A5021175709- Privacy-Preserving Technologies in Data
- Internet Traffic Analysis and Secure E-voting
- Cryptography and Data Security
- Privacy, Security, and Data Protection
- Data Quality and Management
- Data-Driven Disease Surveillance
- Traffic Prediction and Management Techniques
- Cloud Data Security Solutions
- Access Control and Trust
- Human Mobility and Location-Based Analysis
Imperial College London
2018-2024
University of Oxford
2024
Recent advances in synthetic data generation (SDG) have been hailed as a solution to the difficult problem of sharing sensitive while protecting privacy. SDG aims learn statistical properties real order generate "artificial" that are structurally and statistically similar data. However, prior research suggests inference attacks on can undermine privacy, but only for specific outlier records. In this work, we introduce new attribute attack against The is based linear reconstruction methods...
Behavioral data generated by users' devices, ranging from emoji use to pages visited, are collected at scale improve apps and services. These data, however, contain fine-grained records can reveal sensitive information about individual users. Local differential privacy has been used companies as a solution collect users while preserving privacy. We here first introduce pool inference attacks, where an adversary access user's obfuscated defines pools of objects, exploits the polarized...
Mobile phones and other ubiquitous technologies are generating vast amounts of high-resolution location data. This data has been shown to have a great potential for the public good, e.g. monitor human migration during crises or predict spread epidemic diseases. Location is, however, considered one most sensitive types data, large body research limits traditional anonymization methods big Privacy concerns so far strongly limited use collected by telcos, especially in developing countries.In...
Anonymized data is highly valuable to both businesses and researchers. A large body of research has however shown the strong limits de-identification release-and-forget model, where anonymized shared. This led development privacy-preserving query-based systems. Based on idea "sticky noise", Diffix been recently proposed as a novel mechanism satisfying alone EU Article~29 Working Party's definition anonymization. According its authors, adds less noise answers than solutions based differential...