Cascading Failures Analysis Considering Extreme Virus Propagation of Cyber-Physical Systems in Smart Grids

Communication networks as smart infrastructure systems play an important role in smart girds to monitor, control, and manage the operation of electrical networks. However, due to the interdependencies between communication networks and electrical networks, once communication networks fail (or are attacked), the faults can be easily propagated to electrical networks which even lead to cascading blackout; therefore it is crucial to investigate the impacts of failures of communication networks on the operation of electrical networks. This paper focuses on cascading failures in interdependent systems from the perspective of cyber-physical security. In the interdependent fault propagation model, the complex network-based virus propagation model is used to describe virus infection in the scale-free and small-world topologically structured communication networks. Meanwhile, in the electrical network, dynamic power flow is employed to reproduce the behaviors of the electrical networks after a fault. In addition, two time windows, i.e., the virus infection cycle and the tripping time of overloaded branches, are considered to analyze the fault characteristics of both electrical branches and communication nodes along time under virus propagation. The proposed model is applied to the IEEE 118-bus system and the French grid coupled with different communication network structures. The results show that the scale-free communication network is more vulnerable to virus propagation in smart cyber-physical grids

Multi-Agent Systems and Complex Networks: Review and Applications in Systems Engineering

Systems engineering is an ubiquitous discipline of Engineering overlapping industrial, chemical, mechanical, manufacturing, control, software, electrical, and civil engineering. It provides tools for dealing with the complexity and dynamics related to the optimisation of physical, natural, and virtual systems management. This paper presents a review of how multi-agent systems and complex networks theory are brought together to address systems engineering and management problems. The review also encompasses current and future research directions both for theoretical fundamentals and applications in the industry. This is made by considering trends such as mesoscale, multiscale, and multilayer networks along with the state-of-art analysis on network dynamics and intelligent networks. Critical and smart infrastructure, manufacturing processes, and supply chain networks are instances of research topics for which this literature review is highly relevant

Modelling of the Electric Vehicle Charging Infrastructure as Cyber Physical Power Systems: A Review on Components, Standards, Vulnerabilities and Attacks

The increasing number of electric vehicles (EVs) has led to the growing need to establish EV charging infrastructures (EVCIs) with fast charging capabilities to reduce congestion at the EV charging stations (EVCS) and also provide alternative solutions for EV owners without residential charging facilities. The EV charging stations are broadly classified based on i) where the charging equipment is located - on-board and off-board charging stations, and ii) the type of current and power levels - AC and DC charging stations. The DC charging stations are further classified into fast and extreme fast charging stations. This article focuses mainly on several components that model the EVCI as a cyberphysical system (CPS)

Data-driven cyber attack detection and mitigation for decentralized wide-area protection and control in smart grids

Modern power systems have already evolved into complicated cyber physical systems (CPS), often referred to as smart grids, due to the continuous expansion of the electrical infrastructure, the augmentation of the number of heterogeneous system components and players, and the consequential application of a diversity of information and telecommunication technologies to facilitate the Wide Area Monitoring, Protection and Control (WAMPAC) of the day-to-day power system operation. Because of the reliance on cyber technologies, WAMPAC, among other critical functions, is prone to various malicious cyber attacks. Successful cyber attacks, especially those sabotage the operation of Bulk Electric System (BES), can cause great financial losses and social panics. Application of conventional IT security solutions is indispensable, but it often turns out to be insufficient to mitigate sophisticated attacks that deploy zero-day vulnerabilities or social engineering tactics. To further improve the resilience of the operation of smart grids when facing cyber attacks, it is desirable to make the WAMPAC functions per se capable of detecting various anomalies automatically, carrying out adaptive activity adjustments in time and thus staying unimpaired even under attack. Most of the existing research efforts attempt to achieve this by adding novel functional modules, such as model-based anomaly detectors, to the legacy centralized WAMPAC functions. In contrast, this dissertation investigates the application of data-driven algorithms in cyber attack detection and mitigation within a decentralized architecture aiming at improving the situational awareness and self-adaptiveness of WAMPAC. First part of the research focuses on the decentralization of System Integrity Protection Scheme (SIPS) with Multi-Agent System (MAS), within which the data-driven anomaly detection and optimal adaptive load shedding are further explored. An algorithm named as Support Vector Machine embedded Layered Decision Tree (SVMLDT) is proposed for the anomaly detection, which provides satisfactory detection accuracy as well as decision-making interpretability. The adaptive load shedding is carried out by every agent individually with dynamic programming. The load shedding relies on the load profile propagation among peer agents and the attack adaptiveness is accomplished by maintaining the historical mean of load shedding proportion. Load shedding only takes place after the consensus pertaining to the anomaly detection is achieved among all interconnected agents and it serves the purpose of mitigating certain cyber attacks. The attack resilience of the decentralized SIPS is evaluated using IEEE 39 bus model. It is shown that, unlike the traditional centralized SIPS, the proposed solution is able to carry out the remedial actions under most Denial of Service (DoS) attacks. The second part investigates the clustering based anomalous behavior detection and peer-assisted mitigation for power system generation control. To reduce the dimensionality of the data, three metrics are designed to interpret the behavior conformity of generator within the same balancing area. Semi-supervised K-means clustering and a density sensitive clustering algorithm based on Hieararchical DBSCAN (HDBSCAN) are both applied in clustering in the 3D feature space. Aiming to mitigate the cyber attacks targeting the generation control commands, a peer-assisted strategy is proposed. When the control commands from control center is detected as anomalous, i.e. either missing or the payload of which have been manipulated, the generating unit utilizes the peer data to infer and estimate a new generation adjustment value as replacement. Linear regression is utilized to obtain the relation of control values received by different generating units, Moving Target Defense (MTD) is adopted during the peer selection and 1-dimensional clustering is performed with the inferred control values, which are followed by the final control value estimation. The mitigation strategy proposed requires that generating units can communicate with each other in a peer-to-peer manner. Evaluation results suggest the efficacy of the proposed solution in counteracting data availability and data integrity attacks targeting the generation controls. However, the strategy stays effective only if less than half of the generating units are compromised and it is not able to mitigate cyber attacks targeting the measurements involved in the generation control

