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We consider the problem of enhancing user privacy in common data analysis and machine learning development tasks, such as data annotation and inspection, by substituting the real data with samples from a generative adversarial network. We propose employing ...
The need for efficient, widespread and reliable security and user privacy technologies is important more so than ever before. This is in particular crucial for workflows involving image data. Images can be easily edited to give a false impression of realit ...
In this thesis, we focus on the problem of achieving practical privacy guarantees in machine learning (ML), where the classic differential privacy (DP) fails to maintain a good trade-off between user privacy and data utility. Differential privacy guarantee ...
Smartphones present many interesting opportunities for survey research, particularly through the use of mobile data collection applications (apps). There is still much to learn, however, about how to integrate apps in general population surveys. Recent stu ...
Homomorphic encryption, which enables the execution of arithmetic operations directly on ciphertexts, is a promising solution for protecting privacy of cloud-delegated computations on sensitive data. However, the correctness of the computation result is no ...
Strategic information is valuable either by remaining private (for instance if it is sensitive) or, on the other hand, by being used publicly to increase some utility. These two objectives are antagonistic and leaking this information by taking full advant ...
Secure retrieval of data requires integrity, confidentially, transparency, and metadata-privacy of the process. Existing protection mechanisms, however, provide only partially these properties: encryption schemes still expose cleartext metadata, protocols ...
In human-computer interaction, self-disclosure of sensitive information regarding distressing experiences requires the establishment of a trust channel between the user and the digital tool. As privacy and security have been identified as factors that cont ...
To help fighting the COVID-19 pandemic, the Pan-European Privacy-Preserving Proximity Tracing (PEPP-PT) project proposed a Decentralized Privacy-Preserving Proximity Tracing (DP3T) system. This helps tracking the spread of SARS-CoV-2 virus while keeping th ...
This article assesses the risk-risk trade-off between privacy and efficacy that the use of contact tracing apps entails. It argues for the use of privacy-preserving apps, but highlights potential weaknesses and cautions against allowing digital tracing to ...
