Stream Reasoning with Linked Data

Slides describing streaming data, data stream processing systems and stream reasoning Also we have some description of CSPARQL

INFO2009 2012-13 Resource Group 16 Cyber Security

This resource is an informational resource that attempts to inform the general public about security and privacy with using the internet.

INFO2009 2012-13 Resource Group 18 Animation Cyber Security

Resource and flyer produced for INFO2009 12/13. An animation on public-key encryption related to cybercrime and cybersecurity. Target audience is undergraduates, but the resource does not assume prior knowledge of the topics, or any in-depth knowledge of IT.

Why Cyber Security is Hard

Abstract There has been a great deal of interest in the area of cyber security in recent years. But what is cyber security exactly? And should society really care about it? We look at some of the challenges of being an academic working in the area of cyber security and explain why cyber security is, to put it rather simply, hard! Speaker Biography Keith Martin Prof. Keith Martin is Professor of Information Security at Royal Holloway, University of London. He received his BSc (Hons) in Mathematics from the University of Glasgow in 1988 and a PhD from Royal Holloway in 1991. Between 1992 and 1996 he held a Research Fellowship at the University of Adelaide, investigating mathematical modelling of cryptographic key distribution problems. In 1996 he joined the COSIC research group of the Katholieke Universiteit Leuven in Belgium, working on security for third generation mobile communications. Keith rejoined Royal Holloway in January 2000, became a Professor in Information Security in 2007 and was Director of the Information Security Group between 2010 and 2015. Keith's research interests range across cyber security, but with a focus on cryptographic applications. He is the author of 'Everyday Cryptography' published by Oxford University Press.

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.

COMP1205 2013-13 Student Presentations: Slot 2

Slides on presentations on the following topics: 2.1 Privacy and Security Legal overview, 2.2 Creative Commons open source, open movements 2.3 Crime online, Cyber security 2.4 Freedom of Speech and Defamation

INFO6003 (2013) Week 3

What is cyber security?

COMP1205 Student Presentations E-H

Monday 12th May Building 34 Room 3001, 12.00-13.45 Su & Rikki Presenting: Groups: E, F, G, H Marking Groups: I, J, K, L Schedule and Topics 12.00-12.05: Introduction and protocol for the session 12.05-12.25 Group E: Creative commons, open source, open movements 12.25-12.45 Group F: Trolling, Banter, Cyber Hate, Online Bullying 12.45-13.05 Group G: Personal Privacy and Security 13.05-13.25 Group H: Crime online; cyber security 13.25-13.45: Wash-up: feedback session for presentation groups

Data Science Seminar: Generic Big Data Processing for Advancing Situation Awareness and Decision-Support

The generation of heterogeneous big data sources with ever increasing volumes, velocities and veracities over the he last few years has inspired the data science and research community to address the challenge of extracting knowledge form big data. Such a wealth of generated data across the board can be intelligently exploited to advance our knowledge about our environment, public health, critical infrastructure and security. In recent years we have developed generic approaches to process such big data at multiple levels for advancing decision-support. It specifically concerns data processing with semantic harmonisation, low level fusion, analytics, knowledge modelling with high level fusion and reasoning. Such approaches will be introduced and presented in context of the TRIDEC project results on critical oil and gas industry drilling operations and also the ongoing large eVacuate project on critical crowd behaviour detection in confined spaces.