Cyber-physical attacks and defences in the smart grid: a survey <s> Distribution system/customer-side attacks <s> Global energy generation and delivery systems are transitioning to a new computerized "smart grid". One of the principle components of the smart grid is an advanced metering infrastructure (AMI). AMI replaces the analog meters with computerized systems that report usage over digital communication interfaces, e.g., phone lines. However, with this infrastructure comes new risk. In this paper, we consider adversary means of defrauding the electrical grid by manipulating AMI systems. We document the methods adversaries will use to attempt to manipulate energy usage data, and validate the viability of these attacks by performing penetration testing on commodity devices. Through these activities, we demonstrate that not only is theft still possible in AMI systems, but that current AMI devices introduce a myriad of new vectors for achieving it. <s> BIB001 </s> Cyber-physical attacks and defences in the smart grid: a survey <s> Distribution system/customer-side attacks <s> The advanced metering infrastructure (AMI) is revolutionizing electrical grids. Intelligent AMI "smart meters" report real time usage data that enables efficient energy generation and use. However, aggressive deployments are outpacing security efforts: new devices from a dizzying array of vendors are being introduced into grids with little or no understanding of the security problems they represent. In this paper we develop an archetypal attack tree approach to guide penetration testing across multiple-vendor implementations of a technology class. In this, we graft archetypal attack trees modeling broad adversary goals and attack vectors to vendor-specific concrete attack trees. Evaluators then use the grafted trees as a roadmap to penetration testing. We apply this approach within AMI to model attacker goals such as energy fraud and denial of service. Our experiments with multiple vendors generate real attack scenarios using vulnerabilities identified during directed penetration testing, e.g., manipulation of energy usage data, spoofing meters, and extracting sensitive data from internal registers. More broadly, we show how we can reuse efforts in penetration testing to efficiently evaluate the increasingly large body of AMI technologies being deployed in the field. <s> BIB002 </s> Cyber-physical attacks and defences in the smart grid: a survey <s> Distribution system/customer-side attacks <s> An experiment is carried out to measure the power consumption of households. The analysis on the real measurement data shows that the significant change of power consumption arrives in a Poisson manner. Based on this experiment, a novel wireless communication scheme is proposed for the advanced metering infrastructure (AMI) in smart grid that can significantly improve the spectrum efficiency. The main idea is to transmit only when a significant power consumption change occurs. On the other hand, the policy of transmitting only when change occurs may bring a security issue; i.e., an eavesdropper can monitor the daily life of the house owner, particularly the information of whether the owner is at home. Hence, a defense scheme is proposed to combat this vulnerability by adding artificial spoofing packets. It is shown by numerical results that the defense scheme can effectively prevent the security challenge. <s> BIB003 </s> Cyber-physical attacks and defences in the smart grid: a survey <s> Distribution system/customer-side attacks <s> Advanced Metering Infrastructures (AMI) facilitate bidirectional communication between smart meters and utilities, allowing information about consumption, outages, and electricity rates to be shared reliably and efficiently. However, the numerous smart meters being connected through mesh networks open new opportunities for attackers to interfere with communications and compromise utilities' assets or steal customers' private information. The goal of this paper is to survey the various threats facing AMIs and the common attack techniques used to realize them in order to identify and understand the requirements for a comprehensive intrusion detection solution. The threat analysis leads to an extensive “attack tree” that captures the attackers' key objectives (e.g., energy theft) and the individual attack steps (e.g., eavesdropping on the network) that would be involved in achieving them. With reference to the attack tree, we show the type of information that would be required to effectively detect attacks. We also suggest that the widest coverage in monitoring the attacks can be provided by a hybrid sensing infrastructure that uses both a centralized intrusion detection system and embedded meter sensors. <s> BIB004 </s> Cyber-physical attacks and defences in the smart grid: a survey <s> Distribution system/customer-side attacks <s> The recent deployment of smart grids has proven to bring numerous advantages in terms of energy consumption reduction in both homes and businesses. A more accurate measurement of up-to-date electricity necessities through smart meters utilization leads to an enhancement in the ability of monitoring, controlling