Securing IoT Applications with Smart Objects: Framework and a Socially Assistive Robots Case Study
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Securing IoT Applications with Smart Objects: Framework and a Socially Assistive Robots Case Study John Soldatos1 · Sofoklis Kyriazakos2 · Pouyan Ziafati3 · Albena Mihovska4
© Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract The expanded deployment of smart objects in IoT applications is pushing existing IoT platform architectures and their security functionalities to their limits. Indeed, smart objects exhibit semi-autonomous behaviours, are not centrally controlled all the time and therefore need more dynamic approaches in protecting them against vulnerabilities and security incidents. In this paper, we introduce a novel framework for securing the latest generation of IoT applications that involve smart objects, while illustrating its application in securing an Ambient Assisted Living (AAL) system that comprises socially assistive robots. The framework’s innovative aspects lie in the use of predictive analytics for anticipating the behaviour of smart objects, including abnormalities in their security behaviour. The importance of anticipating such abnormalities is validated, demonstrated and discussed in the context of the AAL application. Keywords Internet of things · IoT · Security · Cybersecurity · Smart objects · Robots · AAL · Ambient assisted living · Socially assisted robots · Healthcare
1 Introduction In recent years the world has witnessed several notorious security incidents on IoT devices and applications, such as the “Lizard Stressor” attacks on home routers in January 2015, the 1.4 million cars that were recalled by Chrysler due to potential hacking of their control software in July 2015, Tesla’s autopilot crash in July 2016, as well as “Mirai”, the first large scale distributed denial of service (DDoS) attack based on IoT devices that took place in October 2016. These incidents have indicated the vulnerability of emerging IoT infrastructures, while at the same time highlighting the tremendous socio-economic importance of IoT security. * John Soldatos [email protected] 1
Athens Information Technology, Athens, Greece
2
Innovation Sprint Sprl, Brussels, Belgium
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LuxAI S.A Luxembourg, Luxembourg City, Luxembourg
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Aarhus University, Aarhus, Denmark
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The rising number of IoT-related cyber-security incidents is not only due to the proliferation of internet-connect devices, but also to their increasing complexity [1]. Modern IoT systems and deployments are more complex and sophisticated than ever before. In particular, for over a decade, IoT platform architectures and their applications have been focused on integrating a very large number of IoT devices and their data streams in the cloud [2]. More recently, IoT architectures and applications are increasingly comprising smart objects i.e. objects with semi-autonomous behaviours, such as drones, robots, autonomous guided vehicles, self-driving cars and more. The integration of smart objects within IoT applications opens up new opportunities for cyber-crime and renders IoT sec
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