PETRAS projects are organised within a matrix of ‘sectors’ and ‘lenses’ that help to define research challenges in a real-world context.
The Centre’s Lenses are research challenge domains: Securing the Edge; Useful, Usable Decentralisation; Law and Economics at the Edge; and Building Public Value at the Edge.
The Sectors have specific application-focussed contexts in terms of technology, regulation, economics, interventions, and innovation: Ambient Environments; Supply Chains and Control Systems; Infrastructure; Health and Wellbeing; Agritech; and Transport and Mobility.
Lenses and Sectors are units of synthesis of findings, points of contact for accessing the Centre’s programme and expertise, as well as special interest groups.
Each project is associated with at least one challenge and applies its findings in at least one sector.
The world of IoT can be considered under sectors of application. This brings new technologies, standardisation and regulatory contexts to each sector.
Ambient Environments (Built Environment / Homes / Cities / Public Spaces)
Cities, neighbourhoods, homes, and the environment in which we live are affected by the integration of IoT and ‘Edge’ technologies. This sector looks at how the IoT may affect our everyday experience of the world around us. It will study how our private spaces and privacy can be maintained in an environment where, increasingly, information is being captured and shared. Research in this application area will look at a cross section of settings, including retail, leisure, work and home.
Examples:
Supply Chains and Control Systems (Industrial / Buildings / Utilities)
The focus of this sector is the use of IoT devices and networks within the supply chain and in control systems. From a supply chain perspective, the IoT solution may involve passive devices (e.g. RFID tags) attached to an object, or small low power devices to enable tracking and traceability within a factory. The control systems applications range across buildings (BMS) to industrial (ICS) or transport systems and potentially involve the use of IoT sensors to monitor performance, track objects or provide data. Research in this sector aims to explore security issues, of the controlled system, the device and the data it provides, and the application architecture.
Examples:
Agritech
The UK produces less than half of the food it consumes and relies on produce being readily available. It is important to ensure that food security is not impacted by cyber-attacks on the surrounding infrastructure, processes, sensors or Edge computing used in agriculture and farming. Previous focus has been on avoiding attacks on the administrative side of food production, rather than anticipating system disruption and failure as a result of attacks in sensor networks and Edge devices. This sector will look at exploring vulnerabilities in currently deployed Agritech.
Examples:
Health and Wellbeing (Critical care to leisure wearables)
This theme focuses on the challenges around IoT in the health care and wellbeing sectors. This may include diagnostic and monitoring sensors for identifying chronic diseases such as diabetes, also wellbeing enabling devices. Specific focus will be placed on the security of wireless technologies within wearable and implantable devices, addressing ethics, privacy, adoption and usage of medical information.
Examples:
Infrastructure (Critical infrastructure and digital infrastructure)
Critical infrastructures include systems that are essential for the functioning of society and the economy.
Examples:
Digital Infrastructures
Critical Infrastructures
Transport and Mobility
There has been a great push for smarter, connected transport and mobility. IoT can enhance typical single mode transport systems to create new reactive models for multi-mode transport. However new systems and models face significant challenges if they are to be of maximum benefit. They need to manage mobile identity while protecting privacy, and to be flexible but resilient, secure and safe. This includes all aspects cyber, physical and their interfaces.
Examples:
The Lens programme provides a cross-cutting set of research headings that pull together common and generic themes that apply across one or more sectors. Such generic learning has the potential to assist government and the private sector in the creation of policies and best practices.
Securing the Connected Edge
This Lens looks at challenges stemming from the cyber-physical and socio-technical nature of systems at the Edge. The role of AI at the Edge may be fundamental in securing systems. Use of IoT increases attack surfaces, requiring systems to detect, diagnose and react to potential attacks. Edge AI can enable systems to react to perceived threats as well as to make decisions on interventions using trade-offs (e.g. between safety and security). This Lens involves research on characterising vulnerabilities at the Edge, improving resilience, and understanding trade-offs.
Examples:
Public Value at the Edge
Connected IoT devices provide many avenues for public good, including increased understanding of the world to support policy interventions; new innovative goods and services; and information to help safeguard individuals.
Many of these benefits will come from the combination of IoT with AI. New challenges are expected in processing the data at the Edge in ways that preserve privacy, security and trust yet yield the same benefits.
Examples:
Useful and Useable Decentralisation
There is a gap between autonomy on paper that decentralised systems promise to Edge-users, and the control that Edge users feel capable and able to exert, particularly given the number of decisions they are expected to make in this data-saturated world. Research in psychology and human-computer interaction is needed to identify how decentralised systems can be useful and useable in practice, rather than only in theory. This in turn is likely to trigger new questions for security researchers, for example in areas such as identification and interoperability.
Examples:
Law and Economics at the Edge
Business and governance models for IoT systems, particularly those undertaking decentralised analytics, are still emerging.
Examples: