IDC Seminar – Interactive Visualisation of Semantic Patterns in Passwords

IDC Seminar – Interactive Visualisation of Semantic Patterns in Passwords

Interactive Visualisation of Semantic Patterns in Passwords

Room C218

Dr Shujun Li and Ms Stephanie Schmid

Abstract: We propose a visual approach to explore and analyse the use of passwords. It is designed to 1) educate users to use stronger passwords for authentication and 2) help security experts develop useful password policies. The basis of our work is a tool implemented at the University of Surrey in 2016. It was improved during the project focusing on visual aspects. A live demo of the current version will be used to illustrate the advantages of visual exploration in the field of password analysis. With the aid of use cases covering recently leaked password lists, the features of the tool will be explained and new data exploration possibilities shown. Both results and limitations (incl. Ideas and future work) will be shown and discussed. We will also illustrate how the integration of higher semantics in passwords could improve our work. For that, we will discuss some recent related work and show how this could be used in the tool.


Dr. Shujun Li will join the University of Kent later in 2017 as a Professor of Cyber Security and Director of its Interdisciplinary Research Centre in Cyber Security. He is currently a Reader (Associate Professor) at the Department of Computer Science, University of Surrey, and has been a Deputy Director of the Surrey Centre for Cyber Security (SCCS) since July 2014. SCCS has been a UK government recognized Academic Centre of Excellence in Cyber Security Research (ACE-CSR) since 2015 and its status has been recently re-recognised until 2022. Dr Li’s research interests are mostly around interdisciplinary topics covering cyber security, digital forensics and cybercrime, human factors and human-centric computing, multimedia computing and information and information visualization, and applications of artificial intelligence and discrete optimization.

Stefanie Schmid is a student associate at the Department for Data Analysis and Visualization of Prof. Daniel Keim at the University of Konstanz In 2013, she received a BSc. degree in Information-oriented Business Administration from the University of Augsburg, where she focused on Statistics and Data Analysis. Subsequently, she studied Information Engineering at the University of Konstanz and finished with a BSc. Degree in 03/2017. Her research interests are in data analysis, data visualisation, visual analytics and exploration of high dimensional data.


Simon Attfield

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