Biblio

While there has been considerable research on making power grid Supervisory Control and Data Acquisition (SCADA) systems resilient to attacks, the problem of transitioning these technologies into deployed SCADA systems remains largely unaddressed. We describe our experience and lessons learned in deploying an intrusion-tolerant SCADA system in two realistic environments: a red team experiment in 2017 and a power plant test deployment in 2018. These experiences resulted in technical lessons related to developing an intrusion-tolerant system with a real deployable application, preparing a system for deployment in a hostile environment, and supporting protocol assumptions in that hostile environment. We also discuss some meta-lessons regarding the cultural aspects of transitioning academic research into practice in the power industry.

Processing smart grid data for analytics purposes brings about a series of privacy-related risks. In order to allow for the most suitable mitigation strategies, reasonable privacy risks need to be addressed by taking into consideration the perspective of each smart grid stakeholder separately. In this context, we use the notion of privacy concerns to reflect potential privacy risks from the perspective of different smart grid stakeholders. Privacy concerns help to derive privacy goals, which we represent using the goals structuring notation. Thus represented goals can more comprehensibly be addressed through technical and non-technical strategies and solutions. The thread of argumentation - from concerns to goals to strategies and solutions - is presented in form of a privacy case, which is analogous to the safety case used in the automotive domain. We provide an exemplar privacy case for the smart grid developed as part of the Aspern Smart City Research project.

Cascading failure, which can be triggered by both physical and cyber attacks, is among the most critical threats to the security and resilience of power grids. In current literature, researchers investigate the issue of cascading failure on smart grids mainly from the attacker's perspective. From the perspective of a grid defender or operator, however, it is also an important issue to restore the smart grid suffering from cascading failure back to normal operation as soon as possible. In this paper, we consider cascading failure in conjunction with the restoration process involving repairing of the failed nodes/links in a sequential fashion. Based on a realistic power flow cascading failure model, we exploit a Q-learning approach to develop a practical and effective policy to identify the optimal way of sequential restorations for large-scale smart grids. Simulation results on three power grid test benchmarks demonstrate the learning ability and the effectiveness of the proposed strategy.

With the rapid development of Internet of Things applications, the power Internet of Things technologies and applications covering the various production links of the power grid "transmission, transmission, transformation, distribution and use" are becoming more and more popular, and the terminal, network and application security risks brought by them are receiving more and more attention. Combined with the architecture and risk of power Internet of Things, this paper first proposes the overall security protection technology system and strategy for power Internet of Things; then analyzes terminal identity authentication and authority control, edge area autonomy and data transmission protection, and application layer cloud fog security management. And the whole process real-time security monitoring; Finally, through the analysis of security risks and protection, the technical difficulties and directions for the security protection of the Internet of Things are proposed.

In order to make up for the shortcomings of traditional evaluation methods neglecting node difference, a vulnerability assessment method considering node heterogeneity for cyber physical power system (CPPS) is proposed. Based on the entropy of the power flow and complex network theory, we establish heterogeneity evaluation index system for CPPS, which considers the survivability of island survivability and short-term operation of the communication network. For mustration, hierarchical CPPS model and distributed CPPS model are established respectively based on partitioning characteristic and different relationships of power grid and communication network. Simulation results show that distributed system is more robust than hierarchical system of different weighting factor whether under random attack or deliberate attack and a hierarchical system is more sensitive to the weighting factor. The proposed method has a better recognition effect on the equilibrium of the network structure and can assess the vulnerability of CPPS more accurately.

The risk of large-scale blackouts and cascading failures in power grids can be due to vulnerable transmission lines and lack of proper remediation techniques after recognizing the first failure. In this paper, we assess the vulnerability of a system using fault chain theory and a power flow-based method, and calculate the probability of large-scale blackout. Further, we consider a Remedial Action Scheme (RAS) to reduce the vulnerability of the system and to harden the critical components against intentional attacks. To identify the most critical lines more efficiently, a new vulnerability index is presented. The effectiveness of the new index and the impact of the applied RAS is illustrated on the IEEE 14-bus test system.

