations of Global Navigation Satellite Systems are firstly introduced. The literature review also involves the introduction of different power grid components and subsystems, that utilize Global Positioning System for time synchronization. Threat modeling techniques traditionally practiced in software development are applied to power grid components and subsystems to gain insight about the possible threats and their impacts. The threats recognized through this process are evaluated and potential techniques for mitigating the most notable threats are presented.Sähköverkot ovat siirtymässä kohti tulevaisuuden älykkäitä sähköverkkoja ja perinteiset sähköverkon suojaus- ja ohjausmenetelmät tekevät tilaa uusille sovelluksille. Alan kehitys on tehnyt aikasynkronoinnin tarkkuusvaatimuksista huomattavasti aikaisempaa vaativampia. Tarkka aikareferenssi sähköverkoissa on tähän saakka saavutettu satelliittinavigointijärjestelmien tarjoamien signaalien avulla. Nämä signaalit ovat kuitenkin erittäin alttiita erilaisille hyökkäyksille. Sähkönjakelujärjestelmät ovat kriittinen osa nykyaikaista yhteiskuntaa ja riskejä sekä seuraamuksia, jotka liittyvät satelliittipohjaisten aikasynkronointimenetelmien hyödyntämiseen sähköverkoissa, tulisi tarkastella. Tämä tutkielma pyrkii vastaamaan tähän tarpeeseen. Päämääränä on selvittää, miten satelliittinavigointijärjestelmiä hyödynnetään sähköverkoissa, kuinka erilaisia hyökkäyksiä voidaan toteuttaa satelliittisignaaleja häiritsemällä ja satelliittisignaalivastaanottimia harhauttamalla ja kuinka näiden muodostamia uhkia voidaan lieventää. Valtaosa tästä tutkimuksesta on toteutettu kirjallisuuskatselmoinnin pohjalta. Työ kattaa satelliittinavigointijärjestelmien perusteet ja esittelee erilaisia tapoja, kuinka satelliittisignaaleja hyödynnetään sähköverkoissa erityisesti aikasynkronoinnin näkökulmasta. Työssä hyödynnettiin perinteisesti ohjelmistokehityksessä käytettyjä uhkamallinnusmenetelmiä mahdollisten uhkien ja seurausten analysointiin. Lopputuloksena esitellään riskiarviot uhkamallinnuksen pohjalta tunnistetuista uhkista, sekä esitellään erilaisia menettelytapoja uhkien lieventämiseksi

Undetectable Timing-Attack on Linear State-Estimation by Using Rank-1 Approximation

Smart-grid applications based on synchrophasor measurements have recently been shown to be vulnerable to timing attacks. A fundamental question is whether timing attacks could remain undetected by bad-data detection algorithms used in conjunction with state-of-the-art situational-awareness state estimators. In this paper, we analyze the detectability of timing attacks on linear state-estimation. We show that it is possible to forge delay attacks that are undetectable. We give a closed form for an undetectable attack; it imposes two phase offsets to two or more synchrophasor-based measurement units that can be translated to synchrophasors’ time delays. We also propose different methods for combining two-delays attacks to produce a larger impact. We simulate the attacks on a benchmark power- transmission grid, we show that they are successful and can lead to physical grid damage. To prove undetectability, we use classic bad-data detection techniques such as the largest normalized residual and the χ2-test