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20192022
most citedFine-grained Poisoning Attack to Local Differential Privacy Protocols for Mean and Variance Estimation

7 citations · 17 across the 7 of their papers we have counts for

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7 papers · 1 filter

cs.CR2022★ 7 cited

Fine-grained Poisoning Attack to Local Differential Privacy Protocols for Mean and Variance Estimation

Xiaoguang Li, Ninghui Li, Wenhai Sun +2

Although local differential privacy (LDP) protects individual users' data from inference by an untrusted data curator, recent studies show that an attacker can launch a data poison…

cs.CR2021

Speedster: A TEE-assisted State Channel System

Jinghui Liao, Fengwei Zhang, Wenhai Sun +1

State channel network is the most popular layer-2 solution to theissues of scalability, high transaction fees, and low transaction throughput of public Blockchain networks. However…

cs.CR2020★ 3 cited

Monitoring-based Differential Privacy Mechanism Against Query-Flooding Parameter Duplication Attack

Haonan Yan, Xiaoguang Li, Hui Li +3

Public intelligent services enabled by machine learning algorithms are vulnerable to model extraction attacks that can steal confidential information of the learning models through…

cs.CR2020

Towards Overcoming the Undercutting Problem

Tiantian Gong, Mohsen Minaei, Wenhai Sun +1

Mining processes of Bitcoin and similar cryptocurrencies are currently incentivized with voluntary transaction fees and fixed block rewards which will halve gradually to zero. In t…

cs.CR2020★ 5 cited

Fingerprinting Encrypted Voice Traffic on Smart Speakers with Deep Learning

Chenggang Wang, Sean Kennedy, Haipeng Li +5

This paper investigates the privacy leakage of smart speakers under an encrypted traffic analysis attack, referred to as voice command fingerprinting. In this attack, an adversary…

cs.CR2020★ 2 cited

Mitigating Query-Flooding Parameter Duplication Attack on Regression Models with High-Dimensional Gaussian Mechanism

Xiaoguang Li, Hui Li, Haonan Yan +3

Public intelligent services enabled by machine learning algorithms are vulnerable to model extraction attacks that can steal confidential information of the learning models through…

cs.CR2019

Enjoy the Untrusted Cloud: A Secure, Scalable and Efficient SQL-like Query Framework for Outsourcing Data

Yaxing Chen, Qinghua Zheng, Dan Liu +5

While the security of the cloud remains a concern, a common practice is to encrypt data before outsourcing them for utilization. One key challenging issue is how to efficiently per…