Defence against the dark artefacts: Smart home cybercrimes and cybersecurity standards

This paper analyses the assumptions underpinning a range of emerging EU and UK smart home cybersecurity standards. We use internet of things (IoT) case studies (such as the Mirai Botnet affair) and the criminological concept of 'routine activity theory' to situate our critique. Our study shows that current cybersecurity standards mainly assume smart home environments are (and will continue to be) underpinned by cloud architectures. This is a shortcoming in the longevity of standards. This paper argues that edge computing approaches, such as personal information management systems, are emerging for the IoT and challenge the cloud focused assumptions of these standards. In edge computing, data can be stored in a decentralised manner, locally and analysed on the client using federated learning. This can have advantages for security, privacy and legal compliance, over centralised cloud-based approaches, particularly around cross border data flows and edge based security analytics. As a consequence, standards should start to reflect the increased interest in this trend to make them more aspirational and responsive for the long term; as ultimately, current IoT architectures are a choice, as opposed to inherent. Our paper unpacks the importance of the adoption of edge computing models which could enable better management of external cyber-criminality threats in smart homes. We also briefly discuss challenges of building smart homes that can accommodate the complex nature of everyday life in the home. In addition to technical aspects, the social and interactional complexities of the home mean internal threats can also emerge. As these human factors remain unresolved in current approaches to smart home cybersecurity, a user's security can be impacted by such technical design choices. (c) 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ )