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In recent decades, Industrial Control Systems (ICS) have been affected by heterogeneous cyberattacks that have a huge impact on the physical world and the people's safety. Nowadays, the techniques achieving the best performance in the detection of cyber anomalies are based on Machine Learning and, more recently, Deep Learning. Due to the incipient stage of cybersecurity research in ICS, the availability of datasets enabling the evaluation of anomaly detection techniques is insufficient. In this paper, we propose a methodology to generate reliable anomaly detection datasets in ICS that consists of four steps: attacks selection, attacks deployment, traffic capture and features computation. The proposed methodology has been used to generate the Electra Dataset, whose main goal is the evaluation of cybersecurity techniques in an electric traction substation used in the railway industry. Using the Electra dataset, we train several Machine Learning and Deep Learning models to detect anomalies in ICS and the performed experiments show that the models have high precision and, therefore, demonstrate the suitability of our dataset for use in production systems.

Critical infrastructures are interdependent systems that are continuously evolving. Their evolution is, oftentimes, in a way that tightens, or creates new, interdependences. As urban areas continue to develop, the philosophy of officials and policy makers to meet growth in the energy demand tends to prioritize sustainable planning by deferring infrastructural upgrades and relying instead on the smart operation. Relying on information and communication technology (ICT) network is a prerequisite to achieving smart operation. With the anticipated high penetration of distributed energy resources (DERs) and electric vehicles (EVs), increased reliance on real-time monitoring and control is a must for the power grid to handle such unprecedented levels of load/generation uncertainties. This paper sheds light on how the power grid, the ICT network, and the transportation network are interrelated and interdependent. This paper also presents a benchmark problem for this type of research and a case study. Initial results of the case study show that the impact of these rising interdependences may be significant and must be fully understood and taken into consideration.

The growth in the critical infrastructure (CI) complexity, interdependency, and data flows has required enhanced reliability assessment methods. This paper proposes a reliability assessment model which considers various sources affecting the CI performance, including internal and external fault sources including natural disasters and malicious attacks. The paper proposes a hybrid data and model-based approach for a comprehensive CI reliability assessment, which considers fault source effects on CI subsystems and their interdependencies. The Shannon entropy concept is proposed for detecting any variations in the system information fault sources. The graph concept is used to determine interdependencies of CI subsystems. We have presented two case studies to illustrate the effectiveness of the proposed method, and compare the results with similar studies. [ABSTRACT FROM AUTHOR]

Modern society is highly dependent on its critical infrastructures. These infrastructures usually suffer intentional attacks, which is a serious threat to social wellbeing, making the protection of them to be a great challenge for the security agencies. Many game models have been proposed to tackle this problem. However, little of them consider the interrelationship of different targets within the infrastructures. In this paper, the protection of critical infrastructures against a malicious attacker is modeled as a simultaneous game, where the payoffs of the players are evaluated on the basis of the topology structure of the infrastructure system. An efficient algorithm is adopted to obtain the Nash equilibrium solution. The experimental results reveal that in the equilibriums, the defender distributes higher probabilities on protecting the targets who are more important, for example, those with large degrees or betweenness, while the attacker prefers attacking targets with medium degrees or betweenness. The effectiveness of the game-theoretic solution is validated, and the experimental results in a real-world network provide us a clear insight on which targets to protect.

Critical infrastructures (CIs) are essential for the national security, economy, and public safety, whose protection against cyberattacks has become the focus of significant attention. Impact assessment plays an important role in this protection, which provides real-time situations for security managers. The assessment of CIs not only need to analyze the cyberattack's impact on any specific station, but also to consider the spreading process of the negative impact. However, few research in this domain consider the above two aspects simultaneously due to the complexity of CIs and their operation. To tackle this problem, a hierarchical flow model (HFM)-based impact assessment is presented. In this approach, a novel HFM method is proposed to describe a system from a function system perspective, which combines a flow model and hierarchical knowledge. By using this method, a CI model which considers cyber–physical interaction within a station, dependence among stations, and the topological structure of the physical network is established. Next, based on the CI model, an impact assessment is proposed to quantify the loss which is caused by the impact spreading within the CI network. Finally, case studies on a gas supply system are conducted to verify the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

In this paper, we provide a novel framework to assess the vulnerability/robustness of a network with respect to pair-wise nodes’ connectivity. In particular, we consider attackers that aim, at the same time, at dealing the maximum possible damage to the network in terms of the residual connectivity after the attack and at keeping the cost of the attack (e.g., the number of attacked nodes) at a minimum. Differently from the previous literature, we consider the attacker perspective using a multiobjective formulation and, rather than making hypotheses on the mindset of the attacker in terms of a particular tradeoff between the objectives, we consider the entire Pareto front of nondominated solutions. Based on that, we define novel global and local robustness/vulnerability indicators and we show that such indices can be the base for the implementation of effective protection strategies. Specifically, we propose two different problem formulations and we assess their performances. We conclude this paper by analyzing, as case studies, the IEEE118 power network and the U.S. Airline Network as it was in 1997, comparing the proposed approach against centrality measures. [ABSTRACT FROM AUTHOR]

