abstract: The electric power system is one of the largest, most complicated, and most important cyber-physical systems in the world. The link between the cyber and physical level is the Supervisory Control and Data Acquisition (SCADA) systems and Energy Management Systems (EMS). Their functions include monitoring the real-time system operation through state estimation (SE), controlling the system to operate reliably, and optimizing the system operation efficiency. The SCADA acquires the noisy measurements, such as voltage angle and magnitude, line power flows, and line current magnitude, from the remote terminal units (RTUs). These raw data are firstly sent to the SE, which filters all the noisy data and derives the best estimate of the system state. Then the estimated states are used for other EMS functions, such as contingency analysis, optimal power flow, etc. In the existing state estimation process, there is no defense mechanism for any malicious attacks. Once the communication channel between the SCADA and RTUs is hijacked by the attacker, the attacker can perform a man-in-middle attack and send data of its choice. The only step that can possibly detect the attack during the state estimation process is the bad data detector. Unfortunately, even the bad data detector is unable to detect a certain type of attack, known as the false data injection (FDI) attacks. Diagnosing the physical consequences of such attacks, therefore, is very important to understand system stability. In this thesis, theoretical general attack models for AC and DC attacks are given and an optimization problem for the worst-case overload attack is formulated. Furthermore, physical consequences of FDI attacks, based on both DC and AC model, are addressed. Various scenarios with different attack targets and system configurations are simulated. The details of the research, results obtained and conclusions drawn are presented in this document. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2015

abstract: The flexibility in power system networks is not fully modeled in existing real-time contingency analysis (RTCA) and real-time security-constrained economic dispatch (RT SCED) applications. Thus, corrective transmission switching (CTS) is proposed in this dissertation to enable RTCA and RT SCED to take advantage of the flexibility in the transmission system in a practical way. RTCA is first conducted to identify critical contingencies that may cause violations. Then, for each critical contingency, CTS is performed to determine the beneficial switching actions that can reduce post-contingency violations. To reduce computational burden, fast heuristic algorithms are proposed to generate candidate switching lists. Numerical simulations performed on three large-scale realistic power systems (TVA, ERCOT, and PJM) demonstrate that CTS can significantly reduce post-contingency violations. Parallel computing can further reduce the solution time. RT SCED is to eliminate the actual overloads and potential post-contingency overloads identified by RTCA. Procedure-A, which is consistent with existing industry practices, is proposed to connect RTCA and RT SCED. As CTS can reduce post-contingency violations, higher branch limits, referred to as pseudo limits, may be available for some contingency-case network constraints. Thus, Procedure-B is proposed to take advantage of the reliability benefits provided by CTS. With the proposed Procedure-B, CTS can be modeled in RT SCED implicitly through the proposed pseudo limits for contingency-case network constraints, which requires no change to existing RT SCED tools. Numerical simulations demonstrate that the proposed Procedure-A can effectively eliminate the flow violations reported by RTCA and that the proposed Procedure-B can reduce most of the congestion cost with consideration of CTS. The system status may be inaccurately estimated due to false data injection (FDI) cyber-attacks, which may mislead operators to adjust the system improperly and cause network violations. Thus, a two-stage FDI detection (FDID) approach, along with several metrics and an alert system, is proposed in this dissertation to detect FDI attacks. The first stage is to determine whether the system is under attack and the second stage would identify the target branch. Numerical simulations demonstrate the effectiveness of the proposed two-stage FDID approach. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2017

Automated vehicles promise to be one of the most constructive inventions of late as they promote road safety, fuel efficiency, and reduced time road travel, by decreasing traffic congestion and workload on the driver. In a platoon (which is a method of grouping vehicles, which helps increase the capacity of roads by managing the distance between vehicles by using electrical and mechanical coupling) of such automated vehicles, as in automated highway systems (AHS), tracking of inter-vehicular spacing is one of the significant factors to be considered. Because of the close spacing, computer-controlled platoons with inter-vehicular communication, which is the concept of adaptive cruise control (ACC), become open to cyber security attacks. Cyber physical and cyber attacks on smart grid systems in the electricity market have been a focus of researchers, and much work has been done on that front. However, cyber physical (CP) attacks on autonomous vehicle platoons have not been examined. Thus this research entails the survey of a number of vehicle models used in different works pertaining to longitudinal vehicle motion and analysis of a special class of cyber physical attacks called false data injection (FDI) attacks on vehicle platoons moving with longitudinal motion. In this kind of attack, an attacker can exploit the configuration of any cyber physical system to launch such attacks to successfully introduce arbitrary errors into certain state variables so as to gain control over the system. So here, an n-vehicle platoon is considered and a linearized vehicle model is used as a testbed to study vehicle dynamics and control, after false information is fed into the system.

