1.6k citations · 2.1k across the 35 of their papers we have counts for
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Leveraging Prior Knowledge Asymmetries in the Design of Location Privacy-Preserving Mechanisms
Nazanin Takbiri, Virat Shejwalker, Amir Houmansadr +2
The prevalence of mobile devices and Location-Based Services (LBS) necessitate the study of Location Privacy-Preserving Mechanisms (LPPM). However, LPPMs reduce the utility of LBS…
Asymptotic Limits of Privacy in Bayesian Time Series Matching
Nazanin Takbiri, Dennis L. Goeckel, Amir Houmansadr +1
Various modern and highly popular applications make use of user data traces in order to offer specific services, often for the purpose of improving the user's experience while usin…
Asymptotic Loss in Privacy due to Dependency in Gaussian Traces
Nazanin Takbiri, Ramin Soltani, Dennis L. Goeckel +2
The rapid growth of the Internet of Things (IoT) necessitates employing privacy-preserving techniques to protect users' sensitive information. Even when user traces are anonymized,…
Privacy against Statistical Matching: Inter-User Correlation
Nazanin Takbiri, Amir Houmansadr, Dennis L. Goeckel +1
Modern applications significantly enhance user experience by adapting to each user's individual condition and/or preferences. While this adaptation can greatly improve utility or b…
Privacy of Dependent Users Against Statistical Matching
Nazanin Takbiri, Amir Houmansadr, Dennis L. Goeckel +1
Modern applications significantly enhance user experience by adapting to each user's individual condition and/or preferences. While this adaptation can greatly improve a user's exp…
Matching Anonymized and Obfuscated Time Series to Users' Profiles
Nazanin Takbiri, Amir Houmansadr, Dennis L. Goeckel +1
Many popular applications use traces of user data to offer various services to their users. However, even if user data is anonymized and obfuscated, a user's privacy can be comprom…