and predicting energy use. Nevertheless, it has associated drawbacks related to the privacy of customers as well, since such management might reveal their personal habits and behavior, which electrical appliances they are using at each moment, whether they are at home or not, and so on. In this article we present a privacy enhanced architecture for smart metering aimed to tackle this threat by means of a new and novel protocol encrypting individual measurements while allowing the electricity supplier to access the aggregation of the corresponding decrypted values. The technique being used is named additively homomorphic encryption, and enables the direct connection and exchange of data between electricity suppliers and final users, while preserving the privacy of the latter. <s> BIB005 </s> Cyber-physical attacks and defences in the smart grid: a survey <s> Distribution system/customer-side attacks <s> Smart meters are being rolled out in large numbers throughout the world, with proponents claiming they are a critical step in the transition to a low-carbon economy. Yet there are significant unresolved negative reactions to smart meters, principally based on the concern that smart meters might be used to infer the private activities that occur within a dwelling. Though smart meter data is classified as personal data, and as such protected under existing data protection frameworks in the EU, there are relevant exceptions, notably where the data is required for legitimate applications associated with the performance of 'regulated duties'. This paper contributes to this debate by examining the data requirements for some of the proposed applications of smart meter data within the electricity supply industry, and investigates whether the use of personal data can be minimized or even avoided. The discussion includes system balancing, demand reduction, demand response and distribution network operation and planning, and indicates that, for most of these applications, the requirements for personal data can indeed be minimized. 'Privacy friendly' alternatives are discussed. <s> BIB006 </s> Cyber-physical attacks and defences in the smart grid: a survey <s> Distribution system/customer-side attacks <s> The advanced metering infrastructure (AMI) is a crucial component of the smart grid, replacing traditional analog devices with computerized smart meters. Smart meters have not only allowed for efficient management of many end-users, but also have made AMI an attractive target for remote exploits and local physical tampering with the end goal of stealing energy. While smart meters posses multiple sensors and data sources that can indicate energy theft, in practice, the individual methods exhibit many false positives. In this paper, we present AMIDS, an AMI intrusion detection system that uses information fusion to combine the sensors and consumption data from a smart meter to more accurately detect energy theft. AMIDS combines meter audit logs of physical and cyber events with consumption data to more accurately model and detect theft-related behavior. Our experimental results on normal and anomalous load profiles show that AMIDS can identify energy theft efforts with high accuracy. Furthermore, AMIDS correctly identified legitimate load profile changes that more elementary analyses classified as malicious. <s> BIB007 </s> Cyber-physical attacks and defences in the smart grid: a survey <s> Distribution system/customer-side attacks <s> The solutions offered to-date for end-user privacy in smart meter measurements, a well-known challenge in the smart grid, have been tied to specific technologies such as batteries or assumptions on data usage without quantifying the loss of benefit (utility) that results from any such approach. Using tools from information theory and a hidden Markov model for the measurements, a new framework is presented that abstracts both the privacy and the utility requirements of smart meter data. This leads to a novel privacy-utility tradeoff problem with minimal assumptions that is tractable. For a stationary Gaussian model of the electricity load, it is shown that for a desired mean-square distortion (utility) measure between the measured and revealed data, the optimal privacy-preserving solution: i) exploits the presence of high-power but less private appliance spectra as implicit distortion noise, and ii) filters out frequency components with lower power relative to a distortion threshold; this approach encompasses many previously proposed approaches to smart meter privacy. <s> BIB008 </s> Cyber-physical attacks and defences in the smart grid: a survey <s> Distribution system/customer-side attacks <s> Advanced Metering Infrastructure (AMI) is the core component in a smart grid that exhibits a highly complex network configuration. AMI shares information about consumption, outages, and electricity rates reliably and efficiently by bidirectional communication between smart meters and utilities. However, the numerous smart meters being connected through mesh networks open new opportunities for attackers to interfere with communications and compromise utilities assets or steal customers private information. In this