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

Autonomic computing architecture for SCADA cyber security

Cognitive computing relates to intelligent computing platforms that are based on the disciplines of artificial intelligence, machine learning, and other innovative technologies. These technologies can be used to design systems that mimic the human brain to learn about their environment and can autonomously predict an impending anomalous situation. IBM first used the term ‘Autonomic Computing’ in 2001 to combat the looming complexity crisis (Ganek and Corbi, 2003). The concept has been inspired by the human biological autonomic system. An autonomic system is self-healing, self-regulating, self-optimising and self-protecting (Ganek and Corbi, 2003). Therefore, the system should be able to protect itself against both malicious attacks and unintended mistakes by the operator

Autonomic computing meets SCADA security

© 2017 IEEE. National assets such as transportation networks, large manufacturing, business and health facilities, power generation, and distribution networks are critical infrastructures. The cyber threats to these infrastructures have increasingly become more sophisticated, extensive and numerous. Cyber security conventional measures have proved useful in the past but increasing sophistication of attacks dictates the need for newer measures. The autonomic computing paradigm mimics the autonomic nervous system and is promising to meet the latest challenges in the cyber threat landscape. This paper provides a brief review of autonomic computing applications for SCADA systems and proposes architecture for cyber security

Identifying attack surfaces in the evolving space industry using reference architectures

The space environment is currently undergoing a substantial change and many new entrants to the market are deploying devices, satellites and systems in space; this evolution has been termed as NewSpace. The change is complicated by technological developments such as deploying machine learning based autonomous space systems and the Internet of Space Things (IoST). In the IoST, space systems will rely on satellite-to-x communication and interactions with wider aspects of the ground segment to a greater degree than existing systems. Such developments will inevitably lead to a change in the cyber security threat landscape of space systems. Inevitably, there will be a greater number of attack vectors for adversaries to exploit, and previously infeasible threats can be realised, and thus require mitigation. In this paper, we present a reference architecture (RA) that can be used to abstractly model in situ applications of this new space landscape. The RA specifies high-level system components and their interactions. By instantiating the RA for two scenarios we demonstrate how to analyse the attack surface using attack trees

Toward unified security and privacy protection for smart meter networks

The management of security and privacy protection mechanisms is one fundamental issue of future smart grid and metering networks. Designing effective and economic measures is a non-trivial task due to a) the large number of system requirements and b) the uncertainty over how the system functionalities are going to be specified and evolve. The paper explores a unified approach for addressing security and privacy of smart metering systems. In the process, we present a unified framework that entails the analysis and synthesis of security solutions associated with closely interrelated components of a typical smart metering system. Ultimately, the proposed framework can be used as a guideline for embedding cross-domain security and privacy solutions into smart grid communication systems

Assets focus risk management framework for critical infrastructure cybersecurity risk management

Critical infrastructure (CI) is vital for the overall economic growth and its reliable and safe operation is essential for a nation's stability and people's safety. Proper operation of the assets is essential for such a system and any threats that could negatively impact the asset could have a severe disruption. Risk management is an important aspect of the protection of CI. There are several frameworks and methodologies for identifying assets, quantifying and analysing vulnerabilities. However, there is a lack of focus on the interdependencies among the assets and cascading effect of the inherent vulnerabilities on the asset. This study attempts to bridge that gap by presenting a novel asset focus risk management approach for the CI. It presents a systematic methodology for identifying and analysing critical assets, their potential vulnerabilities, threats and risks facing CI. This work taking into account cascading vulnerability impacts on assets leading to threats and causing risk. The authors use a running example from a smart grid system to demonstrate the usability of the approach. The result shows that some assets are prioritised and more vulnerable than other assets for the power grid system and it can severely impact on the overall business continuity