Cyber Physical System (CPS) is a system where cyber and physical components work in a complex co-ordination to provide better performance. By exploiting the communication infrastructure among the sensors, actuators, and control systems, attackers may compromise the security of a CPS. In this dissertation, security measures for different types of attacks/ faults in two CPSs, water supply system (WSS) and smart grid system, are presented. In this context, I also present my study on energy management in Smart Grid. The techniques for detecting attacks/faults in both WSS and Smart grid system adopt Kalman Filter (KF) and χ2 detector. The χ2 -detector can detect myriad of system fault- s/attacks such as Denial of Service (DoS) attack, short term and long term random attacks. However, the study shows that the χ2 -detector is unable to detect the intelligent False Data Injection attack (FDI). To overcome this limitation, I present a Euclidean detector for smart grid which can effectively detect such injection attacks. Along with detecting attack/faults I also present the isolation of the attacked/faulty nodes for smart grid. For isolation the Gen- eralized Observer Scheme (GOS) implementing Kalman Filter is used. As GOS is effective in isolating attacks/faults on a single sensor, it is unable to isolate simultaneous attacks/faults on multiple sensors. To address this issue, an Iterative Observer Scheme (IOS) is presented which is able to detect attack on multiple sensors. Since network is an integral part of the future CPSs, I also present a scheme for pre- serving privacy in the future Internet architecture, namely MobilityFirst architecture. The proposed scheme, called Anonymity in MobilityFirst (AMF), utilizes the three-tiered ap- proach to effectively exploit the inherent properties of MF Network such as Globally Unique Flat Identifier (GUID) and Global Name Resolution Service (GNRS) to provide anonymity to the users. While employing new proposed schemes in exchanging of keys between different tiers of routers to alleviate trust issues, the proposed scheme uses multiple routers in each tier to avoid collaboration amongst the routers in the three tiers to expose the end users.

abstract: The large distributed electric power system is a hierarchical network involving the transportation of power from the sources of power generation via an intermediate densely connected transmission network to a large distribution network of end-users at the lowest level of the hierarchy. At each level of the hierarchy (generation/ trans- mission/ distribution), the system is managed and monitored with a combination of (a) supervisory control and data acquisition (SCADA); and (b) energy management systems (EMSs) that process the collected data and make control and actuation de- cisions using the collected data. However, at all levels of the hierarchy, both SCADA and EMSs are vulnerable to cyber attacks. Furthermore, given the criticality of the electric power infrastructure, cyber attacks can have severe economic and social con- sequences. This thesis focuses on cyber attacks on SCADA and EMS at the transmission level of the electric power system. The goal is to study the consequences of three classes of cyber attacks that can change topology data. These classes include: (i) unobservable state-preserving cyber attacks that only change the topology data; (ii) unobservable state-and-topology cyber-physical attacks that change both states and topology data to enable a coordinated physical and cyber attack; and (iii) topology- targeted man-in-the-middle (MitM) communication attacks that alter topology data shared during inter-EMS communication. Specically, attack class (i) and (ii) focus on the unobservable attacks on single regional EMS while class (iii) focuses on the MitM attacks on communication links between regional EMSs. For each class of attacks, the theoretical attack model and the implementation of attacks are provided, and the worst-case attack and its consequences are exhaustively studied. In particularly, for class (ii), a two-stage optimization problem is introduced to study worst-case attacks that can cause a physical line over ow that is unobservable in the cyber layer. The long-term implication and the system anomalies are demonstrated via simulation. For attack classes (i) and (ii), both mathematical and experimental analyses sug- gest that these unobservable attacks can be limited or even detected with resiliency mechanisms including load monitoring, anomalous re-dispatches checking, and his- torical data comparison. For attack class (iii), countermeasures including anomalous tie-line interchange verication, anomalous re-dispatch alarms, and external contin- gency lists sharing are needed to thwart such attacks. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2015