Integrated cyber-physical systems (CPSs), such as the smart grid, are becoming the underpinning technology for major industries. A major concern regarding such systems are the seemingly unexpected large scale failures, which are often attributed to a small initial shock getting escalated due to intricate dependencies within and across the individual counterparts of the system. In this paper, we develop a novel interdependent system model to capture this phenomenon, also known as cascading failures. Our framework consists of two networks that have inherently different characteristics governing their intra-dependency: i) a cyber-network where a node is deemed to be functional as long as it belongs to the largest connected (i.e., giant) component; and ii) a physical network where nodes are given an initial flow and a capacity, and failure of a node results with redistribution of its flow to the remaining nodes, upon which further failures might take place due to overloading. Furthermore, it is assumed that these two networks are inter-dependent. For simplicity, we consider a one-to-one interdependency model where every node in the cyber-network is dependent upon and supports a single node in the physical network, and vice versa. We provide a thorough analysis of the dynamics of cascading failures in this interdependent system initiated with a random attack. The system robustness is quantified as the surviving fraction of nodes at the end of cascading failures, and is derived in terms of all network parameters involved. Analytic results are supported through an extensive numerical study. Among other things, these results demonstrate the ability of our model to capture the unexpected nature of large-scale failures, and provide insights on improving system robustness.

In recent years, there has been a significant increase in wind power penetration into the power system. As a result, the behavior of the power system has become more dependent on wind power behavior. Supervisory control and data acquisition (SCADA) systems responsible for monitoring and controlling wind farms often have vulnerabilities that make them susceptible to cyberattacks. These vulnerabilities allow attackers to exploit and intrude in the wind farm SCADA system. In this paper, a cyber-physical system (CPS) model for the information and communication technology (ICT) model of the wind farm SCADA system integrated with SCADA of the power system is proposed. Cybersecurity of this wind farm SCADA system is discussed. Proposed cyberattack scenarios on the system are modeled and the impact of these cyberattacks on the behavior of the power systems on the IEEE 9-bus modified system is investigated. Finally, an anomaly attack detection algorithm is proposed to stop the attack of tripping of all wind farms. Case studies validate the performance of the proposed CPS model of the test system and the attack detection algorithm.

The interconnection of networks between several techno-socio-economic sectors such as energy, transport, and communication, questions the manageability and resilience of the digital society. System interdependencies alter the fundamental dynamics that govern isolated systems, which can unexpectedly trigger catastrophic instabilities such as cascading failures. This paper envisions a general-purpose, yet simple prototyping of self-management software systems that can turn system interdependencies from a cause of instability to an opportunity for higher resilience. Such prototyping proves to be challenging given the highly interdisciplinary scope of interdependent networks. Different system dynamics and organizational constraints such as the distributed nature of interdependent networks or the autonomy and authority of system operators over their controlled infrastructure perplex the design for a general prototyping approach, which earlier work has not yet addressed. This paper contributes such a modular design solution implemented as an open source software extension of SFINA, the Simulation Framework for Intelligent Network Adaptations. The applicability of the software artifact is demonstrated with the introduction of a novel self-healing mechanism for interdependent power networks, which optimizes power flow exchanges between a damaged and a healer network to mitigate power cascading failures. Results show a significant decrease in the damage spread by self-healing synergies, while the degree of interconnectivity between the power networks indicates a tradeoff between links survivability and load served. The contributions of this paper aspire to bring closer several research communities working on modeling and simulation of different domains with an economic and societal impact on the resilience of real-world interdependent networks.

