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 …

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) and its variants have been recently studied to analyze
personal data collected from Internet of Things (IoT) devices while strongly protecting user …

The objective of differential privacy (DP) is to protect privacy by producing an output
distribution that is indistinguishable between any two neighboring databases. However …

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), 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 …

Abstract Local Differential Privacy (LDP) can provide each user with strong privacy
guarantees under untrusted data curators while ensuring accurate statistics derived from …

Local differential privacy (LDP), where each user perturbs her data locally before sending to
an untrusted data collector, is a new and promising technique for privacy-preserving …

Local Differential Privacy (LDP) provides provable privacy protection for data collection
without the assumption of the trusted data server. Existing mechanisms that satisfy LDP or its …

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 …