CEEME: compensating events based execution monitoring enforcement for Cyber-Physical Systems

Fundamentally, inherently observable events in Cyber-Physical Systems with tight coupling between cyber and physical components can result in a confidentiality violation. By observing how the physical elements react to cyber commands, adversaries can identify critical links in the system and force the cyber control algorithm to make erroneous decisions. Thus, there is a propensity for a breach in confidentiality leading to further attacks on availability or integrity. Due to the highly integrated nature of Cyber-Physical Systems, it is also extremely difficult to map the system semantics into a security framework under existing security models. The far-reaching objective of this research is to develop a science of selfobfuscating systems based on the composition of simple building blocks. A model of Nondeducibility composes the building blocks under Information Flow Security Properties. To this end, this work presents fundamental theories on external observability for basic regular networks and the novel concept of event compensation that can enforce Information Flow Security Properties at runtime --Abstract, page iii

A New Relaying Method for Third Zone Distance Relay Blocking During Power Swings

Due to the increasing complexity of modern bulk power systems, the power swing identification, blocking, and protection have become more challenging than they used to be. Among various transmission line protection methods, distance relays are the most commonly used type. One of the advantages of using distance relays is the zoned protection which provides redundancy. However, the additional redundancy comes with a problem that it increases the probability of incorrect operation. For example, the undesired operation of the third zone distance protection during power swing scenarios has been attributed as one of the major causes for creating large-scale blackouts. Some research works in the literature investigate proper identification of stable and unstable power swing conditions. Most research works dwell on identification of power swing conditions but do not address how the scheme could be used for blocking the third zone of distance relays during stable power swings. Also, the current power swing detection schemes are often very complex to implement for a relaying engineer or are not fast enough for blocking the third zone distance element. This research proposes a reliable and fast methodology for the third zone blocking (TZB) during power swings. The new mathematical formulations and derivations are based on sound time tested power system theory and are simpler to understand for a relaying engineer to implement this technique. The algorithm proposed in the research can prevent unnecessary tripping of distance relays during power swings. The algorithm also overcomes the shortcomings of the conventional power swing identification methods when applied for the third zone blocking. A first zero-crossing (FZC) concept is introduced as the criteria for identifying stable power swing or out-of-step phenomena. The analysis is based on system stability point of view and utilizes power-angle equations. The proposed algorithm could be applied at every discrete time interval or time step of a distance relay to detect power swing points. It could also be applied to any transmission line in the power system by finding an equivalent single machine infinite bus (SMIB) configuration individually for each line on a real-time basis, which is one of the primary advantages of the proposed method. In the thesis work, the proposed technique is first demonstrated using a simple single machine infinite bus system. The TZB algorithm is then tested using a modified Western Electricity Coordinating Council (WSCC) power system configuration using Power System Analysis Toolbox (PSAT) simulations. The code is written in MATLAB. The TZB method is then further analyzed using electromagnetic simulations with Real-Time Digital Simulator (RTDS) on WSCC system. The proposed method uses small time step simulations (50 μs) to take various aspects of power system complexity into consideration, such as different harmonics presents in the system, synchronous machine operation at different speeds, travelling wave representation of transmission lines instead of purely lumped parameter representation, etc. The investigations as mentioned above and the results show that the proposed TZB scheme is a straightforward and reliable technique, involving only a few calculation steps, and could be applied to any power system configuration. The main novelty of this technique is that it does not require a priori stability study to find the relay settings unlike conventional power swing identification or distance relay blocking techniques. The inputs to the relay are basic electrical quantities which could be easily measured locally on any transmission line. The local measurements would make the implementation of the proposed TZB simpler for relaying applications compared to Wide Area Measurement System (WAMS) based techniques. In a WAMS based relaying technique - the cost associated with the communication network, reliability of the communication network, impact of communication delay on relay, etc all become factors for actual industry use

Application of Advanced Early Warning Systems with Adaptive Protection

This project developed and field-tested two methods of Adaptive Protection systems utilizing synchrophasor data. One method detects conditions of system stress that can lead to unintended relay operation, and initiates a supervisory signal to modify relay response in real time to avoid false trips. The second method detects the possibility of false trips of impedance relays as stable system swings “encroach” on the relays’ impedance zones, and produces an early warning so that relay engineers can re-evaluate relay settings. In addition, real-time synchrophasor data produced by this project was used to develop advanced visualization techniques for display of synchrophasor data to utility operators and engineers

Adaptive techniques for scalable optimistic parallel discrete event simulation

Discrete Event Simulation (DES) can be an important tool across various domains such as Engineering, Military, Biology, High Performance Computing, and many others. Interacting systems in these domains can be simulated with a high degree of fidelity and accuracy. Furthermore, DES simulations do not rely on a global time step and simulated entities are only updated at discrete points in virtual time at which events occur. The particular DES simulation engine handles simulation logic and event scheduling, while the particular models written by domain experts need only focus on model-specific logic. As models grow in size and complexity, running simulations in parallel becomes an attractive option. However, a number of issues need to be addressed in order to effectively run DES simulations in parallel in a distributed environment. The issue of how to synchronize PDES simulations has been addressed in a number of ways, using various types of either conservative or optimistic protocols. Optimistic simulation synchronization has shown several benefits over conservative synchronization, but it is also more complex and brings with it some unique challenges. Two of these challenges are synchronizing event execution across distributed processes, and maintaining a high accuracy in the speculative execution of events. This thesis aims to address these challenges in order to make optimistic simulations even more effective and reliable. Specifically, this thesis explores a variety of GVT algorithms in an attempt to lower synchronization costs, while utilizing other techniques such as dynamic load balancing to maintain a high event execution efficiency and keep work balanced across execution units. Most importantly, these techniques aim to make the simulator robust and adaptive, allowing it to work effectively for a variety of models with different characteristics and irregularities

Verifying big data topologies by-design: a semi-automated approach

Big data architectures have been gaining momentum in recent years. For instance, Twitter uses stream processing frameworks like Apache Storm to analyse billions of tweets per minute and learn the trending topics. However, architectures that process big data involve many different components interconnected via semantically different connectors. Such complex architectures make possible refactoring of the applications a difficult task for software architects, as applications might be very different with respect to the initial designs. As an aid to designers and developers, we developed OSTIA (Ordinary Static Topology Inference Analysis) that allows detecting the occurrence of common anti-patterns across big data architectures and exploiting software verification techniques on the elicited architectural models. This paper illustrates OSTIA and evaluates its uses and benefits on three industrial-scale case-studies