paper, we present a new DoS attack, called puppet attack, which can result in denial of service in AMI network. The intruder can select any normal node as a puppet node and send attack packets to this puppet node. When the puppet node receives these attack packets, this node will be controlled by the attacker and flood more packets so as to exhaust the network communication bandwidth and node energy. Simulation results show that puppet attack is a serious and packet deliver rate goes down to 20%-10%. <s> BIB009 </s> Cyber-physical attacks and defences in the smart grid: a survey <s> Distribution system/customer-side attacks <s> In today?s Smart Grid, the power Distribution System Operator (DSO) uses real-time measurement data from the Advanced Metering Infrastructure (AMI) for efficient, accurate and advanced monitoring and control. Smart Grids are vulnerable to sophisticated data integrity attacks like the False Data Injection (FDI) attack on the AMI sensors that produce misleading operational decision of the power system (Liu et al., 2011 1]). Presently, there is a lack of research in the area of power system analysis that relates the FDI attacks with system stability that is important for both analysis of the effect of cyber-attack and for taking preventive measures of protection.In this paper, we study the physical characteristics of the power system, and draw a relationship between the system stability indices and the FDI attacks. We identify the level of vulnerabilities of each AMI node in terms of different degrees of FDI attacks. In order to obtain the interdependent relationship of different nodes, we implement an improved Constriction Factor Particle Swarm Optimization (CF-PSO) based hybrid clustering technique to group the nodes into the most, the moderate and the least vulnerable clusters. With extensive experiments and analysis using two benchmark test systems, we show that the nodes in the most vulnerable cluster exhibit higher likelihood of de-stabilizing system operation compared to other nodes. Complementing research is the construction of FDI attacks and their countermeasures, this paper focuses on the understanding of characteristics and practical effect of FDI attacks on the operation of the Smart Grid by analysing the interdependent nature of its physical properties. <s> BIB010 </s> Cyber-physical attacks and defences in the smart grid: a survey <s> Distribution system/customer-side attacks <s> Advanced Metering Infrastructure (AMI) is the core component in a smart grid that exhibits a highly complex network configuration. AMI shares information about consumption, outages, and electricity rates reliably and efficiently by bidirectional communication between smart meters and utilities. However, the numerous smart meters being connected through mesh networks open new opportunities for attackers to interfere with communications and compromise utilities assets or steal customers private information.In this paper, we present a new DoS attack, called puppet attack, which can result in denial of service in AMI network. The intruder can select any normal node as a puppet node and send attack packets to this puppet node. When the puppet node receives these attack packets, this node will be controlled by the attacker and flood more packets so as to exhaust the network communication bandwidth and node energy. Simulation results show that puppet attack is a serious and packet deliver rate goes down to 20-10%. After analyzing the puppet attack, we propose the detection and prevention mechanism. Simulations show that puppet attack causes the same damage as a flooding attack and the proposed method can prevent the puppet attack efficiently. <s> BIB011
Millions of smart meters have been installed in the AMI systems across the USA and more are on the way. These smart meters provide RT two-way communication between customers and the utility. In general, the AMI system is composed of smart meters, data concentrators/aggregators, and AMI head-ends, which has been hierarchically deployed from customers to the distribution systems BIB003 . Owing to budget and hardware limitations, smart meters only carry limited or light-weight security mechanisms against malicious attacks  BIB004 . This makes them vulnerable and frequent targets of CP attacks. Although each meter has limited impacts on the system stability when compromised, the CP threat of AMI attacks is not negligible, particularly when a cluster of smart meters has been attacked BIB010 . To date, energy thefts BIB001 BIB007 and information/privacy leakages  BIB005 BIB006 BIB008 have been identified as the most prominent threats to the AMI system. The former will result in economic losses at various scales, while the latter maybe exploited to infer customer behaviours and personal information. In addition, the threat of denial-of-service attacks is also a critical issue in the smart grid, as it limits the availability of reliable and available measurements BIB002 . By compromising any smart meters, an attacker can exploit the ubiquitous two-way communication to flood the AMI system with malicious packets, which may effectively paralyse the metering networks BIB009 BIB011 .