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

Capability-based access control for cyber physical systems

Cyber Physical Systems (CPS) couple digital systems with the physical environment, creating technical, usability, and economic security challenges beyond those of information systems. Their distributed and hierarchical nature, real-time and safety-critical requirements, and limited resources create new vulnerability classes and severely constrain the security solution space. This dissertation explores these challenges, focusing on Industrial Control Systems (ICS), but demonstrating broader applicability to the whole domain. We begin by systematising the usability and economic challenges to secure ICS. We fingerprint and track more than 10\,000 Internet-connected devices over four years and show the population is growing, continuously-connected, and unpatched. We then explore adversarial interest in this vulnerable population. We track 150\,000 botnet hosts, sift 70 million underground forum posts, and perform the largest ICS honeypot study to date to demonstrate that the cybercrime community has little competence or interest in the domain. We show that the current heterogeneity, cost, and level of expertise required for large-scale attacks on ICS are economic deterrents when targets in the IoT domain are available. The ICS landscape is changing, however, and we demonstrate the imminent convergence with the IoT domain as inexpensive hardware, commodity operating Cyber Physical Systems (CPS) couple digital systems with the physical environment, creating technical, usability, and economic security challenges beyond those of information systems. Their distributed and hierarchical nature, real-time and safety-critical requirements, and limited resources create new vulnerability classes and severely constrain the security solution space. This dissertation explores these challenges, focusing on Industrial Control Systems (ICS), but demonstrating broader applicability to the whole domain. We begin by systematising the usability and economic challenges to secure ICS. We fingerprint and track more than 10,000 Internet-connected devices over four years and show the population is growing, continuously-connected, and unpatched. We then explore adversarial interest in this vulnerable population. We track 150,000 botnet hosts, sift 70 million underground forum posts, and perform the largest ICS honeypot study to date to demonstrate that the cybercrime community has little competence or interest in the domain. We show that the current heterogeneity, cost, and level of expertise required for large-scale attacks on ICS are economic deterrents when targets in the IoT domain are available. The ICS landscape is changing, however, and we demonstrate the imminent convergence with the IoT domain as inexpensive hardware, commodity operating systems, and wireless connectivity become standard. Industry's security solution is boundary defence, pushing privilege to firewalls and anomaly detectors; however, this propagates rather than minimises privilege and leaves the hierarchy vulnerable to a single boundary compromise. In contrast, we propose, implement, and evaluate a security architecture based on distributed capabilities. Specifically, we show that object capabilities, representing physical resources, can be constructed, delegated, and used anywhere in a distributed CPS by composing hardware-enforced architectural capabilities and cryptographic network tokens. Our architecture provides defence-in-depth, minimising privilege at every level of the CPS hierarchy, and both supports and adds integrity protection to legacy CPS protocols. We implement distributed capabilities in robotics and ICS demonstrators, and we show that our architecture adds negligible overhead to realistic integrations and can be implemented without significant modification to existing source code. In contrast, we propose, implement, and evaluate a security architecture based on distributed capabilities. Specifically, we show that object capabilities, representing physical resources, can be constructed, delegated, and used anywhere in a distributed CPS by composing hardware-enforced architectural capabilities and cryptographic network tokens. Our architecture provides defence-in-depth, minimising privilege at every level of the CPS hierarchy, and both supports and adds integrity protection to legacy CPS protocols. We implement distributed capabilities in robotics and ICS demonstrators, and we show that our architecture adds negligible overhead to realistic integrations and can be implemented without significant modification to existing source code

