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20172026
most citedFederated Learning for 6G Communications: Challenges, Methods, and Future Directions

424 citations · 1.1k across the 25 of their papers we have counts for

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Showing cs.CRShow all

15 papers · 1 filter

cs.CR2026

PrivTune: Efficient and Privacy-Preserving Fine-Tuning of Large Language Models via Device-Cloud Collaboration

Yi Liu, Weixiang Han, Chengjun Cai +2

With the rise of large language models, service providers offer language models as a service, enabling users to fine-tune customized models via uploaded private datasets. However,…

cs.CR2024★ 7 cited

BadSampler: Harnessing the Power of Catastrophic Forgetting to Poison Byzantine-robust Federated Learning

Yi Liu, Cong Wang, Xingliang Yuan

Federated Learning (FL) is susceptible to poisoning attacks, wherein compromised clients manipulate the global model by modifying local datasets or sending manipulated model update…

cs.CR2023★ 39 cited

Leakage-Abuse Attacks Against Forward and Backward Private Searchable Symmetric Encryption

Lei Xu, Leqian Zheng, Chengzhi Xu +2

Dynamic searchable symmetric encryption (DSSE) enables a server to efficiently search and update over encrypted files. To minimize the leakage during updates, a security notion nam…

cs.CR2023★ 27 cited

Training-free Lexical Backdoor Attacks on Language Models

Yujin Huang, Terry Yue Zhuo, Qiongkai Xu +3

Large-scale language models have achieved tremendous success across various natural language processing (NLP) applications. Nevertheless, language models are vulnerable to backdoor…

cs.CR2022★ 19 cited

Penny Wise and Pound Foolish: Quantifying the Risk of Unlimited Approval of ERC20 Tokens on Ethereum

Dabao Wang, Hang Feng, Siwei Wu +3

The prosperity of decentralized finance motivates many investors to profit via trading their crypto assets on decentralized applications (DApps for short) of the Ethereum ecosystem…

cs.CR2022★ 186 cited

The Right to be Forgotten in Federated Learning: An Efficient Realization with Rapid Retraining

Yi Liu, Lei Xu, Xingliang Yuan +2

In Machine Learning, the emergence of \textit{the right to be forgotten} gave birth to a paradigm named \textit{machine unlearning}, which enables data holders to proactively erase…

cs.CR2022★ 4 cited

Aggregation Service for Federated Learning: An Efficient, Secure, and More Resilient Realization

Yifeng Zheng, Shangqi Lai, Yi Liu +3

Federated learning has recently emerged as a paradigm promising the benefits of harnessing rich data from diverse sources to train high quality models, with the salient features th…

cs.CR2021★ 30 cited

DeFiRanger: Detecting Price Manipulation Attacks on DeFi Applications

Siwei Wu, Dabao Wang, Jianting He +5

The rapid growth of Decentralized Finance (DeFi) boosts the Ethereum ecosystem. At the same time, attacks towards DeFi applications (apps) are increasing. However, to the best of o…

cs.CR2020★ 93 cited

Towards A First Step to Understand Flash Loan and Its Applications in DeFi Ecosystem

Dabao Wang, Siwei Wu, Ziling Lin +5

Flash Loan, as an emerging service in the decentralized finance ecosystem, allows users to request a non-collateral loan. While providing convenience, it also enables attackers to…

cs.CR2020★ 2 cited

ShieldDB: An Encrypted Document Database with Padding Countermeasures

Viet Vo, Xingliang Yuan, Shi-Feng Sun +3

The security of our data stores is underestimated in current practice, which resulted in many large-scale data breaches. To change the status quo, this paper presents the design of…

cs.CR2020

Accelerating Forward and Backward Private Searchable Encryption Using Trusted Execution

Viet Vo, Shangqi Lai, Xingliang Yuan +3

Searchable encryption (SE) is one of the key enablers for building encrypted databases. It allows a cloud server to search over encrypted data without decryption. Dynamic SE additi…

cs.CR2020★ 17 cited

Towards Practical Encrypted Network Traffic Pattern Matching for Secure Middleboxes

Shangqi Lai, Xingliang Yuan, Shi-Feng Sun +4

Network Function Virtualisation (NFV) advances the adoption of composable software middleboxes. Accordingly, cloud data centres become major NFV vendors for enterprise traffic proc…

cs.CR2019★ 4 cited

Enabling Efficient Privacy-Assured Outlier Detection over Encrypted Incremental Datasets

Shangqi Lai, Xingliang Yuan, Amin Sakzad +3

Outlier detection is widely used in practice to track the anomaly on incremental datasets such as network traffic and system logs. However, these datasets often involve sensitive i…

cs.CR2019★ 39 cited

GraphSE: An Encrypted Graph Database for Privacy-Preserving Social Search

Shangqi Lai, Xingliang Yuan, Shi-Feng Sun +3

In this paper, we propose GraphSE, an encrypted graph database for online social network services to address massive data breaches. GraphSE preserves the functionality of s…

cs.CR2017★ 72 cited

LightBox: Full-stack Protected Stateful Middlebox at Lightning Speed

Huayi Duan, Cong Wang, Xingliang Yuan +3

Running off-site software middleboxes at third-party service providers has been a popular practice. However, routing large volumes of raw traffic, which may carry sensitive informa…