Radar is an acronym for RAdio Detection And Ranging. In general terms, it is a machine that uses radio waves for object-detection in its near periphery. It transmits radio waves in a known direction, which when intercepted by an obstruction/object are reflected by its surface and are received back at the radar system. The round trip delay time along with the known velocity of radio waves gives an accurate measurement of the distance of the object from the radar system. In a somewhat similar fashion, some radars are even capable of measuring the velocity of this object. Frequency-modulated continuous-wave (FMCW) radar is one such radar system, which is a subclass of continuous wave (CW) radars, where a continuous sinusoidal radio energy is transmitted, reflected, and received back at the radar system. These radar systems are widely used in vehicle automation technologies such as adaptive cruise control (ACC) and collision avoidance systems (CAS) to measure the distance from the nearest vehicles and maintain a safe following distance. But in designing these systems, little attention has been given to security, and these systems have vulnerabilities that are capable of compromising the whole purpose of making such systems. In this work one such vulnerability in FMCW radar was exploited to design an attack that was capable of decreasing the apparent distance, as measured by a radar system. The attack was designed in such a way that there was no tampering with the radar system being attacked. Instead, false distance information was introduced in the return path of the transmitted radio wave by absorbing the original victim transmission and sending out a modified radio wave on the It was shown that the distance could be decreased to alarming values, which at the level of the vehicle automation system results in decreasing the speed of the automobile when actually it should have increased.

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abstract: The electric power system is monitored via an extensive network of sensors in tandem with data processing algorithms, i.e., an intelligent cyber layer, that enables continual observation and control of the physical system to ensure reliable operations. This data collection and processing system is vulnerable to cyber-attacks that impact the system operation status and lead to serious physical consequences, including systematic problems and failures. This dissertation studies the physical consequences of unobservable false data injection (FDI) attacks wherein the attacker maliciously changes supervisory control and data acquisition (SCADA) or phasor measurement unit (PMU) measurements, on the electric power system. In this context, the dissertation is divided into three parts, in which the first two parts focus on FDI attacks on SCADA and the last part focuses on FDI attacks on PMUs. The first part studies the physical consequences of FDI attacks on SCADA measurements designed with limited system information. The attacker is assumed to have perfect knowledge inside a sub-network of the entire system. Two classes of attacks with different assumptions on the attacker's knowledge outside of the sub-network are introduced. In particular, for the second class of attacks, the attacker is assumed to have no information outside of the attack sub-network, but can perform multiple linear regression to learn the relationship between the external network and the attack sub-network with historical data. To determine the worst possible consequences of both classes of attacks, a bi-level optimization problem wherein the first level models the attacker's goal and the second level models the system response is introduced. The second part of the dissertation concentrates on analyzing the vulnerability of systems to FDI attacks from the perspective of the system. To this end, an off-line vulnerability analysis framework is proposed to identify the subsets of the test system that are more prone to FDI attacks. The third part studies the vulnerability of PMUs to FDI attacks. Two classes of more sophisticated FDI attacks that capture the temporal correlation of PMU data are introduced. Such attacks are designed with a convex optimization problem and can always bypass both the bad data detector and the low-rank decomposition (LD) detector. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2017

<p>U ovoj doktorskoj disertaciji predložena je nova metoda za detekciju malicioznih napada injektiranjem loših merenja na elektroenergetski sistem. Predloženi algoritam baziran je na sinergiji statičke i dinamičke estimacije stanja, i u stanju je da detektuje ovaj tip napada u realnom vremenu, za najkritičniji scenario gde napadač ima potpuno znanje o sistemu, i neograničen pristup resursima.</p> / <p>This PhD thesis proposes a novel method for detection of malicious false data<br />injection attacks on power system. The proposed algorithm is based on<br />synergy between static and dynamic state estimators, and is capable of<br />detecting the forementioned attacks in real time, for the most critical scenarios,<br />where an attacker has complete knowledge about the compromised power<br />system and unlimited resources to stage an attack.</p>

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