Bad Data Injection Attack and Defense in Electricity Market using Game Theory Study

Applications of cyber technologies improve the quality of monitoring and decision making in smart grid. These cyber technologies are vulnerable to malicious attacks, and compromising them can have serious technical and economical problems. This paper specifies the effect of compromising each measurement on the price of electricity, so that the attacker is able to change the prices in the desired direction (increasing or decreasing). Attacking and defending all measurements are impossible for the attacker and defender, respectively. This situation is modeled as a zero sum game between the attacker and defender. The game defines the proportion of times that the attacker and defender like to attack and defend different measurements, respectively. From the simulation results based on the PJM 5 Bus test system, we can show the effectiveness and properties of the studied game.Comment: To appear in IEEE Transactions on Smart Grid, Special Issue on Cyber, Physical, and System Security for Smart Gri

Reinforcement Learning and Game Theory for Smart Grid Security

This dissertation focuses on one of the most critical and complicated challenges facing electric power transmission and distribution systems which is their vulnerability against failure and attacks. Large scale power outages in Australia (2016), Ukraine (2015), India (2013), Nigeria (2018), and the United States (2011, 2003) have demonstrated the vulnerability of power grids to cyber and physical attacks and failures. These incidents clearly indicate the necessity of extensive research efforts to protect the power system from external intrusion and to reduce the damages from post-attack effects. We analyze the vulnerability of smart power grids to cyber and physical attacks and failures, design different gametheoretic approaches to identify the critical components vulnerable to attack and propose their associated defense strategy, and utilizes machine learning techniques to solve the game-theoretic problems in adversarial and collaborative adversarial power grid environment. Our contributions can be divided into three major parts:Vulnerability identification: Power grid outages have disastrous impacts on almost every aspect of modern life. Despite their inevitability, the effects of failures on power grids’ performance can be limited if the system operator can predict and identify the vulnerable elements of power grids. To enable these capabilities we study machine learning algorithms to identify critical power system elements adopting a cascaded failure simulator as a threat and attack model. We use generation loss, time to reach a certain percentage of line outage/generation loss, number of line outages, etc. as evaluation metrics to evaluate the consequences of threat and attacks on the smart power grid.Adversarial gaming in power system: With the advancement of the technologies, the smart attackers are deploying different techniques to supersede the existing protection scheme. In order to defend the power grid from these smart attackers, we introduce an adversarial gaming environment using machine learning techniques which is capable of replicating the complex interaction between the attacker and the power system operators. The numerical results show that a learned defender successfully narrows down the attackers’ attack window and reduce damages. The results also show that considering some crucial factors, the players can independently execute actions without detailed information about each other.Deep learning for adversarial gaming: The learning and gaming techniques to identify vulnerable components in the power grid become computationally expensive for large scale power systems. The power system operator needs to have the advanced skills to deal with the large dimensionality of the problem. In order to aid the power system operator in finding and analyzing vulnerability for large scale power systems, we study a deep learning technique for adversary game which is capable of dealing with high dimensional power system state space with less computational time and increased computational efficiency. Overall, the results provided in this dissertation advance power grids’ resilience and security by providing a better understanding of the systems’ vulnerability and by developing efficient algorithms to identify vulnerable components and appropriate defensive strategies to reduce the damages of the attack

Approaches to the Security Analysis of Power Systems: Defence Strategies Against Malicious Threats

This report is intended to provide a conceptual framework for assessing the security risk to power systems assets and operations related to malicious attacks. The problem is analysed with reference to all the actors involved and the possible targets. The specific nature of the malicious attacks is discussed and representations in terms of strategic interaction are proposed. Models based on Game Theory and Multi Agent Systems techniques specifically developed for the representation of malicious attacks against power systems are presented and illustrated with reference to applications to small-scale test systems.JRC.G.6-Sensors, radar technologies and cybersecurit

Bibliographical review on cyber attacks from a control oriented perspective

This paper presents a bibliographical review of definitions, classifications and applications concerning cyber attacks in networked control systems (NCSs) and cyber-physical systems (CPSs). This review tackles the topic from a control-oriented perspective, which is complementary to information or communication ones. After motivating the importance of developing new methods for attack detection and secure control, this review presents security objectives, attack modeling, and a characterization of considered attacks and threats presenting the detection mechanisms and remedial actions. In order to show the properties of each attack, as well as to provide some deeper insight into possible defense mechanisms, examples available in the literature are discussed. Finally, open research issues and paths are presented.Peer ReviewedPostprint (author's final draft

