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.

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Showing 1 to 9 of 9 for “"Privacy Guarantee"”.

  1. Smartphone Privacy in Citizen Science

    … application was implemented to support privacy in citizen science. In this thesis, we will evaluate the usability of our privacy-preserving crowdsensing application for citizen science projects. An in person user study with 22 participants has been performed showing that participants …

    vt Repository record for Smartphone Privacy in Citizen Science (opens in a new tab)

  2. Understanding and mitigating privacy risk in machine learning systems

    … the widespread adoption of machine learning, privacy issues have emerged. This thesis studies the privacy risk in modern machine learning systems in two ways. First, we improve the understanding on machine learning privacy through attacks and measurements. Due to the increasing complexity and …

    uiuc Repository record for Understanding and mitigating privacy risk in machine learning systems (opens in a new tab)

  3. Local differential privacy in decentralized optimization

    Privacy concerns with sensitive data are receiving increasing attention. In this thesis, we study local differential privacy (LDP) in interactive decentralized optimization. Comparing to central differential privacy (DP), where a centralized curator maintains the dataset, LDP is a stronger notion …

    mit Repository record for Local differential privacy in decentralized optimization (opens in a new tab)

  4. Information privacy for linked data

    … prevalent in research applications, information privacy becomes a more important issue. This is especially true in the biological and medical fields, where information sensitivity is high. Previous experience has shown that simple anonymization techniques, such as removing an individual's name …

    mit Repository record for Information privacy for linked data (opens in a new tab)

  5. Efficient Privacy-Aware Imagery Data Analysis

    … data to the public cloud can cause serious privacy concerns and even legal issues.</p> <p>In this dissertation, I propose a comprehensive privacy-preserving imagery data analysis framework which can be integrated in different application scenarios to assist image analysis for …

    embry-riddle Repository record for Efficient Privacy-Aware Imagery Data Analysis (opens in a new tab)

  6. Algorithmic Interactions With Strategic Users: Incentives, Interplay, and Impact

    … recognizing the value of their data, demand privacy guarantees or compensations in exchange for sharing their information. The thesis delves into various aspects of this problem, including the estimation task itself, the allocation of privacy guarantees, and the potential vulnerabilities of …

    mit Repository record for Algorithmic Interactions With Strategic Users: Incentives, Interplay, and Impact (opens in a new tab)

  7. Search over Encrypted Data in Cloud Computing

    … data and applications into the cloud exposes a privacy leakage risk of the user data. As the growing awareness of data privacy, more and more users begin to choose proactive protection for their data in the cloud through data encryption. One major problem of data encryption is that it hinders …

    vt Repository record for Search over Encrypted Data in Cloud Computing (opens in a new tab)

  8. Privacy Preservation for Cloud-Based Data Sharing and Data Analytics

    Data privacy is a globally recognized human right for individuals to control the access to their personal information, and bar the negative consequences from the use of this information. As communication technologies progress, the means to protect data privacy must also evolve to address new …

    vt Repository record for Privacy Preservation for Cloud-Based Data Sharing and Data Analytics (opens in a new tab)

  9. Budget allocation on differentially private decision trees and random forests

    Privacy-preserving techniques are necessary to minimize the possibility of identifying and learning sensitive information about individuals from any datasets that have been released or shared. Datasets containing sensitive information on individuals are becoming increasingly public. Although this …

    uts Repository record for Budget allocation on differentially private decision trees and random forests (opens in a new tab)