Many infrastructures that shape our lifestyle depend on the GPS. Even though not used for positioning, these infrastructures need GPS to derive a precise time synchronization necessary for their operations. Examples are power distribution grids, gateways for financial transactions, and telecommunication networks. However, GPS receivers, and more in general global navigation satellite system (GNSS) receivers, are vulnerable to interference. This makes GNSS-dependent infrastructures prone to time synchronization errors. This paper addresses the vulnerability of GNSS receivers to the intentional injection of counterfeit signals, an operation known as “spoofing.” The analysis is backed by a campaign of tests conducted on three receivers suitable for applications that use GNSS-based synchronization. A battery of spoofing attacks, targeting the control of the output time reference of these receivers, is purposely simulated with lab instrumentation. The effects of such attacks on the receivers’ measurements are observed and quantified; they prove that the vulnerability of GNSS receivers to malevolent radio attacks is a quantifiable reality, but such attacks “leave traces” that could trigger their detection. The purpose of this paper is to increase awareness, though not alarm, about the risk represented by time spoofing on application domains used to look at GNSS as a commodity. This paper shows that reducing this risk is possible at both receiver and system level. [ABSTRACT FROM AUTHOR]

In previous research a novel methodology to assess structural vulnerability was proposed and applied in IEEE test system and high voltage transmission networks of 94 buses, by using graph theory to investigate various risk scenarios that can trigger cascading failures. In this paper we validate the application of this methodology in larger networks by applying a case study on the transmission network 230 and 400 kV of Mexico. The events of cascading failures are simulated through two elimination strategies: by deliberate attacks on critical nodes or by random errors. Iterations are performed by running successive N-1 contingencies on a network that is constantly changing its structure with the elimination of each node. The power flows are not necessary and only the calculation of the graph statistical parameter ?geodesic vulnerability? is required. This reduces the computation time and leads to a comparative analysis of structural vulnerability. [ABSTRACT FROM PUBLISHER]

Many critical infrastructures are interdependent networks in which the behavior of one network impacts those of the others. Despite the fact that interdependencies are essential for the operation of critical infrastructures, such interdependencies can negatively affect the reliability and fuel the cascade of failures within and across the networks. In this paper, a novel interdependent Markov-chain framework is proposed that enables capturing interdependencies between two critical infrastructures with the ultimate goal of predicting their resilience to cascading failures and characterizing the effects of interdependencies on system reliability. The framework is sufficiently general to model cascading failures in any interdependent networks; however, this paper focuses on the electric-cyber infrastructure as an example. Using this framework it is shown that interdependencies among reliable systems, i.e., systems with exponentially distributed failure sizes, can make the individually reliable systems behave unreliably as a whole with power-law failure-size distributions. [ABSTRACT FROM PUBLISHER]

The smart grid is driving the deployment of networked components within the traditional power grid to achieve greater reliability and control. However, those cyber components are creating new security vulnerabilities that could lead to significant disruptions if exploited maliciously. We propose a comprehensive cost model designed to assist in the selection of responses to malicious attacks on an advanced metering infrastructure. The cost model reflects the costs of response actions due to outages in the distribution grid, disruptions of the electricity market, and violations of contractual agreements among stakeholders. We also present a realistic implementation of the cost model using ArcGIS for topology generation and GridLAB-D for grid simulation. The cost model is a step forward toward achievement of automated resilience in the smart grid. It also provides comprehensive modeling for system dynamics and operation costs, while relieving utilities from the burden of manually assigning costs for response actions and modeling attacker steps. [ABSTRACT FROM PUBLISHER]

This paper introduces a novel control scheme for mitigating the cascading effects of a failure in the power transmission grid. Modern power systems include controller entities, which exchange information (measurement/control signals) with the grid through information communication technology (ICT). Nevertheless, networking problems can generate observability/reachability issues, which prevent the controller from correctly estimating the grid's state and applying in a timely manner the necessary actions. Thus, we present a control approach that explicitly takes into account the potential degradation of the ICT performance during power failure events. To this end, the power-induced ICT deficiencies are modeled as additive communication latency, to quantify their impact on the controller's effectiveness. Moreover, in order to overcome excessive/varying delays, a model predictive control architecture is proposed, which produces directives for both the safeguard cut of power lines and the load/generation regulation, in a manner that minimizes the impact of the initial power failure on the overall grid. [ABSTRACT FROM PUBLISHER]

Critical infrastructure (CI) modeling and analysis is a very challenging research topic. One of the most pressing issues is to find an effective representation for addressing the system vulnerabilities caused by interdependencies, which, if exploited, could result in nontrivial accident scenarios. Until now, this question has been tackled for different sector-specific infrastructures (electricity grid, telecommunications networks, supply chains, etc.), and very few generalizable analysis tools have been developed. However, all CI share some features that can be leveraged in order to build a common modeling framework. This paper identifies these common features, which it exploits to develop a modeling language: the infrastructure resilience-oriented modeling language (I $ \circledR $ ML). I $ \circledR $ ML is designed to facilitate the analysis of operational interdependencies among the infrastructure components and overall resilience, i.e., the ability of the infrastructure to withstand and recover under off-nominal (anomalous) conditions. A number of examples are used to illustrate the modeling concepts and highlight the analytical capability of I $ \circledR $ ML. [ABSTRACT FROM AUTHOR]

