
Criminal use of the national network infrastructure is commonplace: blackmail, and phishing (social engineering) alone are significant in economic terms. These activities exploit network hosts that have been previously subverted, by attacks that are becoming increasingly sophisticated. Existing Intrusion Detection Systems (IDSs) are unable to detect new or subtle attacks, and deploying IDS sensors in higher volumes results in high report volumes, but little more effectiveness. This project will show that by taking a system design approach to the choice and configuration of sensors, together with network deployment strategies that allow flexible sensor placement, it is possible to substantially improve the detection of subtle attacks. This work does not focus on improvements to individual intrusion detection components; but rather exploits the synergy that can be obtained by combining the strengths of different types of sensor, in a holistic approach to intrusion management design.
The financial services industry is at the forefront of the digital economy, and is crucial to the UK's, and especially London's, continuing social and economic prosperity. State-of-the-art Financial IT, Computational Finance and Financial Engineering (collectively Financial Computing) research is crucial to our international competitiveness in investment banking, investment funds or retail banking. Academically this DTC focuses on financial computing, as distinct from quantitative finance, already well resourced. Banks and funds view PhD students in science and engineering as an increasingly important and largely untapped talent pool; although one regrettably with little knowledge of finance. The Financial Services Skills Council notes that employers are placing increasing importance on high-level analytical skills, as well as their acute shortage, especially in the newly emerging areas that drive sector growth. This centre completely embraces the spirit of the Digital Economy programme. The proposed DTC is inherently multidisciplinary involving UCL Computer Science, one of the largest leading departments in its field in the UK, with LSE Finance and the London Business School; the two leading academic finance centres in the UK. Key to developing the financial services industry in the Digital Economy is the creation of a new cohort of researchers who have a strong research capability in IT and computation, but also understand finance and the needs of the wholesale financial services industry leading to early adoption of new financial information technology research.The research groups and centres that will participate in this DTC include worldclass groups at: UCL, such as the Software Systems Engineering Group and the Centre for Computational Statistics and Machine Learning, at LSE such as Financial Markets Group, and at the London Business School, including the Management Science and Operations and Finance Subject Areas. The total value of active grants currently held by the participating groups and centres exceeds 20 Million Pounds, and the number of currently registered PhD students exceeds 130. Collaborators in Statistics, Economics, Mathematics and Physics supplement the potential Supervisor pool.A great strength of this DTC proposal is our industry partners, which include: Abbey, Barclays, Barclays Capital, BNP Paribas, Credit Suisse, Deutsche Bank, Goldman Sachs, HSBC, Lloyds TSB, Man Investments, Merrill Lynch, Morgan Stanley, Nomura, RBS and Thomson Reuters. Regarding training and supervision, each DTC PhD student will follow a personally tailored programme of postgraduate courses drawn from the partners covering financial IT, networks & communications, HCI, computational finance, financial engineering and business, supplemented by lectures from our industry partners: * A tailored educational programme comprising graduate-level courses from UCL, LSE and LBS. * An academic supervisor (from UCL, LSE or LBS) and an industrial advisor (a partner bank, fund or Reuters), and a programme of research covered by an MOU. * A research project in financial IT, computational finance or financial engineering. * Training in industry software, such as Reuters 3000 Xtra, through UCL's virtual training floor.* A substantial period of industrial placement as agreed between the academic and industrial supervisors.* A short period at a leading foreign academic centre
Criminal use of the national network infrastructure is commonplace: blackmail, and phishing (social engineering) alone are significant in economic terms. These activities exploit network hosts that have been previously subverted, by attacks that are becoming increasingly sophisticated. Existing Intrusion Detection Systems (IDSs) are unable to detect new or subtle attacks, and deploying IDS sensors in higher volumes results in high report volumes, but little more effectiveness. This project will show that by taking a system design approach to the choice and configuration of sensors, together with network deployment strategies that allow flexible sensor placement, it is possible to substantially improve the detection of subtle attacks. This work does not focus on improvements to individual intrusion detection components; but rather exploits the synergy that can be obtained by combining the strengths of different types of sensor, in a holistic approach to intrusion management design.
Climate and environmental (CE) risks (CER) to our economy and society are accelerating. CER include climate-related physical risks such as floods, storms, or changing growing seasons; climate-related transition risks such as carbon pricing and climate litigation; and environmental risks such as biodiversity loss. It is now well accepted that CER can impact asset values across multiple sectors and pose a threat to the solvency of financial institutions (FIs). This can cause cascading effects with the potential to undermine financial stability. The adoption of CER analytics will ensure that CE risks can be properly measured, priced, and managed by individual FIs and across the financial system. This is also a necessary condition to ensure that capital is allocated by FIs towards technologies, infrastructure, and business models that lower CER, which are also those required to deliver the net zero carbon transition, climate resilience, and sustainable development. These twin tracks - greening finance and financing green - are both enabled by CER analytics being appropriately used by FIs. The UK is a world-leader in Green Finance (GF). UK FIs have played a key role in GF innovation. Yet, despite these advances and leadership in almost every aspect of GF, UK FIs cannot secure the data and analytics needed to properly measure and manage their exposures to CER. While the last decade has seen the exponential growth of CE data, as well as improved analytics and methods, often produced by world-leading UK science, the vast majority of this has not found its way into FI decision-making. Our vision for CERAF is to establish a new national centre to resolve this disconnect. CERAF aims to enable a step-change in the provision and accessibility of data, analytics, and guidance and accelerate the integration of CER into products and decisions by FIs to manage CER risks and drive efficient and sustainable investment decisions, thereby delivering the following impacts: - Enhance the solvency of individual FIs in the UK and globally and so contribute to the resilience of the global financial system as a whole for all, as well the efficient pricing and reallocation of capital away from assets at risk to those that are more resilient. - Underpin the development and the growth of UK GF-related products and services. - Enable a vibrant ecosystem of UK enterprises providing CER analytics and realise the opportunity for UK plc of being a world-leader in the creation and provision of CER services. Our vision is that CERAF will be the nucleus of a new national centre established to deliver world-leading research, information, and innovation to systematically accelerate the adoption and use of CER data and analytics by FIs and to unlock opportunities for the UK to lead internationally in delivering CER services to support advancements in greening finance and financing green globally It aims to overcome the following barriers: 1) Making existing data on hazards, vulnerabilities, and exposures more accessible and useable for FIs, with clearly communicated confidence and with analytics that does not yet exist being secured; 2) Consistency and standards to reduce fragmentation, facilitate innovative products and enable the efficient flow and use of data; 3) Assurance and suitability are needed to understand which CER analytics are best suited for particular uses and provide transparency into underlying data and methodologies, so that CER analytics can be trusted and used; 4) Unlocking innovation through supporting FIs to test new approaches in a lower-risk way; and 5) Building capability, knowledge, and skills within FIs to analyse and interpret CER data. Resolving these barriers is a necessary condition for repricing capital and avoiding its misallocation, and achieving the UK's ambitions on GF.