This paper proposes a game-theoretic approach to analyze the interactions between an attacker and a defender in a cyber-physical system (CPS) and develops effective defense strategies. In a CPS, the attacker launches cyber attacks on a number of nodes in the cyber layer, trying to maximize the potential damage to the underlying physical system while the system operator seeks to defend several nodes in the cyber layer to minimize the physical damage. Given that CPS attacking and defending is often a continual process, a zero-sum Markov game is proposed in this paper to model these interactions subject to underlying uncertainties of real-world events and actions. A novel model is also proposed in this paper to characterize the interdependence between the cyber layer and the physical layer in a CPS and quantify the impact of the cyber attack on the physical damage in the proposed game. To find the Nash equilibrium of the Markov game, we design an efficient algorithm based on value iteration. The proposed general approach is then applied to study the wide-area monitoring and protection issue in smart grid. Extensive simulations are conducted based on real-world data, and results show the effectiveness of the defending strategies derived from the proposed approach.

Reliable operation of power systems is a primary challenge for the system operators. With the advancement in technology and grid automation, power systems are becoming more vulnerable to cyber-attacks. The main goal of adversaries is to take advantage of these vulnerabilities and destabilize the system. This paper describes a game-theoretic approach to attacker / defender modeling in power systems. In our models, the attacker can strategically identify the subset of substations that maximize damage when compromised. However, the defender can identify the critical subset of substations to protect in order to minimize the damage when an attacker launches a cyber-attack. The algorithms for these models are applied to the standard IEEE-14, 39, and 57 bus examples to identify the critical set of substations given an attacker and a defender budget.

In this paper, we evaluate the usefulness of metrics that assess susceptibility to cascading blackouts. The metrics are computed using a matrix of Line Outage Distribution Factors (LODF, or DFAX matrix). The metrics are compared for several base cases with different load levels of the Western Interconnection (WI). A case corresponding to the September 8, 2011 pre-blackout state is used to compute these metrics and relate them to the origin of the cascading blackout. The correlation between the proposed metrics is determined to check redundancy. The analysis is also used to find vulnerable and critical hot spots in the power system.

A smart grid is a fully automated power electricity network, which operates, protects and controls all its physical environments of power electricity infrastructure being able to supply energy in an efficient and reliable way. As the importance of cyber-physical system (CPS) security is growing, various vulnerability analysis methodologies for general systems have been suggested, whereas there has been few practical research targeting the smart grid infrastructure. In this paper, we highlight the significance of security vulnerability analysis in the smart grid environment. Then we introduce various automated vulnerability analysis techniques from executable files. In our approach, we propose a novel binary-based vulnerability discovery method for AMI and EV charging system to automatically extract security-related features from the embedded software. Finally, we present the test result of vulnerability discovery applied for AMI and EV charging system in Korean smart grid environment.

This paper considers a framework of electrical cyber-physical systems (ECPSs) in which each bus and branch in a power grid is equipped with a controller and a sensor. By means of measuring the damages of cyber attacks in terms of cutting off transmission lines, three solution approaches are proposed to assess and deal with the damages caused by faults or cyber attacks. Splitting incident is treated as a special situation in cascading failure propagation. A new simulation platform is built for simulating the protection procedure of ECPSs under faults. The vulnerability of ECPSs under faults is analyzed by experimental results based on IEEE 39-bus system.

The previous consideration of power grid focuses on the power system itself, however, the recent work is aiming at both power grid and communication network, this coupling networks are firstly called as interdependent networks. Prior study on modeling interdependent networks always extracts main features from real networks, the model of network A and network B are completely symmetrical, both degree distribution in intranetwork and support pattern in inter-network, but in reality this circumstance is hard to attain. In this paper, we deliberately set both networks with same topology in order to specialized research the support pattern between networks. In terms of initial failure from power grid or communication network, we find the remaining survival fraction is greatly disparate, and the failure initially from power grid is more harmful than failure initially from communication network, which all show the vulnerability of interdependency and meantime guide us to pay more attention to the protection measures for power grid.

Reliable operation of electrical power systems in the presence of multiple critical N - k contingencies is an important challenge for the system operators. Identifying all the possible N - k critical contingencies to design effective mitigation strategies is computationally infeasible due to the combinatorial explosion of the search space. This paper describes two heuristic algorithms based on the iterative pruning of the candidate contingency set to effectively and efficiently identify all the critical N - k contingencies resulting in system failure. These algorithms are applied to the standard IEEE-14 bus system, IEEE-39 bus system, and IEEE-57 bus system to identify multiple critical N - k contingencies. The algorithms are able to capture all the possible critical N - k contingencies (where 1 ≤ k ≤ 9) without missing any dangerous contingency.

