1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CR2026
Synthesizing Probabilistic Saturating Counters with Differentially Private Formal Guarantees
Zhiming Chi, Lutan Zhao, Depeng Liu +8
Branch predictors improve instruction-level parallelism in modern processors and are commonly modeled using saturating counters. However, classical saturating counters are determin…
cs.CR2022
Defensive Design of Saturating Counters Based on Differential Privacy
Depeng Liu, Lutan Zhao, Pengfei Yang +4
The saturating counter is the basic module of the dynamic branch predictor, which involves the core technique to improve instruction level parallelism performance in modern process…
cs.CR2020★ 1 cited
Verifying Pufferfish Privacy in Hidden Markov Models
Depeng Liu, Bow-yaw Wang, Lijun Zhang
Pufferfish is a Bayesian privacy framework for designing and analyzing privacy mechanisms. It refines differential privacy, the current gold standard in data privacy, by allowing e…