Local Differential Privacy (LDP) is a popular standard for privacy-preserving data collection.
Numerous LDP protocols have been proposed in the literature which differ in how they …

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 …

The protocols that satisfy Local Differential Privacy (LDP) enable untrusted third parties to
collect aggregate information about a population without disclosing each user's privacy. In …

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

Abstract In recent years, Local Differential Privacy (LDP), a robust privacy-preserving
methodology, has gained widespread adoption in real-world applications. With LDP, users …

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 …

Local differential privacy (LDP) is a strong notion of privacy that often leads to a significant
drop in utility. The original definition of LDP assumes that all the elements in the data …

Local Differential Privacy (LDP) is popularly used in practice for privacy-preserving data
collection. Although existing LDP protocols offer high utility for large user populations …

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) protocols enable an untrusted data collector to perform
privacy-preserving data analytics. In particular, each user locally perturbs its data to …