Roberta Terruggia

Unavailability of critical SCADA communication links interconnecting a power grid and a Telco network

The availability of power supply to power grid customers depends upon the availability of services of supervision, control and data acquisition (SCADA) system, which constitutes the nervous system of a power grid. In turn, SCADA services depend on the availability of the interconnected networks supporting such services. We propose a service oriented stochastic modelling methodology to investigate the availability of large interconnected networks, based on the hierarchical application of different modelling formalisms to different parts of the networks. Interconnected networks are decomposed according to the specific services delivered until the failure and repair mechanisms of the decomposed elementary blocks can be identified. We represent each network by a convenient stochastic modelling formalism, able to capture the main technological issues and to cope with realistic assumptions about failure and recovery mechanisms. This procedure confines the application of the more intensive computational techniques to those subsystems that actually require it. The paper concentrates on an actual failure scenario, occurred in Rome in January 2004 that involved the outage of critical SCADA communication links, interconnecting a power grid and a Telco network.

Risk analysis via heterogeneous models of SCADA interconnecting Power Grids and Telco networks

The automation of Power Grids by means of Supervisory Control and Data Acquisition (SCADA) systems has led to an improvement of Power Grid operations and functionalities but also to pervasive cyber interde-pendencies between Power Grids and Telecommunication Networks. Many power grid services are increasingly depending upon the adequate functionality of SCADA system which in turn strictly depends on the adequate functionality of its Communication infrastructure. We propose to tackle the SCADA risk analysis by means of different and heterogeneous modeling techniques and software tools. We demonstrate the applicability of our approach through a case study on an actual SCADA system for an electrical power distribution grid. The modeling techniques we discuss aim at providing a probabilistic dependability analysis, followed by a worst case analysis in presence of malicious attacks and a real-time performance evaluation.

A tool for network reliability analysis

A network is a structure where any couple of nodes is normally connected by different independent paths, thus making the structure intrinsically reliable. For this reason, many natural, social and technological systems organize in the form of networks. A tool for network reliability analysis, where different approaches are tested and compared, is in progress. The paper presents some preliminary results of a scalable benchmark, that includes different network structures.

Reliability and quality of service in weighted probabilistic networks using Algebraic Decision Diagrams

In network reliability studies, nodes and links are usually represented as binary entities (either up or down). In many cases the analysis of the performance of the system requires a richer representation by associating to each arc a weight representing a specific attribute of the arc (e.g. capacity, resistance, cost, length). For example, the amount of traffic characterizing the connections in communication or transport systems or the distance between nodes in a highway network are fundamental for a full description of these networks. The paper explores the problem of the quantitative evaluation of reward functions in stochastic weighted networks, where the weights assigned to the arcs my have different physical interpretations. We discuss two types of interpretation of weights: weights as distances and weights as capacities. Correspondingly, two different algorithms based on a data structure called Algebraic Decision Diagram (ADD), are discussed and presented. The first evaluates the probability that the terminal node can be reached from the source within a determinate distance or cost. The second computes the probability that a flow greater than a threshold can be transmitted between the source and the sink. The algorithms have been tested with several examples and with some benchmark network taken from the literature.

Reliability analysis of multi-source multi-sink critical interacting systems

Traditional reliability studies on probabilistic networks are devoted to evaluate the probability that two nodes or K nodes are connected, assuming that nodes are undifferentiated. In flow networks, however, we need to distinguish between source nodes where the flow is generated and sink nodes where the flow is utilized. Sink nodes may usually be fed by many sources. To this end, we have extended the traditional studies to include multi-source multi-sink networks. A case study is analysed consisting in a portion of an electrical grid controlled by a its SCADA system through a public telecommunication network.

BINARY DECISION DIAGRAMS IN NETWORK RELIABILITY ANALYSIS

Abstract Many social, economical and technological structures can be abstracted in the form of networks where the vertices are the entities of the system and the edges the physical or relational links among them. One relevant property of networks that make them a preferential structure both in natural and technological systems is that the connection between any two nodes of the networks can be achieved through many redundant paths, thus making the connection intrinsically reliable. Network reliability is studied in this paper by resorting to different approaches making use of the BDD representation of Boolean functions. The related algorithms are presented and their merits and limits are briefly discussed.

Quantitative evaluation of attack/defense scenarios through Decision Network modelling and analysis

We exploit Decision Networks (DN) for the analysis of attack/defense scenarios. DN extend both the modeling and the analysis capabilities of formalisms based on Attack Trees, which are the main reference model in such a context. In particular, DN can naturally address uncertainty at every level, including the interaction level of attacks and countermeasures, making possible the modeling of situations which are not limited to Boolean combinations of events. Furthermore, inference algorithms can be exploited for a probabilistic analysis with the goal of assessing the risk and the importance of the attacks (with respect to specific sets of countermeasures), and selecting the optimal set (with respect to a specific objective function) of countermeasures to activate.

A methodology for qualitative/quantitative analysis of weighted attack trees

Abstract Attack and Defense Trees (ADT) constitute a formal modeling technique that has become dominant in recent years in the area of qualitative and quantitative cybersecurity analysis of ICT and digital control systems. A Weighted-ADT (WADT) is augmented with cost or impact attributes to evidence the most convenient attack sequence in terms of investment budget and provoked damage and to provide an indication on how to mitigate the located breaches by means of suitable countermeasures. The original analysis technique proposed in this paper is based on the representation of a WADT by means of an extension of Binary Decision Diagrams (BDD), called Multi Terminal Binary Decision Diagrams (MTBDD). MTBDDs allow the modeler to evaluate the probability distribution function of the cost and impact related to any possible attack scenario. A running example illustrates the methodology.

A new symbolic approach for network reliability analysis

In this paper we propose an improved BDD approach to the network reliability analysis, that allows the user to compute an exact solution or an approximation based on reliability bounds when network complexity makes the former solution practically impossible. To this purpose, a new algorithm for encoding the connectivity graph on a Binary Decision Diagram (BDD) has been developed; it reduces the computation memory peak with respect to previous approaches based on the same type of data structure without increasing the execution time, and allows us also to derive from a subset of the minpaths/mincuts a lower/upper bound of the network reliability, so that the quality of the obtained approximation can be estimated. Finally, a fair and detailed comparison between our approach and another state of the art approach presented in the literature is documented through a set of benchmarks.

Selecting failure countermeasures through Decision Network analysis

We propose a framework for the selection of failure countermeasures and repair actions, based on Decision Networks (DN). We show, through specific examples, that standard probabilistic inference on DN can be used to compute system reliability, component importance measures, as well as to select the best (in terms of Maximum Expected Utility) set of failure countermeasures to activate. Finally, by exploiting the DN formalism, both modeling and analysis capabilities are improved with respect to standard combinatorial models, without resorting to the complexity of global state-space models.