Mitigating cyber supply chain risks in cyber physical systems organizational landscape

Cyber supply chain (CSC) provide an organization with the ability to align its business processes, information flows and data structures with other organization. However, the increase interdependencies have brought about inherent, threats, risks, attacks and vulnerabilities that adversaries maybe able to exploit when not properly mitigated. Additionally, every cyberattack on each organization increases the probability of the risk cascading to others. The CSC risk has increased exponentially due to uncertainties surrounding cyberattacks and the cyber threat landscape. Recent CSC threats have been disruptive and impacting on the smooth flow of delivery of products and services. CSC risk has been observed as one of the areas that impact greatly and causes budget overruns. The aim of this paper is to mitigate CSC risks in an organizational landscape. In particular, the paper identifies supply inbound and outbound chain threat landscape using a risk breakdown structure. Further, weassess the risk to gather cyber threat intelligence. Furthermore, we use the probability distribution method to determine the CSC risks and analyze the risk probabilities and likelihood of risk cascading impact. Our results show that CSC risk can be neutralized using probability distribution methods to detect and mitigate the risks and their impact levels

An Integrated Cyber Security Risk Management Approach for a Cyber-Physical System

A cyber-physical system (CPS) is a combination of physical system components with cyber capabilities that have a very tight interconnectivity. CPS is a widely used technology in many applications, including electric power systems, communications, and transportation, and healthcare systems. These are critical national infrastructures. Cybersecurity attack is one of the major threats for a CPS because of many reasons, including complexity and interdependencies among various system components, integration of communication, computing, and control technology. Cybersecurity attacks may lead to various risks affecting the critical infrastructure business continuity, including degradation of production and performance, unavailability of critical services, and violation of the regulation. Managing cybersecurity risks is very important to protect CPS. However, risk management is challenging due to the inherent complex and evolving nature of the CPS system and recent attack trends. This paper presents an integrated cybersecurity risk management framework to assess and manage the risks in a proactive manner. Our work follows the existing risk management practice and standard and considers risks from the stakeholder model, cyber, and physical system components along with their dependencies. The approach enables identification of critical CPS assets and assesses the impact of vulnerabilities that affect the assets. It also presents a cybersecurity attack scenario that incorporates a cascading effect of threats and vulnerabilities to the assets. The attack model helps to determine the appropriate risk levels and their corresponding mitigation process. We present a power grid system to illustrate the applicability of our work. The result suggests that risk in a CPS of a critical infrastructure depends mainly on cyber-physical attack scenarios and the context of the organization. The involved risks in the studied context are both from the technical and nontechnical aspects of the CPS

Security risks in cyber physical systems—A systematic mapping study

The increased need for constant connectivity and complete automation of existing systems fuels the popularity of Cyber Physical Systems (CPS) worldwide. Increasingly more, these systems are subjected to cyber attacks. In recent years, many major cyber-attack incidents on CPS have been recorded and, in turn, have been raising concerns in their users' minds. Unlike in traditional IT systems, the complex architecture of CPS consisting of embedded systems integrated with the Internet of Things (IoT) requires rather extensive planning, implementation, and monitoring of security requirements. One crucial step to planning, implementing, and monitoring of these requirements in CPS is the integration of the risk management process in the CPS development life cycle. Existing studies do not clearly portray the extent of damage that the unattended security issues in CPS can cause or have caused, in the incidents recorded. An overview of the possible risk management techniques that could be integrated into the development and maintenance of CPS contributing to improving its security level in its actual environment is missing. In this paper, we are set out to highlight the security requirements and issues specific to CPS that are discussed in scientific literature and to identify the state-of-the-art risk management processes adopted to identify, monitor, and control those security issues in CPS. For that, we conducted a systematic mapping study on the data collected from 312 papers published between 2000 and 2020, focused on the security requirements, challenges, and the risk management processes of CPS. Our work aims to form an overview of the security requirements and risks in CPS today and of those published contributions that have been made until now, towards improving the reliability of CPS. The results of this mapping study reveal (i) integrity authentication and confidentiality as the most targeted security attributes in CPS, (ii) model-based techniques as the most used risk identification and assessment and management techniques in CPS, (iii) cyber-security as the most common security risk in CPS, (iv) the notion of “mitigation measures” based on the type of system and the underline internationally recognized standard being the most used risk mitigation technique in CPS, (v) smart grids being the most targeted systems by cyber-attacks and thus being the most explored domain in CPS literature, and (vi) one of the major limitations, according to the selected literature, concerns the use of the fault trees for fault representation, where there is a possibility of runtime system faults not being accounted for. Finally, the mapping study draws implications for practitioners and researchers based on the findings.</p

A Framework for the Performance Analysis and Simulation of RF-Mesh Advanced Metering Infrastructures for Smart Grid Applications

