Abstract Local Differential Privacy (LDP), where each user perturbs her data locally before
sending to an untrusted party, is a new and promising privacy-preserving model. Endorsed …

Local Differential Privacy (LDP), where each user perturbs her data locally before sending to
an untrusted party, is a new and promising privacy-preserving model for mobile data …

Local differential privacy (LDP), where users randomly perturb their inputs to provide
plausible deniability of their data without the need for a trusted party, has been adopted …

Local differential privacy (LDP) is a recently proposed privacy standard for collecting and
analyzing data, which has been used, eg, in the Chrome browser, iOS and macOS. In LDP …

Local differential privacy (LDP) is a well-established privacy protection scheme for collecting
sensitive data, which has been integrated into major platforms such as iOS, Chrome, and …

Organizations with a large user base, such as Samsung and Google, can potentially benefit
from collecting and mining users' data. However, doing so raises privacy concerns, and risks …

Local differential privacy (LDP), which perturbs each user's data locally and only sends the
noisy version of her information to the aggregator, is a popular privacy-preserving data …

Collecting and analyzing massive data generated from smart devices have become
increasingly pervasive in crowdsensing, which are the building blocks for data-driven …

Local differential privacy (LDP) has been received increasing attention as a formal privacy
definition without a trusted server. In a typical LDP protocol, the clients perturb their data …

Local Differential Privacy (LDP) provides provable privacy protection for data collection
without the assumption of the trusted data server. In the real-world scenario, different data …