Hackathon formats have been praised for their potential for promoting innovative thinking and making in a short time-frame. For this reason, hackathons have also been embraced by many researchers who use hackathons as part of their research in various ways. Through an extensive review of 381 publications published during a 10 year time span, we document the multiple ways in which hackathons are embraced and used by researchers The paper contributes to a better understanding of hackathons as part of research by providing a broad overview as a resource for researchers. We identify three main motivations for using hackathons as part of research: 1) Structuring learning, 2) structuring processes, and 3) enabling participation. For each of the motivations, we identify research with hackathons, and research on hackathons as two main categories. Drawing on several examples from the review we discuss benefits and challenges of using hackathons as part of research.

10 Years of Research With and On Hackathons

For many innovative organisations, Industry 4.0 paves the way for significant operational efficiencies, quality of goods and services and cost reductions. One of the ways to realise these benefits is to embark on digital transformation initiatives that may be summed up as the intelligent interconnectivity of people, processes, data and cyber-connected things. Sadly, this interconnectivity between the enterprise information technology (IT) and industrial control systems (ICS) environment introduces new attack surfaces for critical infrastructure (CI) operators. As a result of the ICS cybersecurity risk introduced by the interconnectivity between the enterprise IT and ICS networks, the purpose of this study is to identify the cybersecurity capabilities that CI operators must have to attain good cybersecurity resilience.,A scoping literature review of best practice international CI protection frameworks, standards and guidelines were conducted. Similar cybersecurity practices from these frameworks, standards and guidelines were grouped together under a corresponding National Institute of Standards and Technology (NIST) cybersecurity framework (CF) practice. Practices that could not be categorised under any of the existing NIST CF practices were considered new insights, and therefore, additions.,A CI cybersecurity capability framework comprising 29 capability domains (cybersecurity focus areas) was developed as an adaptation of the NIST CF with an added dimension. This added dimension emphasises cloud computing and internet of things (IoT) security. Each of the 29 cybersecurity capability domains is executed through various capabilities (cybersecurity processes and procedures). The study found that each cybersecurity capability can further be operationalised by a set of cybersecurity controls derived from various frameworks, standards and guidelines, such as COBIT®, CIS®, ISA/IEC 62443, ISO/IEC 27002 and NIST Special Publication 800-53.,CI sectors are immediately able to adopt the CI cybersecurity capability framework to evaluate their levels of resilience against cyber-attacks, given new attack surfaces introduced by the interconnectivity of cyber-connected things between the enterprise and ICS levels.,The authors present an added dimension to the NIST framework for CI cyber protection. In addition to emphasising cryptography, IoT and cloud computing security aspects, this added dimension highlights the need for an integrated approach to CI cybersecurity resilience instead of a piecemeal approach.

Cybersecurity capabilities for critical infrastructure resilience

Cybersecurity is a hot topic and researchers have published extensively on studies conducted using a variety of different research methods. This paper aims to determine which qualitative research methods were most used and for studying which topics. A systematic literature review on Web of Science, Scopus and ACM DL has been conducted to achieve an overview of quantitative methods used in cybersecurity. The review covered the most recent research in different areas of cybersecurity (i.e., personal, organizational and state cybersecurity) in the period of 2017 to 2019. After careful inspection of papers, we identified 160 papers reporting on the use of qualitative methods. The most common qualitative methods are interviews, followed by case studies and observation. Other studied qualitative methods (i.e., focus groups, grounded theory, action research and Delphi method) seem to be much less frequent. Although qualitative methods are used when studying all key cybersecurity areas, they often lack the necessary rigor and detail observed in other research areas where qualitative methods are well-established.

The power of interpretation: Qualitative methods in cybersecurity research

With the Industry 4.0 paradigm comes the convergence of the Internet Technologies and Operational Technologies, and concepts, such as Industrial Internet of Things (IIoT), cloud manufacturing, Cyber-Physical Systems (CPS), and so on. These concepts bring industries into the big data era and allow for them to have access to potentially useful information in order to optimise the Overall Equipment Effectiveness (OEE); however, most European industries still rely on the Computer-Integrated Manufacturing (CIM) model, where the production systems run as independent systems (i.e., without any communication with the upper levels). Those production systems are controlled by a Programmable Logic Controller, in which a static and rigid program is implemented. This program is static and rigid in a sense that the programmed routines cannot evolve over the time unless a human modifies it. However, to go further in terms of flexibility, we are convinced that it requires moving away from the aforementioned old-fashioned and rigid automation to a ML-based automation, i.e., where the control itself is based on the decisions that were taken by ML algorithms. In order to verify this, we applied a time series classification method on a scale model of a factory using real industrial controllers, and widened the variety of parts the production line has to treat. This study shows that satisfactory results can be obtained only at the expense of the human expertise (i.e., in the industrial process and in the ML process).

https://www.mdpi.com/1424-8220/20/24/7273/pdf

A Case Driven Study of the Use of Time Series Classification for Flexibility in Industry 4.0

A challenge is to develop cyber-physical system scenarios that reflect the diversity and complexity of real-life cyber-physical systems in the research questions that they address. Time-bounded collaborative events, such as hackathons, jams and sprints, are increasingly used as a means of bringing groups of individuals together, in order to explore challenges and develop solutions. This paper describes our experiences, using a science hackathon to bring individual researchers together, in order to develop a common use-case implemented on a shared CPS testbed platform that embodies the diversity in their own security research questions. A qualitative study of the event was conducted, in order to evaluate the success of the process, with a view to improving future similar events.

Science Hackathons for Cyberphysical System Security Research: Putting CPS testbed platforms to good use

Aim: Resilience is discussed among researchers and practitioners for several decades, but its definition has been questioned even recently and many methods are proposed to evaluate the resilience of systems. This paper presents a review of historic and recent research articles that define and/or propose a way to measure resilience of systems. Methods: While definitions are classified according to the ideas they focus on, different categories of metrics are described, such as quantitative or qualitative approaches. Results: This paper points out that many metrics tend to valuate resilience similarly. In fact, they are generally built upon a specific definition. On the other hand metrics can also be really heterogeneous and do not capture the same meaning of system resilience when different definitions of resilience are considered. Conclusion: This paper aims at gathering and comparing metrics and definitions of resilience in order to determine the origins of the particularities and classify them according to the attributes they take into account.

/pdf/resilience-properties-and-metrics-how-far-have-we-gone-1pkxgyg4me.pdf

Resilience properties and metrics: how far have we gone?

Contemporary systems are built from complex arrangements of interoperating components implementing functional and other non-functional concerns that are necessary to ensure continuing service delivery. One of these concerns—resilience—relies on components that implement a variety of mechanisms, such as access controls, adaptability and redundancy. How these mechanisms interoperate with each other and the systems’ functional components to provide resilience is considered in this paper. External consistency, defined as the extent to which data in the system corresponds to its real-world value, provides a natural interpretation for the definition of resilience. A model of resilience is developed that can be used to trace how the functional and non-functional components in a system contribute to the determination of our confidence in the external consistency of the data that they process.

Towards the Evaluation of End-to-End Resilience Through External Consistency

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Science Hackathons for Cyberphysical System Security Research: Putting CPS testbed platforms to good use

Science Hackathons for Cyberphysical System Security Research: Putting CPS testbed platforms to good use

Resilience properties and metrics: how far have we gone?

Towards the Evaluation of End-to-End Resilience Through External Consistency