STPA-SafeSec: Safety and Security Analysis for Cyber-Physical Systems

Cyber-physical systems tightly integrate physical processes and information and communication technologies. As today’s critical infrastructures, e.g., the power grid or water distribution networks, are complex cyber-physical systems, ensuring their safety and security becomes of paramount importance. Traditional safety analysis methods, such as HAZOP, are ill-suited to assess these systems. Furthermore, cybersecurity vulnerabilities are often not considered critical, because their effects on the physical processes are not fully understood. In this work, we present STPA-SafeSec, a novel analysis methodology for both safety and security. Its results show the dependencies between cybersecurity vulnerabilities and system safety. Using this information, the most effective mitigation strategies to ensure safety and security of the system can be readily identified. We apply STPA-SafeSec to a use case in the power grid domain, and highlight its benefits.

Early warning systems for cyber defence

Cybercriminals ramp up their efforts with sophisticated techniques while defenders gradually update their typical security measures. Attackers often have a long-term interest in their targets. Due to a number of factors such as scale, architecture and nonproductive traffic however it makes difficult to detect them using typical intrusion detection techniques. Cyber early warning systems (CEWS) aim at alerting such attempts in their nascent stages using preliminary indicators. Design and implementation of such systems involves numerous research challenges such as generic set of indicators, intelligence gathering, uncertainty reasoning and information fusion. This paper discusses such challenges and presents the reader with compelling motivation. A carefully deployed empirical analysis using a real world attack scenario and a real network traffic capture is also presented.

Towards a Resilience Metric Framework for Cyber-Physical Systems

Resilience is widely accepted as a desirable system property for cyber-physical systems. However, there are no metrics that can be used to measure the resilience of cyber-physical systems (CPS) while the multi-dimensional nature of performance in these systems is considered. In this work, we present first results towards a resilience metric framework. The key contributions of this framework are threefold: First, it allows to evaluate resilience with respect to different performance indicators that are of interest. Second, complexities that are relevant to the performance indicators of interest, can be intentionally abstracted. Third and final, it supports the identification of reasons for good or bad resilience to improve system design.

Progress and Research in Cybersecurity - Supporting a resilient and trustworthy system for the UK

Executive summary
Digital systems have transformed, and will continue to transform, our world. Supportive government policy, a strong research base and a history of industrial success make the UK particularly well-placed to realise the benefits of the emerging digital society. These benefits have already been substantial, but they remain at risk. Protecting the benefits and minimising the risks requires reliable and robust cybersecurity, underpinned by a strong research and translation system.
Trust is essential for growing and maintaining participation in the digital society. Organisations earn trust by acting in a trustworthy manner: building systems that are reliable and secure, treating people, their privacy and their data with respect, and providing credible and comprehensible information to help people understand how secure they are.
Resilience, the ability to function, adapt, grow, learn and transform under stress or in the face of shocks, will help organisations deliver systems that are reliable and secure. Resilient organisations can better protect their customers, provide more useful products and services, and earn people’s trust.
Research and innovation in industry and academia will continue to make important contributions to creating this resilient and trusted digital environment. Research can illuminate how best to build, assess and improve digital systems, integrating insights from different disciplines, sectors and around the globe. It can also generate advances to help cybersecurity keep up with the continued evolution of cyber risks.
Translation of innovative ideas and approaches from research will create a strong supply of reliable, proven solutions to difficult to predict cybersecurity risks. This is best achieved by maximising the diversity and number of innovations that see the light of day as products.
Policy, practice and research will all need to adapt. The recommendations made in this report seek to set up a trustworthy, self-improving and resilient digital environment that can thrive in the face of unanticipated threats, and earn the trust people place in it.
Innovation and research will be particularly important to the UK’s economy as it establishes a new relationship with the EU. Cybersecurity delivers important economic benefits, both by underpinning the digital foundations of UK business and trade and also through innovation that feeds directly into growth. The findings of this report will be relevant regardless of how the UK’s relationship to the EU changes.
Headline recommendations
● Trust: Governments must commit to preserving the robustness of encryption, including end-to-end encryption, and promoting its widespread use. Encryption is a foundational security technology that is needed to build user trust, improve security standards and fully realise the benefits of digital systems.
● Resilience: Government should commission an independent review of the UK’s future cybersecurity needs, focused on the institutional structures needed to support resilient and trustworthy digital systems in the medium and longer term. A self-improving, resilient digital environment will need to be guided and governed by institutions that are transparent, expert and have a clear and widely-understood remit.
● Research: A step change in cybersecurity research and practice should be pursued; it will require a new approach to research, focused on identifying ambitious high-level goals and enabling excellent researchers to pursue those ambitions. This would build on the UK's existing strengths in many aspects of cybersecurity research and ultimately help build a resilient and trusted digital sector based on excellent research and world-class expertise.
● Translation: The UK should promote a free and unencumbered flow of cybersecurity ideas from research to practical use and support approaches that have public benefits beyond their short term financial return. The unanticipated nature of future cyber threats means that a diverse set of cybersecurity ideas and approaches will be needed to build resilience and adaptivity. Many of the most valuable ideas will have broad security benefits for the public, beyond any direct financial returns.