Use Case Based Blended Teaching of IIoT Cybersecurity in the Industry 4.0 Era

[Abstract] Industry 4.0 and Industrial Internet of Things (IIoT) are paradigms that are driving current industrial revolution by connecting to the Internet industrial machinery, management tools or products so as to control and gather data about them. The problem is that many IIoT/Industry 4.0 devices have been connected to the Internet without considering the implementation of proper security measures, thus existing many examples of misconfigured or weakly protected devices. Securing such systems requires very specific skills, which, unfortunately, are not taught extensively in engineering schools. This article details how Industry 4.0 and IIoT cybersecurity can be learned through practical use cases, making use of a methodology that allows for carrying out audits to students that have no previous experience in IIoT or industrial cybersecurity. The described teaching approach is blended and has been imparted at the University of A Coruña (Spain) during the last years, even during the first semester of 2020, when the university was closed due to the COVID-19 pandemic lockdown. Such an approach is supported by online tools like Shodan, which ease the detection of vulnerable IIoT devices. The feedback results provided by the students show that they consider useful the proposed methodology, which allowed them to find that 13% of the IIoT/Industry 4.0 systems they analyzed could be accessed really easily. In addition, the obtained teaching results indicate that the established course learning outcomes are accomplished. Therefore, this article provides useful guidelines for teaching industrial cybersecurity and thus train the next generation of security researchers and developers.This work has been funded by the Xunta de Galicia (ED431G 2019/01), the Agencia Estatal de Investigación of Spain (TEC2016-75067-C4-1-R, RED2018-102668-T, PID2019-104958RB-C42) and ERDF funds of the EU (AEI/FEDER, UE)Xunta de Galicia; ED431G 2019/0

A pattern-based framework for the design of secure and dependable SDN/NFV-enabled networks

As the world becomes an interconnected network where objects and humans interact, cyber and physical networks appear to play an important role in smart ecosystems due to their increasing use on critical infrastructure and smart cities. Software Defined Networking (SDN) and Network Function Virtualisation (NFV) are a promising combination for programmable connectivity, rapid service provisioning and service chaining as they offer the necessary end-to-end optimisations. However, with the actual exponential growth of connected devices, future networks, such as SDN and NFV, require open architectures, facilitated by standards and a strong ecosystem.In this thesis, a model-based approach is proposed to support the design and verification of secure and dependable SDN/NFV-enabled networks. The model is based on the development of a pattern-based approach to design executable patterns as solutions for reusable designs and interactions of objects, encoded in a rule based reasoning system, able to guarantee security and dependability (S&D) properties in SDN/NFV enabled networks. To execute S&D patterns, a pattern based framework is implemented for the insertion of patterns at design and at runtime level. The developed pattern framework highlights also the benefit of leveraging the flexibility of SDN/NFV-enabled networks to deploy enhanced reactive security mechanisms for the protection of the industrial network via the use of service function chaining (SFC). To prove the importance of this approach and the functionality of the pattern framework, different pattern instances are implemented to guarantee S&D in network infrastructures. The developed design patterns are able to design network topologies, guarantee network properties and offer security service provisioning and chaining. Finally, in order to evaluate the developed patterns in the pattern framework, three different use cases are described, where a number of usage scenarios are deployed and evaluated experimentally

Application Perspective on Cybersecurity Testbed for Industrial Control Systems

The low-power wide-area (LPWA) technologies, which enable cost and energy-efficient wireless connectivity for massive deployments of autonomous machines, have enabled and boosted the development of many new Internet of things (IoT) applications; however, the security of LPWA technologies in general, and specifically those operating in the license-free frequency bands, have received somewhat limited attention so far. This paper focuses specifically on the security and privacy aspects of one of the most popular license-free-band LPWA technologies, which is named LoRaWAN. The paper’s key contributions are the details of the design and experimental validation of a security-focused testbed, based on the combination of software-defined radio (SDR) and GNU Radio software with a standalone LoRaWAN transceiver. By implementing the two practical man-in-the-middle attacks (i.e., the replay and bit-flipping attacks through intercepting the over-the-air activation procedure by an external to the network attacker device), we demonstrate that the developed testbed enables practical experiments for on-air security in real-life conditions. This makes the designed testbed perspective for validating the novel security solutions and approaches and draws attention to some of the relevant security challenges extant in LoRaWAN

The Proceedings of 15th Australian Information Security Management Conference, 5-6 December, 2017, Edith Cowan University, Perth, Australia

