Assessing and augmenting SCADA cyber security: a survey of techniques

SCADA systems monitor and control critical infrastructures of national importance such as power generation and distribution, water supply, transportation networks, and manufacturing facilities. The pervasiveness, miniaturisations and declining costs of internet connectivity have transformed these systems from strictly isolated to highly interconnected networks. The connectivity provides immense benefits such as reliability, scalability and remote connectivity, but at the same time exposes an otherwise isolated and secure system, to global cyber security threats. This inevitable transformation to highly connected systems thus necessitates effective security safeguards to be in place as any compromise or downtime of SCADA systems can have severe economic, safety and security ramifications. One way to ensure vital asset protection is to adopt a viewpoint similar to an attacker to determine weaknesses and loopholes in defences. Such mind sets help to identify and fix potential breaches before their exploitation. This paper surveys tools and techniques to uncover SCADA system vulnerabilities. A comprehensive review of the selected approaches is provided along with their applicability

Intelligent integrated maintenance for wind power generation

A novel architecture and system for the provision of Reliability Centred Maintenance (RCM) for offshore wind power generation is presented. The architecture was developed by conducting a bottom-up analysis of the data required to support RCM within this specific industry, combined with a top-down analysis of the required maintenance functionality. The architecture and system consists of three integrated modules for Intelligent Condition Monitoring, Reliability and Maintenance Modelling, and Maintenance Scheduling that provide a scalable solution for performing dynamic, efficient and cost effective preventative maintenance management within this extremely demanding renewable energy generation sector. The system demonstrates for the first time, the integration of state-of-the-art advanced mathematical techniques: Random Forests, Dynamic Bayesian Networks, and Memetic Algorithms in the development of an intelligent autonomous solution. The results from the application of the intelligent integrated system illustrated the automated detection of faults within a wind farm consisting of over 100 turbines, the modelling and updating of the turbines’ survivability and creation of a hierarchy of maintenance actions, and the optimising of the maintenance schedule with a view to maximising the availability and revenue generation of the turbines

A holistic approach for measuring the survivability of SCADA systems

Supervisory Control and Data Acquisition (SCADA) systems are responsible for controlling and monitoring Industrial Control Systems (ICS) and Critical Infrastructure Systems (CIS) among others. Such systems are responsible to provide services our society relies on such as gas, electricity, and water distribution. They process our waste; manage our railways and our traffic. Nevertheless to say, they are vital for our society and any disruptions on such systems may produce from financial disasters to ultimately loss of lives. SCADA systems have evolved over the years, from standalone, proprietary solutions and closed networks into large-scale, highly distributed software systems operating over open networks such as the internet. In addition, the hardware and software utilised by SCADA systems is now, in most cases, based on COTS (Commercial Off-The-Shelf) solutions. As they evolved they became vulnerable to malicious attacks. Over the last few years there is a push from the computer security industry on adapting their security tools and techniques to address the security issues of SCADA systems. Such move is welcome however is not sufficient, otherwise successful malicious attacks on computer systems would be non-existent. We strongly believe that rather than trying to stop and detect every attack on SCADA systems it is imperative to focus on providing critical services in the presence of malicious attacks. Such motivation is similar with the concepts of survivability, a discipline integrates areas of computer science such as performance, security, fault-tolerance and reliability. In this thesis we present a new concept of survivability; Holistic survivability is an analysis framework suitable for a new era of data-driven networked systems. It extends the current view of survivability by incorporating service interdependencies as a key property and aspects of machine learning. The framework uses the formalism of probabilistic graphical models to quantify survivability and introduces new metrics and heuristics to learn and identify essential services automatically. Current definitions of survivability are often limited since they either apply performance as measurement metric or use security metrics without any survivability context. Holistic survivability addresses such issues by providing a flexible framework where performance and security metrics can be tailored to the context of survivability. In other words, by applying performance and security our work aims to support key survivability properties such as recognition and resistance. The models and metrics here introduced are applied to SCADA systems as such systems insecurity is one of the motivations of this work. We believe that the proposed work goes beyond the current status of survivability models. Holistic survivability is flexible enough to support the addition of other metrics and can be easily used with different models. Because it is based on a well-known formalism its definition and implementation are easy to grasp and to apply. Perhaps more importantly, this proposed work is aimed to a new era where data is being produced and consumed on a large-scale. Holistic survivability aims to be the catalyst to new models based on data that will provide better and more accurate insights on the survivability of systems

