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

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

Diagnosing accidental and malicious events in an industrial control system requires an event model with specific capacities Most models are dedicated to either safety or security but rarely both And the latter are developed for objectives other than diagnosis and therefore unfit for this task In this paper, we propose an event model considering both safety and security events, usable in real-time, with a probabilistic measure of on-going and future events This model is able to replace alerts in the context of more global scenarios, including with reinforcements or conflicts between safety and security The model is then used to provide an analysis of some of the security and safety events in the Taum Sauk Hydroelectric Power Station

https://hal.inria.fr/hal-01954422/document

Probabilistic Event Graph to Model Safety and Security for Diagnosis Purposes

The recent and increasing interconnection of industrial systems with information technologies creates a new paradigm in which new challenges arise. Being able to provide an explanation when accidents and attacks strike the system is one of them. This article presents an event model designed to provide useful and relevant information for diagnosis of safety and security events. We provide a means for system experts to model elementary events that are automatically recombined in complex and complete scenarios. We specifically focus on the ability to represent countermeasures and sequences of events, recurrent problems in the literature. We also introduce a means to precisely measure the wear of components, an important feature for the model to obtain accurate values. We showcase the use of our model for diagnosis purposes on a cyber-physical system testbed.

PROS2E, a Probabilistic Representation of Safety and Security Events for Diagnosis

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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

Probabilistic Event Graph to Model Safety and Security for Diagnosis Purposes

PROS2E, a Probabilistic Representation of Safety and Security Events for Diagnosis