8 papers
Superstring-Based Sequence Obfuscation to Thwart Pattern Matching Attacks
Bo Guan, Nazanin Takbiri, Dennis Goeckel +2
User privacy can be compromised by matching user data traces to records of their previous behavior. The matching of the statistical characteristics of traces to prior user behavior…
Asymptotic Privacy Loss due to Time Series Matching of Dependent Users
Nazanin Takbiri, Minting Chen, Dennis L. Goeckel +2
The Internet of Things (IoT) promises to improve user utility by tuning applications to user behavior, but revealing the characteristics of a user's behavior presents a significant…
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…
Improving Privacy in Graphs Through Node Addition
Nazanin Takbiri, Xiaozhe Shao, Lixin Gao +1
The rapid growth of computer systems which generate graph data necessitates employing privacy-preserving mechanisms to protect users' identity. Since structure-based de-anonymizati…
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,…