The IoT represents a convergence of ubiquitous computing and communication technologies, with emerging uses that actuate in the real world. No longer do ubiquitous computing systems simply sense and respond digitally, now they physically interact with the world, ultimately becoming embodied and autonomous. At the same time, the game is changing from one of privacy, where it is often (contestably) cited that "users don't care", to one of user safety, where users (along with regulators, governments, and other stakeholders) certainly do care. Likewise, industry needs to become aware that this shift also changes the legal basis under which companies need to operate, from one of disparate and often weakly enforced privacy laws, to one of product liability. The current widely adopted approach in which cloud services underpin IoT devices has already raised major privacy issues. Importantly in an actuated future, untrammelled communications implicating a plethora of heterogeneous online services in their normal operation also brings with it resilience challenges. We must ensure the integrity of actuating systems, which will require greater local autonomy alongside increased situated accountability to users. This problem applies in many areas: industrial control, autonomous vehicles, and smart cities and buildings, including the intimate and shared context of the home. This research seeks to address the challenge in the context of the home, where the network infrastructure protection is minimal, providing little or no isolation between attached devices and the traffic they carry. Scant attention has been paid by the research community to home network security, and its acceptability and usability, from the viewpoint of ordinary citizens. This research is also deeply rooted in pragmatism and recognises the 'real world, real time' conditions that attach to the IoT: - that the cyber security solutions currently being defined for IoT systems will not deal with legacy issues and will never achieve 100% adoption; - that extant businesses limit the period of time for which they will provide software and security updates (if they even remain in business); - that cyber security is an arms race and threats will continue to emerge in future; - and that the public will never become network security experts.

The long-term evolution of energy systems is set by the investment decisions of very many actors such as up-stream resource companies, power plant operators, network infrastructure providers, vehicle owners, transport system operators and building developers and occupiers. But these decisions are deliberately shaped by markets and incentives that have been designed by local and national governments to achieve policy objectives on energy, air-quality, economic growth and so on. It is clear then that government and businesses need detailed and dependable evidence of what can be achieved, what format of energy system we should aim for, what new technologies need to be encouraged, and how energy systems can form part of an industrial strategy to new goods and services. It is widely accepted that a whole-system view of energy is needed, covering not only multiple energy sectors (gas, heat, electricity and transport fuel) but also the behaviour of individuals and organisations within the energy consuming sectors such as transport and the built environment. This means that modelling energy production, delivery and use in a future integrated system is highly complex and analytically challenging. To provide evidence to government and business on what an optimised future system may look like, one has to rise to these modelling challenges. For electricity systems alone, there are established models that can optimise for security, cost and emissions given some assumptions (and sensitivities) and these have been used to provide policy and business strategy evidence. However, such models do not exist for the complex interactions of integrated systems and not at the level of fine detailed needed to expose particularly difficult operating conditions. Our vision is to tackle the very challenging modelling required for integrated energy systems by combining multi-physics optimising techno-economic models with machine learning of human behaviour and operational models emerging multi-carrier network and conversion technologies. The direction we wish to take is clear but there are many detailed challenges along the way for which highly innovative solutions will be needed to overcome the hurdles encountered. The programme grant structure enables us to assemble an exceptional team of experts across many disciplines. There are new and exciting opportunities, for instance, to apply machine learning to identify in a quantitative way models of consumer behaviour and responsiveness to incentives that can help explore demand-side flexibility within an integrated energy system. We have engaged four major partners from complementary sectors of the energy system that will support the programme with significant funding (approximately 35% additional funding) and more importantly engage with us and each other to share insights, challenges, data and case studies. EDF Energy provide the perspective on an energy retail business and access to smart meter trail data. Shell provide insights into the future fuels to be used in transport and building services. National Grid (System Operator) give the perspective of the use of flexibility and new service propositions for efficient system operations. ABB are a provider of data acquisition and control systems and provide industrial perspective of decentralisation of control. ABB have committed to providing substantial equipment and resource to build a verification and demonstration facility for decentralised control. We are also engaging examples of the new entrants, often smaller companies with potentially disruptive technologies and business models, who will engage and share some of their insights.

Internet eXchange Points (IXPs) have become a critical element of the Internet, as they provide the physical locations where networks interconnect and exchange traffic. IXPs carry huge traffic volumes, reduce interconnection costs, and hence make national Internet access affordable. Despite the growth of these infrastructures, the rapid evolution of the Internet poses new challenges. Reacting as soon as possible to the highly dynamic Internet environment has always been the first priority for Network Operators. Unfortunately, state-of-the-art techniques are extremely limited. Networks use the Border Gateway Protocol (BGP) to inform each other of which destinations are reachable. Accordingly, network operators (ab)use BGP Traffic Engineering (TE) to tweak traffic paths. TE is a network-management tool allowing a network to adapt events ranging from a change in customer location to mitigating dramatically large traffic outbursts of a malicious Distributed Denial of Service (DDoS) attack. However, BGP-TE lacks programmability and dynamism: once BGP preferences are set up, they cannot react in real-time to network events. With a high-fidelity measurement-focused approach, a network could implement more sophisticated traffic management techniques. For example, any network connected through an IXP must implement ingress traffic filtering to avoid receiving undesirable traffic (e.g., DDoS attacks or resulting from misconfigurations). However, correctly controlling ingress filters is complex. Thus, most IXP customers unrealistically expect the organisations originating the traffic to manage any problem. TE limitations result from the inability of current Internet monitoring techniques to cope with the wide range of granularities of network events. While control plane related events (those concerned with the selection of paths/routes, such as BGP updates) happen at a time scale of minutes, data plane events (packet processing) occur at time-scales of micro-seconds. While control plane monitoring is relatively easy, data plane observability is poor, relies on expensive equipment, and does not scale. EARL addresses this imbalance between the ability to observe control and data plane, and the consequent limits on the detection and reaction to network events. EARL is a novel integration of monitoring mechanisms and reactive network management. EARL enables a prompt reaction to network events with its Software Defined Networking (SDN) approach. Because of the IXP's central role on the Internet and the critical nature at the national level, we believe that they are the ideal place to explore EARL's ideas. We will demonstrate how measurement-assisted network management permits new Internet-wide services and, enables the provision of services hitherto considered impossible or too costly to deploy. Our goal for the EARL project is to pioneer SDN enabled measurement-based network management to enhance the Internet infrastructure. This will lead to relevant tools and data for the larger researcher and practitioner communities. To this aim, we will create a new research instrument, EARLnet: an operational, research-centered, Autonomous System (AS) directly connected to our partners, providing a new and unique real-world environment for the real-time monitoring of network status and SDN-oriented research. EARLnet will serve also as a test-bed to develop and evaluate novel reactive network management solutions. The EARL project has the potential to revolutionise current Internet network management through new fine-grained and reactive TE policies. EARL will not only create new mechanisms, but also translate the blind, legacy BGP-based, TE into measurement-assisted SDN techniques. Furthermore, through our partner institution, the Cambridge Cloud Cybercrime Centre (CCCC), EARLnet will provide valuable data to a large community of researchers and practitioners.

