Visible to the public Biblio

Filters: Author is Maple, C.  [Clear All Filters]
2021-02-16
Mace, J. C., Czekster, R. Melo, Morisset, C., Maple, C..  2020.  Smart Building Risk Assessment Case Study: Challenges, Deficiencies and Recommendations. 2020 16th European Dependable Computing Conference (EDCC). :59—64.
Inter-networked control systems make smart buildings increasingly efficient but can lead to severe operational disruptions and infrastructure damage. It is vital the security state of smart buildings is properly assessed so that thorough and cost effective risk management can be established. This paper uniquely reports on an actual risk assessment performed in 2018 on one of the world's most densely monitored, state-of-the-art, smart buildings. From our observations, we suggest that current practice may be inadequate due to a number of challenges and deficiencies, including the lack of a recognised smart building risk assessment methodology. As a result, the security posture of many smart buildings may not be as robust as their risk assessments suggest. Crucially, we highlight a number of key recommendations for a more comprehensive risk assessment process for smart buildings. As a whole, we believe this practical experience report will be of interest to a range of smart building stakeholders.
2020-07-16
Mace, J.C., Morisset, C., Pierce, K., Gamble, C., Maple, C., Fitzgerald, J..  2018.  A multi-modelling based approach to assessing the security of smart buildings. Living in the Internet of Things: Cybersecurity of the IoT – 2018. :1—10.

Smart buildings are controlled by multiple cyber-physical systems that provide critical services such as heating, ventilation, lighting and access control. These building systems are becoming increasingly vulnerable to both cyber and physical attacks. We introduce a multi-model methodology for assessing the security of these systems, which utilises INTO-CPS, a suite of modelling, simulation, and analysis tools for designing cyber-physical systems. Using a fan coil unit case study we show how its security can be systematically assessed when subjected to Man-in-the-Middle attacks on the data connections between system components. We suggest our methodology would enable building managers and security engineers to design attack countermeasures and refine their effectiveness.

2019-02-08
Ghirardello, K., Maple, C., Ng, D., Kearney, P..  2018.  Cyber Security of Smart Homes: Development of a Reference Architecture for Attack Surface Analysis. Living in the Internet of Things: Cybersecurity of the IoT - 2018. :1-10.

Recent advances in pervasive computing have caused a rapid growth of the Smart Home market, where a number of otherwise mundane pieces of technology are capable of connecting to the Internet and interacting with other similar devices. However, with the lack of a commonly adopted set of guidelines, several IT companies are producing smart devices with their own proprietary standards, leading to highly heterogeneous Smart Home systems in which the interoperability of the present elements is not always implemented in the most straightforward manner. As such, understanding the cyber risk of these cyber-physical systems beyond the individual devices has become an almost intractable problem. This paper tackles this issue by introducing a Smart Home reference architecture which facilitates security analysis. Being composed by three viewpoints, it gives a high-level description of the various functions and components needed in a domestic IoT device and network. Furthermore, this document demonstrates how the architecture can be used to determine the various attack surfaces of a home automation system from which its key vulnerabilities can be determined.

2018-11-14
Wakenshaw, S. Y. L., Maple, C., Schraefel, M. C., Gomer, R., Ghirardello, K..  2018.  Mechanisms for Meaningful Consent in Internet of Things. Living in the Internet of Things: Cybersecurity of the IoT - 2018. :1–10.

Consent is a key measure for privacy protection and needs to be `meaningful' to give people informational power. It is increasingly important that individuals are provided with real choices and are empowered to negotiate for meaningful consent. Meaningful consent is an important area for consideration in IoT systems since privacy is a significant factor impacting on adoption of IoT. Obtaining meaningful consent is becoming increasingly challenging in IoT environments. It is proposed that an ``apparency, pragmatic/semantic transparency model'' adopted for data management could make consent more meaningful, that is, visible, controllable and understandable. The model has illustrated the why and what issues regarding data management for potential meaningful consent [1]. In this paper, we focus on the `how' issue, i.e. how to implement the model in IoT systems. We discuss apparency by focusing on the interactions and data actions in the IoT system; pragmatic transparency by centring on the privacy risks, threats of data actions; and semantic transparency by focusing on the terms and language used by individuals and the experts. We believe that our discussion would elicit more research on the apparency model' in IoT for meaningful consent.