Measuring and Protecting User Privacy
Members and Collaborators
User privacy is exposed to many risks, from unintentional and unwanted data sharing to data collection without user consent. Our research seeks to measure privacy risks and prevent them by developing better user control over their data
Critter@home is a project to connect researchers to
content-rich data from anonymous Internet end-users. Our goal is to
facilitate the safe sharing of data and provide a platform for end-users
to contribute data and be part of the research process.
Measuring Venmo Privacy Risks
Venmo online payment platform makes user data public by default. In this project we measured the risks this poses to users and how user behavior adapts to lower these risks.
Privacy-Safe Data Sharing
In this research we looked into privacy-safe data queries. Such queries are analyzed and data is aggregated to enforce strong k-anonymity.
- I know what you did on Venmo: Discovering privacy leaks in mobile social payments, Rajat Tandon, Pithayuth Charnsethikul, Ishank Arora, Dhiraj Murthy and Jelena Mirkovic, In Proceedings of Privacy Enhancing Technologies Symposium (PETS), 2022PDFBIB
- Samba: Identifying Inappropriate Videos for Young Children on YouTube, Le Binh, Rajat Tandon, Chingis Oinar, Jeffrey Liu, Uma Durairaj, Jiani Guo, Spencer Zahabizadeh, Sanjana Ilango, Jeremy Tang, Fred Morstatter, Simon Woo and Jelena Mirkovic, In Proceedings of 31st ACM International Conference on Information & Knowledge Management (CKIM), 2022PDFBIB
- Commoner Privacy And A Study On Network Traces, Xiyue Deng and Jelena Mirkovic, In Proceedings of the Annual Computer Security Applications Conference (ACSAC), 2017PDFBIB
- Critter: Content-Rich Traffic Trace Repository, V. Sharma, G. Bartlett and J. Mirkovic, In Proceedings of Workshop on Information Sharing and Collaborative Security (WISCS), 2014PDFBIB
This material is based upon work supported by the
National Science Foundation under grant #1319215 and #1815495, and by the Science and Technology Directorate of the United States Department of Homeland Security under contract number D15PC00184. Any opinions,
findings, and conclusions or recommendations expressed in this material are
those of the authors and do not necessarily reflect the views of the
National Science Foundation nor the Department of Homeland Security.