What is Cybercrime and what do we do about?

A guest lecture by Professor David S.Wall from the University of Durham. This talk will explore the way that networked technology has transformed criminal behaviour. The first part will map out cybercrimes and identify the challenges they pose for both criminologists and also regulators. The second part will show that cybercrimes are informational, networked and global. In this section it will also be shown that cybercrimes are highly disorganised forms of offending when compared to the organisation of more 'traditional' crimes, but display some new organisational logics of their own. The third part of the talk will illustrate how the 'culture of fear' that has arisen around cybercrime has placed demands upon government and police - demands that, for reasons related to the distinct nature of cybercrimes, are hard to resolve. The fourth and final part will look at the new policing arrangements that are designed, it is argued here, to close the reassurance gap.

Data Science Seminar: The data science revolution in Physics and Astronomy

Abstract Heading into the 2020s, Physics and Astronomy are undergoing experimental revolutions that will reshape our picture of the fabric of the Universe. The Large Hadron Collider (LHC), the largest particle physics project in the world, produces 30 petabytes of data annually that need to be sifted through, analysed, and modelled. In astrophysics, the Large Synoptic Survey Telescope (LSST) will be taking a high-resolution image of the full sky every 3 days, leading to data rates of 30 terabytes per night over ten years. These experiments endeavour to answer the question why 96% of the content of the universe currently elude our physical understanding. Both the LHC and LSST share the 5-dimensional nature of their data, with position, energy and time being the fundamental axes. This talk will present an overview of the experiments and data that is gathered, and outlines the challenges in extracting information. Common strategies employed are very similar to industrial data! Science problems (e.g., data filtering, machine learning, statistical interpretation) and provide a seed for exchange of knowledge between academia and industry. Speaker Biography Professor Mark Sullivan Mark Sullivan is a Professor of Astrophysics in the Department of Physics and Astronomy. Mark completed his PhD at Cambridge, and following postdoctoral study in Durham, Toronto and Oxford, now leads a research group at Southampton studying dark energy using exploding stars called "type Ia supernovae". Mark has many years' experience of research that involves repeatedly imaging the night sky to track the arrival of transient objects, involving significant challenges in data handling, processing, classification and analysis.