Cyber- Physical Robustness Enhancement Strategies for Demand Side Energy Systems

An integrated Cyber-Physical System (CPS) system realizes the two-way communication between end-users and power generation in which customers are able to actively re-shaped their consumption profiles to facilitate the energy efficiency of the grid. However, large-scale implementations of distributed assets and advanced communication infrastructures also increase the risks of grid operation. This thesis aims to enhance the robustness of the entire demand-side system in a cyber-physical environment and develop comprehensive strategies about outage energy management (i.e., community-level scheduling and appliance-level energy management), communications infrastructure development, and cybersecurity controls that encounter virus attacks. All these aspects facilitate the demand-side system’s self-serve capability and operational robustness under extreme conditions and dangerous scenarios. The research that contributes to this thesis is grouped around and builds a general scheme to enhance the robustness of CPS demand-side energy system with outage considerations, communication network layouts, and virus intrusions. Under system outage, there are two layers for maximizing the duration of self-power supply duration in extreme conditions. The study first proposed a resilient energy management system for residential communities (CEMS), by scheduling and coordinating the battery energy storage system and energy consumption of houses/units. Moreover, it also proposed a hierarchical resilient energy management system (EMS) by fully considering the appliance-level local scheduling. The method also takes into account customer satisfaction and lifestyle preferences in order to form the optimal outcome. To further enhance the robustness of the CPS system, a complex multi-hop wireless remote metering network model for communication layout on the CPS demand side was proposed. This decreased the number and locations of data centers on the demand side and reduced the security risk of communication and the infrastructure cost of the smart grid for residential energy management. A novel evolutionary aggregation algorithm (EAA) was proposed to obtain the minimum number and locations of the local data centers required to fulfill the connectivity of the smart meters. Finally, the potential for virus attacks has also been studied as well. A trade-off strategy to confront viruses in the system with numerous network nodes is proposed. The allocation of antivirus programs and schemes are studied to avoid system crashes and achieve the minimum potential damages. A DOWNHILL-TRADE OFF algorithm is proposed to address an appropriate allocation strategy under the time evolution of the expected state of the network. Simulations are conducted using the data from the Smart Grid, Smart City national demonstration project trials

Vulnérabilité, interdépendance et analyse des risques des postes sources et des modes d’exploitation décentralisés des réseaux électriques

In view of the increasing use of Information and Communication Technol-ogies in power systems, it is essential to study the interdependencies between these coupled heterogeneous systems. This thesis focuses on the modeling of multi- infrastructure systems. This includes interdependencies and the three major failures families: common mode, escalat-ing and cascading. It is indeed necessary to identify the weaknesses that can trigger one or multiple failure(s) and cascade through these interdependent infrastructures, causing unex-pected and increasingly more serious failures to other infrastructures. In this context, different approaches, based on the theory of Complex Networks, are developed to identify the most critical components in the coupled heterogeneous system. One of the major scientific barriers addressed in this thesis is the development of a unified mathematical model to represent the behavior.Au vu de l’utilisation croissante des technologies de l’information et de la communication dans les réseaux électriques, il est indispensable d’étudier l’étroite liaison entre ces infrastructures et d’avoir une vision intégrée du système couplé. Cette thèse porte ainsi sur la modélisation des systèmes multi-infrastructures. Cela inclut les interdépendances et les trajectoires de défaillances de type modes communs, aggravations et cascades. Il est en effet nécessaire d’identifier les points de faiblesse qui peuvent déclencher une ou de multiples défaillance(s), se succéder en cascade au travers de ces infrastructures liées et ainsi entrainer des défaillances inattendues et de plus en plus graves dans des autres infrastructures. Dans cette optique, différents modèles basés sur la théorie des Réseaux Complexes sont développés afin d’identifier les composants les plus importantes, et pourtant critiques, dans le système interconnecté. Un des principaux verrous scientifiques levé dans cette thèse est relatif au développement d'un modèle mathématique « unifié » afin de représenter les comportements des multiples infrastructures non-homogènes qui ont des interdépendances asymétriques

Critical Infrastructures: Enhancing Preparedness & Resilience for the Security of Citizens and Services Supply Continuity: Proceedings of the 52nd ESReDA Seminar Hosted by the Lithuanian Energy Institute & Vytautas Magnus University

Critical Infrastructures Preparedness and Resilience is a major societal security issue in modern society. Critical Infrastructures (CIs) provide vital services to modern societies. Some CIs’ disruptions may endanger the security of the citizen, the safety of the strategic assets and even the governance continuity. The European Safety, Reliability and Data Association (ESReDA) as one of the most active EU networks in the field has initiated a project group on the “Critical Infrastructure/Modelling, Simulation and Analysis – Data”. The main focus of the project group is to report on the state of progress in MS&A of the CIs preparedness & resilience with a specific focus on the corresponding data availability and relevance. In order to report on the most recent developments in the field of the CIs preparedness & resilience MS&A and the availability of the relevant data, ESReDA held its 52nd Seminar on the following thematic: “Critical Infrastructures: Enhancing Preparedness & Resilience for the security of citizens and services supply continuity”. The 52nd ESReDA Seminar was a very successful event, which attracted about 50 participants from industry, authorities, operators, research centres, academia and consultancy companies.JRC.G.10-Knowledge for Nuclear Security and Safet