With the increasing scale of the network, the power information system has many characteristics, such as large number of nodes, complicated structure, diverse network protocols and abundant data, which make the network intrusion detection system difficult to detect real alarms. The current security technologies cannot meet the actual power system network security operation and protection requirements. Based on the attacker ability, the vulnerability information and the existing security protection configuration, we construct the attack sub-graphs by using the parallel distributed computing method and combine them into the whole network attack graph. The vulnerability exploit degree, attacker knowledge, attack proficiency, attacker willingness and the confidence level of the attack evidence are used to construct the security evaluation index system of the power information network system to calculate the attack probability value of each node of the attack graph. According to the probability of occurrence of each node attack, the pre-order attack path will be formed and then the most likely attack path and attack targets will be got to achieve the identification of attack intent.

The IEC 61850 protocol suite for electrical sub-station automation enables substation configuration and design for protection, communication, and control. These power system applications can be formally verified through use of object models, common data classes, and message classes. The IEC 61850-7-420 DER (Distributed Energy Resource) extension further defines object classes for assets such as types of DER (e.g., energy storage, photovoltaic), DER unit controllers, and other DER-associated devices (e.g., inverter). These object classes describe asset-specific attributes such as state of charge, capacity limits, and ramp rate. Attributes can be fixed (rated capacity of the device) dynamic (state of charge), or binary (on or off, dispatched or off-line, operational or fault state). We sketch out a proposed ontology based on the 61850 and 61850-7-420 DER object classes to model threats against a micro-grid, which is an electrical system consisting of controllable loads and distributed generation that can function autonomously (in island mode) or connected to a larger utility grid. We consider threats against the measurements on which the control loop is based, as well as attacks against the control directives and the communication infrastructure. We use this ontology to build a threat model using the ADversary View Security Evaluation (ADVISE) framework, which enables identification of attack paths based on adversary objectives (for example, destabilize the entire micro-grid by reconnecting to the utility without synchronization) and helps identify defender strategies. Furthermore, the ADVISE method provides quantitative security metrics that can help inform trade-off decisions made by system architects and controls.

Cascading failure is an intrinsic threat of power grid to cause enormous cost of society, and it is very challenging to be analyzed. The risk of cascading failure depends both on its probability and the severity of consequence. It is impossible to analyze all of the intrinsic attacks, only the critical and high probability initial events should be found to estimate the risk of cascading failure efficiently. To recognize the critical and high probability events, a cascading failure analysis model for power transmission grid is established based on complex network theory (CNT) in this paper. The risk coefficient of transmission line considering the betweenness, load rate and changeable outage probability is proposed to determine the initial events of power grid. The development tendency of cascading failure is determined by the network topology, the power flow and boundary conditions. The indicators of expected percentage of load loss and line cut are used to estimate the risk of cascading failure caused by the given initial malfunction of power grid. Simulation results from the IEEE RTS-79 test system show that the risk of cascading failure has close relations with the risk coefficient of transmission lines. The value of risk coefficient could be useful to make vulnerability assessment and to design specific action to reduce the topological weakness and the risk of cascading failure of power grid.

Information and communication technologies have augmented interoperability and rapidly advanced varying industries, with vast complex interconnected networks being formed in areas such as safety-critical systems, which can be further categorised as critical infrastructures. What also must be considered is the paradigm of the Internet of Things which is rapidly gaining prevalence within the field of wireless communications, being incorporated into areas such as e-health and automation for industrial manufacturing. As critical infrastructures and the Internet of Things begin to integrate into much wider networks, their reliance upon communication assets by third parties to ensure collaboration and control of their systems will significantly increase, along with system complexity and the requirement for improved security metrics. We present a critical analysis of the risk assessment methods developed for generating attack graphs. The failings of these existing schemas include the inability to accurately identify the relationships and interdependencies between the risks and the reduction of attack graph size and generation complexity. Many existing methods also fail due to the heavy reliance upon the input, identification of vulnerabilities, and analysis of results by human intervention. Conveying our work, we outline our approach to modelling interdependencies within large heterogeneous collaborative infrastructures, proposing a distributed schema which utilises network modelling and attack graph generation methods, to provide a means for vulnerabilities, exploits and conditions to be represented within a unified model.