Security Aspects of Internet of Things aided Smart Grids: a Bibliometric Survey

The integration of sensors and communication technology in power systems, known as the smart grid, is an emerging topic in science and technology. One of the critical issues in the smart grid is its increased vulnerability to cyber threats. As such, various types of threats and defense mechanisms are proposed in literature. This paper offers a bibliometric survey of research papers focused on the security aspects of Internet of Things (IoT) aided smart grids. To the best of the authors' knowledge, this is the very first bibliometric survey paper in this specific field. A bibliometric analysis of all journal articles is performed and the findings are sorted by dates, authorship, and key concepts. Furthermore, this paper also summarizes the types of cyber threats facing the smart grid, the various security mechanisms proposed in literature, as well as the research gaps in the field of smart grid security.Comment: The paper is published in Elsevier's Internet of Things journal. 25 pages + 20 pages of reference

Using Gamification to Raise Awareness of Cyber Threats to Critical National Infrastructure

Linked to the SCIPS tabletop gameSenior executives of critical national infrastructure facilities face competing requirements for investment budgets. Whilst the impact of a cyber attack upon such utilities is potentially catastrophic, the risks to continued operations from failing to upgrade ageing infrastructure, or not meeting mandated regulatory regimes, are considered higher given the demonstrable impact of such circumstances. As cyber attacks on critical national infrastructure remain low-frequency events, there is little to motivate business leaders to increase their investment in cyber defences to comparable levels. This paper describes SCIPS, a gamified environment in which senior executives experience the impact of a cyber attack on an electric power generation plant, demonstrating how it can strategically affect shareholder value, and allows them to form their own views on the relative importance of cyber security investment

Application of Artificial Intelligence to the Development of Playing Ability in the Valorant Game

 From children to adults, everyone enjoys playing online games as a form of entertainment. Online games have a more popular market because they can meet other players worldwide connected to the internet. NPCs (players controlled by a computer system) are also available in online games as player substitutes or for skill practice. As a result, we have been interacting with artificial intelligence in the competition and our environment without realizing it. The game's AI (Artificial Intelligent) can offer an experience similar to playing with other players. Artificial intelligence may always influence online games, whether to replace opponents or choose the game's plot. First Person Shooter (FPS) game Valorant was made available for free on the Windows platform by Riot Games. With a CS: GO-like concept (Counter Strike Global Offensive). The amount of money you have available for each round must be calculated at the equipment purchasing phase to produce effective gaming equipment. The Greedy Algorithm is one of the algorithms that can be used to choose the equipment for the money/cred owned. This algorithm will select the most expensive item the player can buy each round so that the player's chances of winning that round increase

Optimizing MAKWA on GPU and CPU

We present here optimized implementations of the MAKWA password hashing function on an AMD Radeon HD 7990 GPU, and compare its efficiency with an Intel i7 4770K CPU for systematic dictionary attacks. We find that the GPU seems to get more hashing done for a given budget, but not by a large amount (the GPU is less than twice as efficient as the CPU). Raising the MAKWA modulus size to 4096 bits, instead of the default 2048 bits, should restore the balance in favour of the CPU. We also find that power consumption, not hardware retail price, is likely to become the dominant factor for industrialized, long-term attacking efforts

Security-by-experiment: lessons from responsible deployment in cyberspace

Conceiving new technologies as social experiments is a means to discuss responsible deployment of technologies that may have unknown and potentially harmful side-effects. Thus far, the uncertain outcomes addressed in the paradigm of new technologies as social experiments have been mostly safetyrelated, meaning that potential harm is caused by the design plus accidental events in the environment. In some domains, such as cyberspace, dversarial agents (attackers)may be at least as important when it comes to undesirable effects of deployed technologies. In such cases, conditions for responsible experimentation may need to be implemented differently, as attackers behave strategically rather than probabilistically. In this contribution, we outline how adversarial aspects are already taken into account in technology deployment in the field of cyber security, and what the paradigm of new technologies as social experiments can learn from this. In particular, we show the importance of adversarial roles in social experiments with new technologies