Abstract
Large-scale password data breaches are becoming increasingly commonplace, which has enabled researchers to produce a substantial body of password security research utilising real-world password datasets, which often contain numbers of records in the tens or even hundreds of millions. While much study has been conducted on how password composition policies—sets of rules that a user must abide by when creating a password—influence the distribution of user-chosen passwords on a system, much less research has been done on inferring the password composition policy that a given set of user-chosen passwords was created under. In this paper, we state the problem with the naive approach to this challenge, and suggest a simple approach that produces more reliable results. We also present pol-infer, a tool that implements this approach, and demonstrates its use in inferring password composition policies.
Alexandra Mendes
Assistant Professor
My research focuses on encouraging a wider adoption of software verification by creating tools and methods that hide the complexities of verifying software. Recently, I started work on usable security, in particular on the impact of formal verification on the use and adoption of formally verified security software products. Much of my most recent work overlaps with the area of software engineering. For more details, see selected publications and some of my projects. Follow me on Twitter or add me on LinkedIn.