Effective network security monitoring: from attribution to target-centric monitoring

Network security monitoring remains a challenge. As global networks scale up, in terms of traffic, volume and speed, effective attribution of cyber attacks is increasingly difficult. The problem is compounded by a combination of other factors, including the architecture of the Internet, multi-stage attacks and increasing volumes of nonproductive traffic. This paper proposes to shift the focus of security monitoring from the source to the target. Simply put, resources devoted to detection and attribution should be redeployed to efficiently monitor for targeting and prevention of attacks. The effort of detection should aim to determine whether a node is under attack, and if so, effectively prevent the attack. This paper contributes by systematically reviewing the structural, operational and legal reasons underlying this argument, and presents empirical evidence to support a shift away from attribution to favour of a target-centric monitoring approach. A carefully deployed set of experiments are presented and a detailed analysis of the results is achieved.

Threat Analysis of BlackEnergy Malware for Synchrophasor based Real-time Control and Monitoring in Smart Grid

The BlackEnergy malware targeting critical infrastructures has a long history. It evolved over time from a simple DDoS platform to a quite sophisticated plug-in based malware. The plug-in architecture has a persistent malware core with easily installable attack specific modules for DDoS, spamming, info-stealing, remote access, boot-sector formatting etc. BlackEnergy has been involved in several high profile cyber physical attacks including the recent Ukraine power grid attack in December 2015. This paper investigates the evolution of BlackEnergy and its cyber attack capabilities. It presents a basic cyber attack model used by BlackEnergy for targeting industrial control systems. In particular, the paper analyzes cyber threats of BlackEnergy for synchrophasor based systems which are used for real-time control and monitoring functionalities in smart grid. Several BlackEnergy based attack scenarios have been investigated by exploiting the vulnerabilities in two widely used synchrophasor communication standards: (i) IEEE C37.118 and (ii) IEC 61850-90-5. Specifically, the paper addresses reconnaissance, DDoS, man-in-the-middle and replay/reflection attacks on IEEE C37.118 and IEC 61850-90-5. Further, the paper also investigates protection strategies for detection and prevention of BlackEnergy based cyber physical attacks.

N-opcode analysis for android malware classification and categorization

Malware detection is a growing problem particularly on the Android mobile platform due to its increasing popularity and accessibility to numerous third party app markets. This has also been made worse by the increasingly sophisticated detection avoidance techniques employed by emerging malware families. This calls for more effective techniques for detection and classification of Android malware. Hence, in this paper we present an n-opcode analysis based approach that utilizes machine learning to classify and categorize Android malware. This approach enables automated feature discovery that eliminates the need for applying expert or domain knowledge to define the needed features. Our experiments on 2520 samples that were performed using up to 10-gram opcode features showed that an f-measure of 98% is achievable using this approach.

Dynalog: an automated dynamic analysis framework for characterizing android applications

Android is becoming ubiquitous and currently has the largest share of the mobile OS market with billions of application downloads from the official app market. It has also become the platform most targeted by mobile malware that are becoming more sophisticated to evade state-of-the-art detection approaches. Many Android malware families employ obfuscation techniques in order to avoid detection and this may defeat static analysis based approaches. Dynamic analysis on the other hand may be used to overcome this limitation. Hence in this paper we propose DynaLog, a dynamic analysis based framework for characterizing Android applications. The framework provides the capability to analyse the behaviour of applications based on an extensive number of dynamic features. It provides an automated platform for mass analysis and characterization of apps that is useful for quickly identifying and isolating malicious applications. The DynaLog framework leverages existing open source tools to extract and log high level behaviours, API calls, and critical events that can be used to explore the characteristics of an application, thus providing an extensible dynamic analysis platform for detecting Android malware. DynaLog is evaluated using real malware samples and clean applications demonstrating its capabilities for effective analysis and detection of malicious applications.

Multidimensional Intrusion Detection System for IEC 61850 based SCADA Networks

Emerging cybersecurity vulnerabilities in supervisory control and data acquisition (SCADA) systems are becoming urgent engineering issues for modern substations. This paper proposes a novel intrusion detection system (IDS) tailored for cybersecurity of IEC 61850 based substations. The proposed IDS integrates physical knowledge, protocol specifications and logical behaviours to provide a comprehensive and effective solution that is able to mitigate various cyberattacks. The proposed approach comprises access control detection, protocol whitelisting, model-based detection, and multi-parameter based detection. This SCADA-specific IDS is implemented and validated using a comprehensive and realistic cyber-physical test-bed and data from a real 500kV smart substation.