SuperIdentity: Fusion of cues across online and offline contexts Sarah Stevenage (University of Southampton)

Users and Visualisation Modelling Forensic Identification Automated Identification Social Acceptability, Feedback and Trust Personality and CyberBehaviour Legal Reform Our SID Team

3 Represent Identity Real World Digital World (biometrics) (cybermetrics) BehaveDeceive

4 SuperIdentity – Who are you? We intentionally reveal, and unintentionally leak identity information in many ways Confidence in Biometric and Cybermetric recognition Linkage across identity metrics

5 1.Use Cases (US and UK) 2.Intelligence and Service Providers 3.Evident wisdom and case lore 4.Systematic experimentation Guiding Principles Security

6 Biographic Cybermetric Biometric Personality Generating Links; Making Predictions Body modifications Password riskiness Hand geometry

7 Visualisation 7 Discovery with ArcWeld If all identity data were available, transitions could be welded to discover patterns and build several rich super identities. Goal-oriented Identity Attribution with Identity Path This would allow users to define their start and end element attributes in order to vet and assert confidence of certain paths of identity attribution. Researcher view of the model with Green Hornet A graph visualization tool could enable identification of gaps or “islands, and to identify ‘centrality’ etc. 7

8 Visualisation: ArcWeld 8 8

9 Visualisation: Identity Path 9

10 Visualisation: Green Hornet 10

11 Impact Journal Publications: 7 journal papers in print/press, 1 submitted, several in prep Conference Presentations/Workshops: 9 national/international presentations Keynotes and Invited addresses Outreach: Science Centres (Bath, Hampshire, Glasgow) Big Bang (London, Glasgow) Forensic Expo Social Acceptability Workshops Schools and Colleges Dissemination to Key Parties: IBM, dstl, GCHQ, Biometrics Institute, CEOP, Forensic Science Society, Future of Identity Network, SOCA,

12 Open to ideas…