Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 14 of 14 for “"Privacy and Utility"”.
-
Statistical learning with differential privacy
… growth of data, the preservation of individual privacy has become a prominent challenge in data-driven decision-making across diverse domains. The concept of differential privacy, a robust mathematical framework, has emerged as the gold standard for providing rigorous data privacy protections. …
-
Stable Privacy Parameter Settings Using Game Theory
Privacy protection appears as a fundamental concern when personal data is collected, stored, and published. Several privacy protection methods have been proposed to address privacy issues in private datasets. Each method has at least one parameter to adjust the guaranteed level of privacy …
-
Random Sequential Encoders for Private Data Release in NLP
… to guarantee while maintaining the model utility of said task. In computer vision, lightweight random convolutional networks have shown potential to be an encoder that balances privacy and utility. This thesis takes a novel exploration of random sequential encoders - (1) random recurrent …
-
Neural Data Shaping and Evaluation via Mutual Information Estimation
… the scarcity of data that is publicly available. Privacy protection regulations such as HIPAA and GDPR and recent progress in information estimation literature motivate us to investigate the issue from an information theoretic perspective. In this thesis, we propose InfoShape, an encoder training …
-
Privacy-Preserving Video Analytics
… cameras have become pervasive in public settings and accurate computer vision has become commonplace, there has been increasing interest in collecting and processing data from these cameras at scale ("video analytics"). While these trends enable many useful applications (such as monitoring the …
-
Non-Metric Multi-Dimensional Scaling for Distance-Based Privacy-Preserving Data Mining
… of data mining have led to major concerns about privacy. Sharing data with external parties for analysis puts private information at risk. The original data are often perturbed before external release to protect private information. However, data perturbation can decrease the utility of the …
-
Analysis of Privacy-aware Data Sharing in Cyber-physical Energy Systems
In this thesis, we determine the key factors and correlations among the privacy, security, and utility requirements of grid networks to ensure effective inter-and intra-actions within physical layer equipment (e.g., distributed energy resources (DERs), intelligent electronic devices (IEDs), etc.). …
-
Generative Modeling with Guarantees
… leveraging large amounts of unlabeled data and fine-tuning for downstream tasks. However, concerns have been raised regarding the accuracy and trustworthiness of the text generated by these models. In parallel, differential privacy has emerged as a framework to protect sensitive information …
-
The fundamental limits of statistical data privacy
… Internet is shaping our daily lives. On the one hand, social networks like Facebook and Twitter allow people to share their precious moments and opinions with virtually anyone around the world. On the other, services like Google, Netflix, and Amazon allow people to look up information, watch …
-
Task Oriented Privacy-preserving (TOP) Technologies Using Automatic Feature Selection
A large amount of digital information collected and stored in datasets creates vast opportunities for knowledge discovery and data mining. These datasets, however, may contain sensitive information about individuals and, therefore, it is imperative to ensure that their privacy is protected. Most …
-
Advancing SCRAM: Privacy-Centric Approaches in Cyber Risk Measurement
The Secure Cyber Risk Aggregation and Measurement (SCRAM) framework allows multiple parties to compute aggregate cyber-risk measurements without the need to disclose publicly any information about their identity and their personal data. The framework, through the use of Multi-Party Computation …
-
The optimal mechanism in differential privacy
Differential privacy is a framework to quantify to what extent individual privacy in a statistical database is preserved while releasing useful aggregate information about the database. This dissertation studies the fundamental trade-off between privacy and utility in differential privacy in the …
-
Balancing utility and privacy of high-dimensional datasets : mobile phone metadata
… the way we develop cities, fight disease and crime, and respond to natural disasters. However, understanding the privacy of these data sets is key to their broad use and potential impact, for these consist of sensitive information such as citizens' geo-location. Moreover, recent research …
-
Information-theoretic metrics for security and privacy
… this thesis, we study problems in cryptography, privacy and estimation through the information-theoretic lens. We introduce information-theoretic metrics and associated results that shed light on the fundamental limits of what can be learned from noisy data. These metrics and results, in turn, …