Critical control systems manage many of today's critical infrastructures, whose continuous operation, maintenance, and protection are high national priorities for governments around the world. The authors present the fundamental architectural components of these systems, identify vulnerabilities and potential threats, and describe protection solutions that can be deployed to mitigate attacks. [ABSTRACT FROM PUBLISHER]

This paper presents a novel approach to the CI interdependencies analysis, based on the DBN formalism. An original modeling procedure is illustrated, which divides the DBN in three distinct levels: an atomic events level, a propagation level, and a services level. The first level models the adverse events that may impact on the analyzed CIs, the second one properly captures interdependencies among CIs' services and devices, and the last one allows to monitor the state of provided services. The resulting DBN permits to perform three kinds of analysis: a reliability study, which allows to find structural weaknesses of interconnected CIs, an adverse events propagation study, which highlights the role interdependency plays in the propagation of adverse events, and a failure prediction analysis, that can serve as an useful guide to the fault localization process (failures may have many different explanations due to interdependency). A specific case study provided by Israel Electric Corporation is considered, and explicative simulations are presented and discussed in detail. [ABSTRACT FROM PUBLISHER]

Infrastructure interdependency stems from the functional and logical relations among individual components in different distributed systems. To characterize the extent to which a contingency affecting an infrastructure is going to weaken, and possibly disrupt, the safe operation of an interconnected system, it is necessary to model the relations established through the connections linking the multiple components of the involved infrastructures. In this work, the modeling of interdependencies among network systems and of their effects on failure propagation is carried out within the simulation framework of a failure cascade process. The sensitivity of the critical loading value (the lower bound of the cascading failure region) and of the average cascade size with respect to the coupling parameters defining the interdependency strength is investigated as a means to arrive at the definition and prescription of cascade-safe operating margins. [ABSTRACT FROM AUTHOR]

Critical infrastructures such as the power grid are essentially physical processes controlled by computers connected by networks. They're usually as vulnerable as any other interconnected computer system, but their failure has a high socioeconomic impact. The Critical Utility Infrastructural Resilience (Crutial) project designed an information switch (CIS) to protect these infrastructures. These devices help ensure that incoming and outgoing traffic satisfies the security policy of an infrastructure in face of cyberattacks. A CIS isn't a firewall, but a distributed protection device based on a sophisticated access control model. Furthermore, a CIS is intrusion-tolerant and self-healing, seeking perpetual unattended correct operation. [ABSTRACT FROM PUBLISHER]

Wide area measurements have been widely used in the energy management systems (EMS) of power systems for monitoring, operation, and control. In recent years, the advent of synchronized phasor measurements has added another dimension to the field of wide-area measurements. At the same time, the field of protection systems has been dominated by computer based relays, which make it relatively easy to communicate with relays and thus include them in many innovative protection systems. Special Protection Systems (SPS) or Remedial Action Schemes (RAS) are one example of integration of communication and protection systems. In recent years-due to operational demands imposed on transmission networks by deregulation it has become clearer that wide-area measurements and their integration in protection and control systems is a necessity. This paper documents the state-of-the-art in modem sensor, communication, and protection technologies which show great potential for innovations in protection and control systems for the future. [ABSTRACT FROM AUTHOR]

This paper provides a comprehensive state-of-the-art overview on power infrastructure defense systems. A review of the literature on the subjects of critical infrastructures, threats to the power grids, defense system concepts, and the special protection systems is reported. The proposed Strategic Power Infrastructure Defense (SPID) system methodology is a real-time, wide-area, adaptive protection and control system involving the power, communication, and computer infrastructures. The SPID system performs the failure analysis, vulnerability assessment, and adaptive control actions to avoid catastrophic power outages, This paper also includes a new concept for bargaining by multiagents to identify the decision options to reduce the system vulnerability. The concept of a flexible configuration of the wide-area grid is substantiated with an area-partitioning algorithm. A 179-bus system is used to illustrate the area partitioning method that is. intended to minimize the total amount of load shedding. [ABSTRACT FROM AUTHOR]

Because critical infrastructures touch us all, the growing potential for infrastructure problems stems from multiple sources, including system complexity, economic growth, deregulation, terrorism, and even the weather. Electric power systems constitute the fundamental infrastructure of modern society. A successful terrorist attempt to disrupt electricity supplies could have devastating effects on national security, the economy, and every citizen's life. Yet power systems have widely dispersed assets that can never be absolutely defended against a determined attack. Indeed, because of the intimate connections between power systems and society's other infrastructures, we need to consider three different kinds of threats: attacks upon the power system; attacks by the power system; and attacks through the power system [ABSTRACT FROM PUBLISHER]