On the Definition of Cyber-Physical Resilience in Power Systems

In recent years, advanced sensors, intelligent automation, communication networks, and information technologies have been integrated into the electric grid to enhance its performance and efficiency. Integrating these new technologies has resulted in more interconnections and interdependencies between the physical and cyber components of the grid. Natural disasters and man-made perturbations have begun to threaten grid integrity more often. Urban infrastructure networks are highly reliant on the electric grid and consequently, the vulnerability of infrastructure networks to electric grid outages is becoming a major global concern. In order to minimize the economic, social, and political impacts of power system outages, the grid must be resilient. The concept of a power system cyber-physical resilience centers around maintaining system states at a stable level in the presence of disturbances. Resilience is a multidimensional property of the electric grid, it requires managing disturbances originating from physical component failures, cyber component malfunctions, and human attacks. In the electric grid community, there is not a clear and universally accepted definition of cyber-physical resilience. This paper focuses on the definition of resilience for the electric grid and reviews key concepts related to system resilience. This paper aims to advance the field not only by adding cyber-physical resilience concepts to power systems vocabulary, but also by proposing a new way of thinking about grid operation with unexpected disturbances and hazards and leveraging distributed energy resources.Comment: 20 pages. This is a modified versio

SUNSEED — An evolutionary path to smart grid comms over converged telco and energy provider networks

SUNSEED, 'Sustainable and robust networking for smart electricity distribution', is a 3-year project started in 2014 and partially funded under call FP7-ICT-2013-11. The project objective is to research, design and implement methods for exploitation of existing communication infrastructure of energy distribution service operators (DSO) and telecom operators (telco) for the future smart grid operations and services. To achieve this objective, SUNSEED proposes an evolutionary approach to converge existing DSO and telco networks, consisting of six steps: overlap, interconnect, interoperate, manage, plan and open. Each step involves identification of the related smart grid service requirements and implementation of the appropriate solutions. The promise of SUNSEED approach lies in potentially much lower investments and total cost of ownership of future smart energy grids within dense distributed energy generation and prosumer environments

A review of cyber security risk assessment methods for SCADA systems

This paper reviews the state of the art in cyber security risk assessment of Supervisory Control and Data Acquisition (SCADA) systems. We select and in-detail examine twenty-four risk assessment methods developed for or applied in the context of a SCADA system. We describe the essence of the methods and then analyse them in terms of aim; application domain; the stages of risk management addressed; key risk management concepts covered; impact measurement; sources of probabilistic data; evaluation and tool support. Based on the analysis, we suggest an intuitive scheme for the categorisation of cyber security risk assessment methods for SCADA systems. We also outline five research challenges facing the domain and point out the approaches that might be taken

Security, Privacy and Safety Risk Assessment for Virtual Reality Learning Environment Applications

Social Virtual Reality based Learning Environments (VRLEs) such as vSocial render instructional content in a three-dimensional immersive computer experience for training youth with learning impediments. There are limited prior works that explored attack vulnerability in VR technology, and hence there is a need for systematic frameworks to quantify risks corresponding to security, privacy, and safety (SPS) threats. The SPS threats can adversely impact the educational user experience and hinder delivery of VRLE content. In this paper, we propose a novel risk assessment framework that utilizes attack trees to calculate a risk score for varied VRLE threats with rate and duration of threats as inputs. We compare the impact of a well-constructed attack tree with an adhoc attack tree to study the trade-offs between overheads in managing attack trees, and the cost of risk mitigation when vulnerabilities are identified. We use a vSocial VRLE testbed in a case study to showcase the effectiveness of our framework and demonstrate how a suitable attack tree formalism can result in a more safer, privacy-preserving and secure VRLE system.Comment: Tp appear in the CCNC 2019 Conferenc

A Graphical Adversarial Risk Analysis Model for Oil and Gas Drilling Cybersecurity

Oil and gas drilling is based, increasingly, on operational technology, whose cybersecurity is complicated by several challenges. We propose a graphical model for cybersecurity risk assessment based on Adversarial Risk Analysis to face those challenges. We also provide an example of the model in the context of an offshore drilling rig. The proposed model provides a more formal and comprehensive analysis of risks, still using the standard business language based on decisions, risks, and value.Comment: In Proceedings GraMSec 2014, arXiv:1404.163

A Constrained, Possibilistic Logical Approach for Software System Survivability Evaluation

In this paper, we present a logical framework to facilitate users in assessing a software system in terms of the required survivability features. Survivability evaluation is essential in linking foreign software components to an existing system or obtaining software systems from external sources. It is important to make sure that any foreign components/systems will not compromise the current system’s survivability properties. Given the increasing large scope and complexity of modern software systems, there is a need for an evaluation framework to accommodate uncertain, vague, or even ill-known knowledge for a robust evaluation based on multi-dimensional criteria. Our framework incorporates user-defined constrains on survivability requirements. Necessity-based possibilistic uncertainty and user survivability requirement constraints are effectively linked to logic reasoning. A proof-of-concept system has been developed to validate the proposed approach. To our best knowledge, our work is the first attempt to incorporate vague, imprecise information into software system survivability evaluation