RÉSUMÉ L’Infrastructure de Mesurage Avancée (IMA), conçue à l’origine pour lire à distance des compteurs intelligents, est actuellement considérée comme une composante essentielle dans le domaine des Smart Grid. Le but principal des IMAs est de connecter le grand nombre de compteurs intelligents installés chez les clients au le centre de contrôle de données de l’entreprise d’électricité et viceversa. Cette communication bidirectionnelle est une caractéristique recherchée par un grand nombre d’applications, qui visent à utiliser ces infrastructures comme support à la transmission de leurs données dans le réseau électrique, comme par exemple la gestion de la charge et la demande-réponse. Un grand nombre de technologies et de protocoles de communication sont actuellement utilisés dans les IMAs : parmi les solutions disponibles, le RF-Mesh est une des plus populaires, surtout grâce au bas coût pour l’installation et les équipements. Toutefois, le débit nominal des communications RF-Mesh est très bas, de l’ordre des dizaines de kbps, et la littérature qui traite leur performance est très limitée. Ceci pourrait en limiter l’utilisation pour des applications autres que la lecture à distance des compteurs intelligents. Ce travail de thèse vise à développer un système de modèles et outils pour évaluer la performance des réseaux RF-Mesh et encourager leur utilisation pour un grand nombre d’applications dans le domaine des Smart Grid. Le système d’évaluation de performance proposé est constitué (i) de modèles analytiques, pour calculer la probabilité de collision entre les paquets transmis, (ii) d’un simulateur de réseau, pour recréer le fonctionnement des réseaux RF-Mesh dans un environnement virtuel, (iii) d’un générateur de topologie, pour créer des cas réalistes en se basant sur des données géographiques et (iv) des méthodes pour l’analyse de la performance. Trois différents modèles analytiques ont été implémentés. Dans les deux premiers, une nouvelle formule analytique a été utilisée pour calculer la probabilité de collision entre paquets. La probabilité de collision est ensuite utilisée pour estimer le délai moyen de/vers chaque compteur intelligent dans l’IMA analysée. Par la suite, des indices de performance, basés sur le délai moyen, sont utilisés pour faire des analyses de performance : études de faisabilité pour les applications de Smart Grid, l’identification de noeuds critiques et d’éventuels goulots d’étranglement. Dans le troisième modèle analytique, la théorie de Markov-Modulated System est utilisée pour prendre en considération d’importants détails d’implémentation, comme la probabilité de retransmission et la taille des mémoires tampons des noeuds, qui n’avaient pas été inclus dans la modélisations précédente.----------ABSTRACT Advanced Metering Infrastructure (AMI), originally conceived to replace the old Automated Meter Reading (AMR) infrastructures, have now become a key element in the Smart Grid context and might be used for applications other than remote meter reading. The main driver to their widespread installation is that they provide power utilities with a bidirectional connectivity with the smart meters. A wide variety of communication networks are currently proposed to support the implementation of AMIs, and, among them, the RF-Mesh technology seems to be very popular. The main reasons for its adoption are the proprietary infrastructure and the modest cost for the installation and the equipment. However, RF-Mesh systems are characterized by poor achievable data-rates in the order of 10 kbps, and their performance is not well studied in the literature. The lack of tools and methods for the performance evaluation might be a roadblock to their widespread adoption. This thesis aims at filling this gap and increase the knowledge of large-scale RF-Mesh systems to foster their use for a wide variety of applications. We propose a comprehensive framework for the performance evaluation of large-scale AMIs adopting the RF-Mesh technology. The framework includes (i) a geo-based topology generator that uses geographic data to produce realistic AMI cases, (ii) analytic models for the computation of packet collision probability and delay, (iii) a network simulator to recreate the behavior of large-scale RF-Mesh systems, and (iv) methods to evaluate the performance. Three different analytic models are included in the framework. The first two provide a novel analytic formulation of the packet collision probability in a mesh network with timeslotted ALOHA and the Frequency Hopping Spread Spectrum (FHSS) protocol : the collision probability is then used to estimate the average delay in the network, and to define and evaluate performance indexes (e.g., critical nodes and survival function). In the third model, a complex Markov-Modulated System (MMS) is used to take into consideration important implementation details, such as the retransmission probability and the buffer size, that were not considered in the two previous models. This model also provides a more accurate computation of the packet collision probability. A Poisson distribution is used to represent the traffic coming from potential Smart Grid applications. The framework also includes an RFMesh network simulator, written in Java and Python. The tool provides additional enhanced features with respect to the analytic models, such as a dynamic routing protocol or different traffic distributions

Digital governance in support of infrastructure asset management

Voor besluitvorming op het gebied van strategisch infrastructuurassetbeheer is hoogwaardige, geharmoniseerde assetinformatie uit IT- en controlesystemen noodzakelijk. Er zijn problemen die verband houden met het verzamelen en omzetten van de assetinformatie die nodig is voor besluitvormingsdoeleinden. De basiscasestudy Rand Water is het grootste waterbedrijf in Afrika. De problemen waarnaar hierboven verwezen wordt, komen veel voor bij Rand Water en bij andere infrastructuurassetintensieve organisaties uit verschillende sectoren. Een nieuwe digitale-governanceabenadering is noodzakelijk om assetinformatiebeheer ondernemingsbreed mogelijk te maken; hiermee wordt besluitvorming op het gebied van strategisch infrastructuurassetbeheer ondersteund. Daarnaast moet de nieuwe digitale-governancebenadering op duurzame wijze worden geïmplementeerd. Deze studie maakt gebruik van een onderzoeksfilosofie uit de design science, die wordt uitgevoerd aan de hand van een inductief-hypothetische onderzoeksstrategie. De onderzoeker is een reflective practitioner. Het unieke artefact van het onderzoek is de Rand Water Way. Het onderzoek biedt een uitgebalanceerde digitale-governancebenadering die op passende wijze de relevante risico’s beperkt; het gaat om een geïntegreerde, ondernemingsbrede, op risico’s gebaseerde benadering. Daarnaast biedt het onderzoek een benadering om de nieuwe manier van digitale governance succesvol te implementeren bij infrastructuurassetintensieve organisaties. De Rand Water Way werd geïnstantieerd, getest en geaccepteerd door Rand Water, en is ook getest en geaccepteerd door vergelijkbare organisaties uit verschillende sectoren. Het onderzoek draagt bij aan de theorie- en kennisvermeerdering over hoe digitale technologie en assetinformatie moeten worden beheerd om infrastructuurassetbeheer te ondersteunen, alsook over hoe deze nieuwe digitale-governancebenadering moet worden geïmplementeerd in grote, complexe infrastructuurassetintensieve organisaties