Conference Foreword The annual Security Congress, run by the Security Research Institute at Edith Cowan University, includes the Australian Information Security and Management Conference. Now in its fifteenth year, the conference remains popular for its diverse content and mixture of technical research and discussion papers. The area of information security and management continues to be varied, as is reflected by the wide variety of subject matter covered by the papers this year. The papers cover topics from vulnerabilities in “Internet of Things” protocols through to improvements in biometric identification algorithms and surveillance camera weaknesses. The conference has drawn interest and papers from within Australia and internationally. All submitted papers were subject to a double blind peer review process. Twenty two papers were submitted from Australia and overseas, of which eighteen were accepted for final presentation and publication. We wish to thank the reviewers for kindly volunteering their time and expertise in support of this event. We would also like to thank the conference committee who have organised yet another successful congress. Events such as this are impossible without the tireless efforts of such people in reviewing and editing the conference papers, and assisting with the planning, organisation and execution of the conference. To our sponsors, also a vote of thanks for both the financial and moral support provided to the conference. Finally, thank you to the administrative and technical staff, and students of the ECU Security Research Institute for their contributions to the running of the conference

Ransomware detection using the dynamic analysis and machine learning: A survey and research directions

Ransomware is an ill-famed malware that has received recognition because of its lethal and irrevocable effects on its victims. The irreparable loss caused due to ransomware requires the timely detection of these attacks. Several studies including surveys and reviews are conducted on the evolution, taxonomy, trends, threats, and countermeasures of ransomware. Some of these studies were specifically dedicated to IoT and android platforms. However, there is not a single study in the available literature that addresses the significance of dynamic analysis for the ransomware detection studies for all the targeted platforms. This study also provides the information about the datasets collection from its sources, which were utilized in the ransomware detection studies of the diverse platforms. This study is also distinct in terms of providing a survey about the ransomware detection studies utilizing machine learning, deep learning, and blend of both techniques while capitalizing on the advantages of dynamic analysis for the ransomware detection. The presented work considers the ransomware detection studies conducted from 2019 to 2021. This study provides an ample list of future directions which will pave the way for future research

Next-Generation Industrial Control System (ICS) Security:Towards ICS Honeypots for Defence-in-Depth Security

The advent of Industry 4.0 and smart manufacturing has led to an increased convergence of traditional manufacturing and production technologies with IP communications. Legacy Industrial Control System (ICS) devices are now exposed to a wide range of previously unconsidered threats, which must be considered to ensure the safe operation of industrial processes. Especially as cyberspace is presenting itself as a popular domain for nation-state operations, including against critical infrastructure. Honeypots are a well-known concept within traditional IT security, and they can enable a more proactive approach to security, unlike traditional systems. More work needs to be done to understand their usefulness within OT and critical infrastructure. This thesis advances beyond current honeypot implementations and furthers the current state-of-the-art by delivering novel ways of deploying ICS honeypots and delivering concrete answers to key research questions within the area. This is done by answering the question previously raised from a multitude of perspectives. We discuss relevant legislation, such as the UK Cyber Assessment Framework, the US NIST Framework for Improving Critical Infrastructure Cybersecurity, and associated industry-based standards and guidelines supporting operator compliance. Standards and guidance are used to frame a discussion on our survey of existing ICS honeypot implementations in the literature and their role in supporting regulatory objectives. However, these deployments are not always correctly configured and might differ from a real ICS. Based on these insights, we propose a novel framework towards the classification and implementation of ICS honeypots. This is underpinned by a study into the passive identification of ICS honeypots using Internet scanner data to identify honeypot characteristics. We also present how honeypots can be leveraged to identify when bespoke ICS vulnerabilities are exploited within the organisational network—further strengthening the case for honeypot usage within critical infrastructure environments. Additionally, we demonstrate a fundamentally different approach to the deployment of honeypots. By deploying it as a deterrent, to reduce the likelihood that an adversary interacts with a real system. This is important as skilled attackers are now adept at fingerprinting and avoiding honeypots. The results presented in this thesis demonstrate that honeypots can provide several benefits to the cyber security of and alignment to regulations within the critical infrastructure environment