Artificial intelligence and machine learning in dynamic cyber risk analytics at the edge
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Artificial intelligence and machine learning in dynamic cyber risk analytics at the edge Petar Radanliev1 · David De Roure1 · Rob Walton1 · Max Van Kleek2 · Rafael Mantilla Montalvo3 · La’Treall Maddox3 · Omar Santos3 · Peter Burnap4 · Eirini Anthi4 Received: 22 April 2020 / Accepted: 21 September 2020 © The Author(s) 2020 OPEN
Abstract We explore the potential and practical challenges in the use of artificial intelligence (AI) in cyber risk analytics, for improving organisational resilience and understanding cyber risk. The research is focused on identifying the role of AI in connected devices such as Internet of Things (IoT) devices. Through literature review, we identify wide ranging and creative methodologies for cyber analytics and explore the risks of deliberately influencing or disrupting behaviours to sociotechnical systems. This resulted in the modelling of the connections and interdependencies between a system’s edge components to both external and internal services and systems. We focus on proposals for models, infrastructures and frameworks of IoT systems found in both business reports and technical papers. We analyse this juxtaposition of related systems and technologies, in academic and industry papers published in the past 10 years. Then, we report the results of a qualitative empirical study that correlates the academic literature with key technological advances in connected devices. The work is based on grouping future and present techniques and presenting the results through a new conceptual framework. With the application of social science’s grounded theory, the framework details a new process for a prototype of AI-enabled dynamic cyber risk analytics at the edge. Keywords Artificial cognition · Internet of things · Cyber-physical systems · Artificial intelligence · Machine learning · Automatic anomaly detection system · Dynamic analytics
1 Introduction It has been argued that the spectacular advancements in cyber-physical systems (CPSs) and Internet of things (IoT) technology represent the foundation for Industry 4.0 [1], an IoT term originated in 1999 [2], along with the first view of how an IoT-based environment might look like in the future [3]. The term CPS encompasses the complex and multidisciplinary aspects of ‘smart’ systems that are built and depend on the interaction between physical and computational components [4]. CPS theory emerged from control theory and control systems engineering and
focuses on the interconnection of physical components and use of complex software entities to establish new network and systems capabilities. CPSs thus link physical and engineered systems and bridge the cyber world with the physical world. In contrast, IoT theory emerged from computer science and Internet technologies and focuses mainly on the interconnectivity, interoperability and integration of physical components on the Internet. With full IoT market adoption over the next decade, this integration work is anticipated to lead to developments such as IoT automation of CPSs [5,
* Petar Ra
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