Circular approaches to design, manufacture and services are proposed as one of the most significant opportunities to radically re-think how we use and re-use finite resources. Pairing the digital revolution with the principles of a Circular Economy (CE) has the potential to radically transform the industrial landscape and its relationship to materials and finite resources, thus unlocking additional value for the manufacturing sector. Despite meaningful success by a handful of manufacturers to move towards more sustainable practices through the use of data-driven intelligence, it is unclear which CE strategy is the most valuable for a business and at what time in a products lifecycle it should be implemented. As such, this research aims to identify how data from products in use can inform intelligent decisions surrounding the implementation of Circular Economy strategies so as to accelerate the implementation of circular approaches to resource use within UK manufacturing. Multiple research efforts and best practice examples have shown that a transition towards a Circular Economy can bring about lasting benefits from a more innovative, resilient and productive economy. This is particularly prevalent for manufacturing as it offers one of the biggest potentials for economic and environmental impact of any sector. It is estimated that materials savings alone in the European Union could amount to USD 630 billion. Digital technology is rapidly becoming a key enabler for unlocking the value from Circular Economy strategies with an estimated 10 billion physical objects with embedded information technology already in existence today and a predicted 50 billion in use by 2020. For the manufacturing sector, the ability to monitor and manage objects in the physical world electronically through data-driven decision-making changes the way that value is created. The capture and analysis of data streams between manufacturing, product and user is already enabling organisations to decouple manufacturing growth from resource consumption through new service offerings, providing customers with added value such as financial savings and safety improvement, and enabling organisations to shift their business model from selling to leasing. This shift in ownership, enabled through access to the right data, brings about a need for manufacturers to design products that last and to integrate processes such as remanufacturing to enable materials and resources to be cycled as many times as possible resulting in significant environmental savings, job creation and up-skilling associated with the development of new processes. Through harnessing digital technological advances to inform decisions on Circular Economy strategies, this research has the opportunity to radically transform UK manufacturing and enable the sector to capture significant value from a Circular Economy that is currently being lost. The originality of this research lies in using data-driven intelligence to optimise the selection of CE strategies for products and the timings of intervention in the product lifecycle. This challenging three year project will bring together an internationally renowned team of experts in Circular Innovation, Manufacturing Informatics and Information Theory from Cranfield University and University of Sheffield drawing on leading-edge strengths of the host institutions and international connections with research communities, companies, business intermediaries and governance at national and international scales. The research team will partner with key players across the manufacturing sector, capable of initiating system level change, to develop novel methods for acquiring and integrating new data streams, uncovering exciting opportunities for new value creation within manufacturing organisations and enabling informed circular interventions surrounding the manufacture and use of products.

Recent reports from the Royal Society, the government Cybersecurity strategy, as well as the National Cyber Security Center highlight the importance of cybersecurity, in ensuring a safe information society. They highlight the challenges faced by the UK in this domain, and in particular the challenges this field poses: from a need for multi-disciplinary expertise and work to address complex challenges, that span from high-level policy to detailed engineering; to the need for an integrated approach between government initiatives, private industry initiatives and wider civil society to tackle both cybercrime and nation state interference into national infrastructures, from power grids to election systems. They conclude that expertise is lacking, particularly when it comes to multi-disciplinary experts with good understanding of effective work both in government and industry. The EPSRC Doctoral Training Center in Cybersecurity addresses this challenge, and aims to train multidisciplinary experts in engineering secure IT systems, tacking and interdicting cybercrime and formulating effective public policy interventions in this domain. The training provided provides expertise in all those areas through a combination of taught modules, and training in conducting original world-class research in those fields. Graduates will be domain experts in more than one of the subfields of cybersecurity, namely Human, Organizational and Regulatory aspects; Attacks, Defences and Cybercrime; Systems security and Cryptography; Program, Software and Platform Security and Infrastructure Security. They will receive training in using techniques from computing, social sciences, crime science and public policy to find appropriate solutions to problems within those domains. Further, they will be trained in responsible research and innovation to ensure both research, but also technology transfer and policy interventions are protective of people's rights, are compatible with democratic institutions, and improve the welfare of the public. Through a program of industrial internships all doctoral students will familiarize themselves with the technologies, polices and also challenges faced by real-world organizations, large and small, trying to tackle cybersecurity challenges. Therefore they will be equipped to assume leadership positions to solve those problems upon graduation.