45 citations · 173 across the 17 of their papers we have counts for
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cs.CR2023★ 5 cited
Pool Inference Attacks on Local Differential Privacy: Quantifying the Privacy Guarantees of Apple's Count Mean Sketch in Practice
Andrea Gadotti, Florimond Houssiau, Meenatchi Sundaram Muthu Selva Annamalai +1
Behavioral data generated by users' devices, ranging from emoji use to pages visited, are collected at scale to improve apps and services. These data, however, contain fine-grained…
cs.CR2023★ 11 cited
SoK: A Data-driven View on Methods to Detect Reflective Amplification DDoS Attacks Using Honeypots
Marcin Nawrocki, John Kristoff, Raphael Hiesgen +3
In this paper, we revisit the use of honeypots for detecting reflective amplification attacks. These measurement tools require careful design of both data collection and data analy…