Privacy-Preserving Algorithms

DataFunSummit

Jul 22, 2023 · Information Security

HG‑LDP: A Memory‑Efficient Framework for High‑Frequency Item Statistics under Local Differential Privacy

This article introduces the HG‑LDP framework, which combines local differential privacy with the HeavyGuardian data structure to enable accurate, privacy‑preserving high‑frequency item statistics on streaming data while using only limited memory, and evaluates four algorithmic variants (BGR, DSR, BDR, CNR) through extensive experiments on synthetic and real‑world datasets.

HeavyGuardianHigh-Frequency ItemLocal Differential Privacy

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HG‑LDP: A Memory‑Efficient Framework for High‑Frequency Item Statistics under Local Differential Privacy

DataFunSummit

Oct 2, 2022 · Artificial Intelligence

Differential Privacy: Principles, Algorithms, and Applications in Data Security

This article presents an in‑depth overview of differential privacy, covering its motivation, mathematical definition, noise‑addition mechanisms, a heterogeneous‑data variant, and practical applications such as federated learning, while also discussing challenges, theoretical guarantees, experimental results, and future research directions.

Data SecurityFederated LearningPrivacy-Preserving Algorithms

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Differential Privacy: Principles, Algorithms, and Applications in Data Security