On Designing Social Norm-Grounded Privacy Preserving Systems
Today, data privacy (collection, storage, sharing, and processing of personal data) is often highlighted in public discourse with the advent of a multitude of recent government-mandated privacy regulations like GDPR and CCPA. To that end, in this talk, I will discuss our current and ongoing body of work on creating social norm-grounded privacy-preserving systems—systems that help to align the collection, sharing, or storage of large-scale personal user data in online systems with rules collectively created by groups of users in particular and society in general. I will give an overview of our recently published work in this space and focus on use cases ranging from secure financial technology to cultural norms of social data sharing. I will conclude this talk by touching on our general research agenda of understanding, designing, and building human-in-the-loop, private, secure, and abuse-free systems.
For remote participation link, email us at <trustlab.office@cse.iitb.ac.in>
Speaker Biography
Dr. Mainack Mondal is an Assistant Professor of Computer Science at IIT Kharagpur. He completed his Ph.D. from the Max Planck Institute for Software Systems (MPI-SWS), Germany, in 2017. Prior to joining IIT Kharagpur, he was a postdoctoral researcher at the University of Chicago and Cornell Tech. Mainack is broadly interested in incorporating human factors into security and privacy and consequently designing usable online services. Specifically, he works on developing systems that provide usable privacy and security mechanisms to online users while minimizing system abuse. His work has led to papers in Usenix Security, ACM’s CCS, NDSS, AsiaCCS, PETS, AAAI’s ICWSM, Usenix’s SOUPS, ACM’s CSCW, ACM’s CoNExt and Usenix’s EuroSys among others. His work also received distinguished paper award in Usenix’s SOUPS, Google India faculty research award in 2022 and IITB Trust Lab Early Career Award in 2023.
