A Comprehensive Review Study of Cyber-Attacks and Cyber Security

In today's world, the majority of governmental, cultural, social, economic, and commercial interactions and activities take place online. This includes interactions between nations, individuals, NGOs, and government agencies. The threat of cyberattacks and wireless communication technologies has recently become an issue for numerous private organisations and government agencies across the globe. Nowadays, our world relies heavily on electronic technology, and safeguarding this data from cyber-attacks is no easy feat. Cybercriminals target businesses with the intention of stealing money. Cyberattacks may also serve political or military objectives in certain instances. Computer viruses, information breaches, data distribution services (DDS), and other attack vectors are among the causes of these damages. In order to accomplish this goal, different organisations employ different strategies to safeguard against cyberattacks. The most recent information technology data is tracked in real-time by cyber security. So far, academics from all around the globe have suggested a number of ways to either stop cyberattacks in their tracks or at least mitigate the harm they do. A few of the approaches have moved on to the study phase, while others are still in the operational stage. The purpose of this research is to examine the offered approaches, identify their strengths and shortcomings, and conduct a thorough evaluation of the standard advancements made in the area of cyber security

Reliability Evaluation and Defense Strategy Development for Cyber-physical Power Systems

With the smart grid initiatives in recent years, the electric power grid is rapidly evolving into a complicated and interconnected cyber-physical system. Unfortunately, the wide deployment of cutting-edge communication, control and computer technologies in the power system, as well as the increasing terrorism activities, make the power system at great risk of attacks from both cyber and physical domains. It is pressing and meaningful to investigate the plausible attack scenarios and develop efficient methods for defending the power system against them. To defend the power grid, it is critical to first study how the attacks could happen and affect the power system, which are the basis for the defense strategy development. Thus, this dissertation quantifies the influence of several typical attacks on power system reliability. Specifically, three representative attack are considered, i.e., intrusion against substations, regional LR attack, and coordinated attacks. For the intrusion against substations, the occurrence frequency of the attack events is modeled based on statistical data and human dynamics; game-theoretical approaches are adopted to model induvial and consecutive attack cases; Monte Carlo simulation is deployed to obtain the desired reliability indices, which incorporates both the attacks and the random failures. For the false data injection attack, a practical regional load redistribution (LR) attack strategy is proposed; the man-in-the-middle (MITM) intrusion process is modeled with a semi-Markov process method; the reliability indices are obtained based on the regional LR attack strategy and the MITM intrusion process using Monte Carlo simulation. For the coordinated attacks, a few typical coordination strategies are proposed considering attacking the current-carrying elements as well as attacking the measurements; a bilevel optimization method is applied to develop the optimal coordination strategy. Further, efficient and effective defense strategies are proposed from the perspectives of power system operation strategy and identification of critical elements. Specially, a robustness-oriented power grid operation strategy is proposed considering the element random failures and the risk of man-made attacks. Using this operation strategy, the power system operation is robust, and can minimize the load loss in case of malicious man-made attacks. Also, a multiple-attack-scenario (MAS) defender-attack-defender model is proposed to identify the critical branches that should be defended when an attack is anticipated but the defender has uncertainty about the capability of the attacker. If those identified critical branches are protected, the expected load loss will be minimal

Comprehensive Survey and Taxonomies of False Injection Attacks in Smart Grid: Attack Models, Targets, and Impacts

Smart Grid has rapidly transformed the centrally controlled power system into a massively interconnected cyber-physical system that benefits from the revolutions happening in the communications (e.g. 5G) and the growing proliferation of the Internet of Things devices (such as smart metres and intelligent electronic devices). While the convergence of a significant number of cyber-physical elements has enabled the Smart Grid to be far more efficient and competitive in addressing the growing global energy challenges, it has also introduced a large number of vulnerabilities culminating in violations of data availability, integrity, and confidentiality. Recently, false data injection (FDI) has become one of the most critical cyberattacks, and appears to be a focal point of interest for both research and industry. To this end, this paper presents a comprehensive review in the recent advances of the FDI attacks, with particular emphasis on 1) adversarial models, 2) attack targets, and 3) impacts in the Smart Grid infrastructure. This review paper aims to provide a thorough understanding of the incumbent threats affecting the entire spectrum of the Smart Grid. Related literature are analysed and compared in terms of their theoretical and practical implications to the Smart Grid cybersecurity. In conclusion, a range of technical limitations of existing false data attack research is identified, and a number of future research directions is recommended.Comment: Double-column of 24 pages, prepared based on IEEE Transaction articl

Reliability in a smart power system with cyber-physical interactive operation of photovoltaic systems and heat pumps