Power System Stability Analysis Using Wide Area Measurement System

Advances in wide area measurement systems have transformed power system operation from simple visualization, state estimation, and post-mortem analysis tools to real-time protection and control at the systems level. Transient disturbances (such as lightning strikes) exist only for a fraction of a second but create transient stability issues and often trigger cascading type failures. The most common practice to prevent instabilities is with local generator out-of-step protection. Unfortunately, out-of-step protection operation of generators may not be fast enough, and an instability may take down nearby generators and the rest of the system by the time the local generator relay operates. Hence, it is important to assess power system stability over transmission lines as soon as the transient instability is detected instead of relying on purely localized out-of-step protection in generators. This thesis proposes a synchrophasor-based out-of-step prediction methodology at the transmission line level using wide area measurements from optimal phasor measurement unit (PMU) locations in the interconnected system. Voltage and current measurements from wide area measurement systems (WAMS) are utilized to find the swing angles. The proposed scheme was used to predict the first swing out-of-step condition in a Western Systems Coordinating Council (WSCC) 9 bus power system. A coherency analysis was first performed in this multi-machine system to determine the two coherent groups of generators. The coherent generator groups were then represented with a two-machine equivalent system, and the synchrophasor-based out-of-step prediction algorithm then applied to the reduced equivalent system. The coherency among the group of generators was determined within 100 ms for the contingency scenarios tested. The proposed technique is able to predict the instability 141.66 to 408.33 ms before the system actually reaches out-of-step conditions. The power swing trajectory is either a steady-state trajectory, monotonically increasing type (when the system becomes unstable), or oscillatory type (under stable conditions). Un- der large disturbance conditions, the swing could also become non-stationary. The mean and variance of the signal is not constant when it is monotonically increasing or non-stationary. An autoregressive integrated (ARI) approach was developed in this thesis, with differentiation of two successive samples done to make the mean and variance constant and facilitate time series prediction of the swing curve. Electromagnetic transient simulations with a real-time digital simulator (RTDS) were used to test the accuracy of the proposed algorithm with respect to predicting transient in- stability conditions. The studies show that the proposed method is computationally efficient and accurate for larger power systems. The proposed technique was also compared with a conventional two blinder technique and swing center voltage method. The proposed method was also implemented with actual PMU measurements from a relay (General Electric (GE) N60 relay). The testing was carried out with an interface between the N60 relay and the RTDS. The WSCC 9 bus system was modeled in the simulator and the analog time signals from the optimal location in the network communicated to the N60 relay. The synchrophasor data from the PMUs in the N60 were used to back-calculate the rotor angles of the generators in the system. Once the coherency was established, the swing curves for the coherent group of generators were found from time series prediction (ARI model). The test results with the actual PMUs match quite well with the results obtained from virtual PMU-based testing in the RTDS. The calculation times for the time series prediction are also very small. This thesis also discusses a novel out-of-step detection technique that was investigated in the course of this work for an IEEE Power Systems Relaying Committee J-5 Working Group document using real-time measurements of generator accelerating power. Using the derivative or second derivative of a measurement variable significantly amplifies the noise term and has limited the actual application of some methods in the literature, such as local measurements of voltage or voltage deviations at generator terminals. Another problem with the voltage based methods is taking an average over a period; the intermediate values cancel out and, as a result, just the first and last sample values are used to find the speed. This effectively means that the sample values in between are not used. The first solution proposed to overcome this is a polynomial fitting of the points of the calculated derivative points (to calculate speed). The second solution is the integral of the accelerating power method (this eliminates taking a derivative altogether). This technique shows the direct relationship of electrical power deviation to rotor acceleration and the integral of accelerating power to generator speed deviation. The accelerating power changes are straightforward to measure and the values obtained are more stable during transient conditions. A single machine infinite bus (SMIB) system was used for the purpose of verifying the proposed local measurement based method

Power-Aware Resilience for Exascale Computing

To enable future scientific breakthroughs and discoveries, the next generation of scientific applications will require exascale computing performance to support the execution of predictive models and analysis of massive quantities of data, with significantly higher resolution and fidelity than what is possible within existing computing infrastructure. Delivering exascale performance will require massive parallelism, which could result in a computing system with over a million sockets, each supporting many cores. Resulting in a system with millions of components, including memory modules, communication networks, and storage devices. This increase in number of components significantly increases the propensity of exascale computing systems to faults, while driving power consumption and operating costs to unforeseen heights. To achieve exascale performance two challenges must be addressed: resilience to failures and adherence to power budget constraints. These two objectives conflict insofar as performance is concerned, as achieving high performance may push system components past their thermal limit and increase the likelihood of failure. With current systems, the dominant resilience technique is checkpoint/restart. It is believed, however, that this technique alone will not scale to the level necessary to support future systems. Therefore, alternative methods have been suggested to augment checkpoint/restart -- for example process replication. In this thesis, we present a new fault tolerance model called shadow replication that addresses resilience and power simultaneously. Shadow replication associates a shadow process with each main process, similar to traditional replication, however, the shadow process executes at a reduced speed. Shadow replication reduces energy consumption and produces solutions faster than checkpoint/restart and other replication methods in limited power environments. Shadow replication reduces energy consumption up to 25 depending upon the application type, system parameters, and failure rates. The major contribution of this thesis is the development of shadow replication, a power-aware fault tolerant computational model. The second contribution is an execution model applying shadow replication to future high performance exascale-class systems. Next, is a framework to analyze and simulate the power and energy consumption of fault tolerance methods in high performance computing systems. Lastly, to prove the viability of shadow replication an implementation is presented for the Message Passing Interface

Secure Virtualization and Multicore Platforms State-of-the-Art report

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