Recent trends in authentication research suggest that improved feedback and interaction can help users make more secure and memorable choices. In this presentation I will review methods such as persuasive passwords, and provide a sneak peek at some of my own research into social authentication.

The analysis of social and technological networks has attracted a lot of attention as social networking applications and mobile sensing devices have given us a wealth of real data. Classic studies looked at analysing static or aggregated networks, i.e., networks that do not change over time or built as the result of aggregation of information over a certain period of time. Given the soaring number of collections of measurements related to very large real network traces, researchers are quickly starting to realise that connections are inherently varying over time and exhibit more dimensionality than static analysis can capture. In this talk I will present a novel theoretical framework to quantify and compare the speed (delay) of information diffusion processes in dynamic networks. We show how these metrics are able to capture the temporal characteristics of time-varying graphs, such as delay, duration and time order of contacts (interactions), compared to the metrics used in the past on static graphs. I will also discuss the extension of centrality metrics to temporal graphs and some results about small-world properties of time-varying networks.