The connectivity of the power grid is increasing with the internet of things, and low carbon technologies being deployed to help enhance smart grid performance and reliability. Meanwhile, they also increase the digital complexity and dependency of cyber assets, which might be vulnerable to cyber-physical threats, and hence may impact the reliability of power systems. Due to cyber-threats’ unpredictable nature, the interactive operation of low carbon technologies with cyber-physical systems is becoming a challenging task for smart grids. This thesis proposes novel mathematical frameworks to estimate the availability of photovoltaics and heat pumps with cyber-physical components. These frameworks are developed to quantify the level of risk posed by cyber-threats to the interactive operation of photovoltaics and heat pumps, using Markov-Chains. The availability framework considers the severity of random cyber-attacks on photovoltaics and the probability of cyber-threats with mean time to detection-time on heat pump operation. Sensitivities of the repair times of cyber-physical component for photovoltaics and sensitivities of cyber-attack-detection time for heat pumps are also evaluated. The impact of cyber threats on the interactive operation of photovoltaics and heat pumps are considerable and inconsistent, however the propagation of cyber-threats can be restricted by appropriate means of photovoltaics. For heat pumps, operational reliability substantially decreases due to the unavailability of their control panel. Contributions of this thesis include an availability model for photovoltaic configurations, an innovative approach to assess the reliability of a photovoltaic integrated power system with cyber-physical interactions, the availability estimation of heat pump with variable detection time, and an enhanced cyber-intrusion process model for reliability analysis of heat pumps. The findings offer insight into the impact of cyber-physical system availability and its importance on power system reliability

Reliability Evaluation of Line Switching Operations and Investigations into Incomplete Data Issues

Research in this dissertation is mainly focused on two topics: reliability evaluation of line switching operations and the investigation into incomplete data issues observed in reliability evaluation. A method is proposed for studying the reliability implications of line switching operations in power systems. This method is designed to explore previously overlooked areas, study objectives and study measures, in reliability evaluation of line switching operations. Line removal test is proposed to obtain simulation data of the system, and then with risk analysis and impact analysis, six reliability indices are used to evaluate reliability performance of each transmission line in the system. Weibull distribution is used to reconstruct distributions of reliability indices which provide variance analysis and worst-case scenario comparisons. Eventually, with results obtained, categorization for line switching operations is introduced to classify all transmission lines based on their reliability performance. The categories provide reliability implications of line switching operations and can be used for guidance in actual operations. This method is tested in two case studies: IEEE Reliability Test System (RTS) and IEEE 118-bus system. Both case studies validate the effectiveness of this method. A contingency ranking (CR) method is introduced as a pre-selection method to create a hybrid reliability evaluation method. The objective is not only to speed up the simulation but also to provide analytical analysis of state space. The differences between event-based and yearly-based indices are analyzed to better understand the results of the proposed method. Two case studies on IEEE RTS and IEEE 118-bus system conclude that this method have high accuracy in identifying critical lines with a significant improvement in calculation speed. To resolve incomplete data issues observed in reliability evaluation, mathematical conditions are derived for the probabilities obtained from the Markov model using transition rates to be identical with those obtained from the state residence times. This research provides guidance on building or recovering transition rate matrix in the absence of complete data. This research also shows equivalent transition rates with implicit assumption of exponential distribution is not affected by the probability distribution of state residence times in steady state analysis

Strategies to Manage Hydroelectricity Interruptions in Zambian Manufacturing Businesses

Interruptions of hydroelectric energy damage equipment and reduce worker productivity. Manufacturing leaders in Zambia who lack strategies to manage hydroelectricity interruptions risk financial losses. Grounded in contingency theory, the purpose of this qualitative multiple case study was to explore strategies that some manufacturing leaders use to manage hydroelectricity interruptions. The participants were six managers from different manufacturing industries based in Lusaka, Zambia, who implemented strategies to manage hydropower interruptions. Data collection involved semistructured interviews and review of company documents, company websites, and publications from the Zambia Association of Manufacturers related to managing hydroelectricity power interruptions. Thematic analysis was used to analyze the data. Four themes emerged: managing stock gaps, use of generators (turn-time), managing cost of labor input, and investment in stabilizers and storage facilities. Key recommendations include investment in alternative power generating equipment and upgrading of plant transformers. The implication for positive social change includes the potential to create jobs and improve the local economy and subsequent tax base

Power system reliability enhancement with reactive power compensation and operational risk assessment with smart maintenance for power generators

Modern power systems incorporate advanced contingency measures with the aim of enhancing system performance. Among them, the strategical installation of reactive power compensators into a power system is commonly practised to minimize power losses and improve system reliability. Such a practice requires a robust optimization technique that could reduce the computational burden and provide optimal planning and operation of the compensators. This thesis proposes an advanced optimization technique, named as Accelerated Quantum Particle Swarm Optimization (AQPSO) to determine the optimal placement, sizing and dispatch strategy of the reactive power compensators with the aim of improving the system level reliability. The uniqueness of the technique is the incorporation of the concept ‘best observation’, which accelerates the search towards the optimal solution. The implementation of advanced maintenance strategies is another common contingency measure used to enhance system performance. In this context, this thesis proposes a novel Smart Maintenance (SM) strategy for power generators that maximize the generation adequacy and provide increased economic benefits in a framework of system reliability. The uniqueness of the SM approach is the incorporation of the ‘obsolescence’ state through the stages of the bathtub curve and half-arch shape to model the aging process and then quantify the operational risk of the generators using fuzzy logic theory. Further, SM combines the proposed AQPSO and Sequential Median Latin Hypercube to obtain a comprehensive maintenance schedule. The investigation presented in this thesis contributes with novel AQPSO-based algorithms to enhance power system reliability with the operation of reactive power compensation; a more realistic and accurate aging reliability model of power generators; a detailed SM mathematical framework and an algorithm for the scheduling of proactive maintenance of generators of small and large-power systems. The proposed models are significant in the journey to the smart operation of a power system with diverse levels of applications