The power system forms the backbone of a modern society, and its security is of paramount importance to nation's economy. However, the power system is vulnerable to intelligent attacks by attackers who have enough knowledge of how the power system is operated, monitored and controlled. This paper proposes a game theoretic approach to explore and evaluate strategies for the defender to protect the power systems against such intelligent attacks. First, a risk assessment is presented to quantify the physical impacts inflicted by attacks. Based upon the results of the risk assessment, this paper represents the interactions between the attacker and the defender by extending the current zero-sum game model to more generalized game models for diverse assumptions concerning the attacker's motivation. The attacker and defender's equilibrium strategies are attained by solving these game models. In addition, a numerical illustration is demonstrated to warrant the theoretical outcomes.

Wide area monitoring, protection and control for power network systems are one of the fundamental components of the smart grid concept. Synchronized measurement technology such as the Phasor Measurement Units (PMUs) will play a major role in implementing these components and they have the potential to provide reliable and secure full system observability. The problem of Optimal Placement of PMUs (OPP) consists of locating a minimal set of power buses where the PMUs must be placed in order to provide full system observability. In this paper a novel solution to the OPP problem using a Memetic Algorithm (MA) is proposed. The implemented MA combines the global optimization power of genetic algorithms with local solution tuning using the hill-climbing method. The performance of the proposed approach was demonstrated on IEEE benchmark power networks as well as on a segment of the Idaho region power network. It was shown that the proposed solution using a MA features significantly faster convergence rate towards the optimum solution.
 

In smart grid, critical data like monitoring data, usage data, state estimation, billing data etc are regularly being talked among its elements. So, security of such a system, if violated, results in massive losses and damages. By compromising with security aspect of such a system is as good as committing suicide. Thus in this paper, we have proposed security mechanism in Advanced Metering Infrastructure of smart grid, formed as Mesh-Zigbee topology. This security mechanism involves PKI based Digital certificate Authentication and Intrusion detection system to protect the AMI from internal and external security attack.

Smart grids, where cyber infrastructure is used to make power distribution more dependable and efficient, are prime examples of modern infrastructure systems. The cyber infrastructure provides monitoring and decision support intended to increase the dependability and efficiency of the system. This comes at the cost of vulnerability to accidental failures and malicious attacks, due to the greater extent of virtual and physical interconnection. Any failure can propagate more quickly and extensively, and as such, the net result could be lowered reliability. In this paper, we describe metrics for assessment of two phases of smart grid operation: the duration before a failure occurs, and the recovery phase after an inevitable failure. The former is characterized by reliability, which we determine based on information about cascading failures. The latter is quantified using resilience, which can in turn facilitate comparison of recovery strategies. We illustrate the application of these metrics to a smart grid based on the IEEE 9-bus test system.

This paper applies a con-resistant trust mechanism to improve the performance of a communications-based special protection system to enhance its effectiveness and resiliency. Smart grids incorporate modern information technologies to increase reliability and efficiency through better situational awareness. However, with the benefits of this new technology come the added risks associated with threats and vulnerabilities to the technology and to the critical infrastructure it supports. The research in this paper uses con-resistant trust to quickly identify malicious or malfunctioning (untrustworthy) protection system nodes to mitigate instabilities. The con-resistant trust mechanism allows protection system nodes to make trust assessments based on the node's cooperative and defective behaviors. These behaviors are observed via frequency readings which are prediodically reported. The trust architecture is tested in experiments by comparing a simulated special protection system with a con-resistant trust mechanism to one without the mechanism via an analysis of the variance statistical model. Simulation results show promise for the proposed con-resistant trust mechanism.