most citedZero-Knowledge Proof-based Practical Federated Learning on Blockchain

8 citations · 11 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CR2024

SoK: Identifying Limitations and Bridging Gaps of Cybersecurity Capability Maturity Models (CCMMs)

Lasini Liyanage, Nalin Asanka Gamagedara Arachchilage, Giovanni Russello

In the rapidly evolving digital landscape, where organisations are increasingly vulnerable to cybersecurity threats, Cybersecurity Capability Maturity Models (CCMMs) emerge as pivo…

cs.CR20242 cited

No Vandalism: Privacy-Preserving and Byzantine-Robust Federated Learning

Zhibo Xing, Zijian Zhang, Zi'ang Zhang +3

Federated learning allows several clients to train one machine learning model jointly without sharing private data, providing privacy protection. However, traditional federated lea…

cs.CR2023

SoK: Access Control Policy Generation from High-level Natural Language Requirements

Sakuna Harinda Jayasundara, Nalin Asanka Gamagedara Arachchilage, Giovanni Russello

Administrator-centered access control failures can cause data breaches, putting organizations at risk of financial loss and reputation damage. Existing graphical policy configurati…

cs.CR2023

Mostree : Malicious Secure Private Decision Tree Evaluation with Sublinear Communication

Jianli Bai, Xiangfu Song, Xiaowu Zhang +4

A private decision tree evaluation (PDTE) protocol allows a feature vector owner (FO) to classify its data using a tree model from a model owner (MO) and only reveals an inference…

cs.CR2023

CryptoMask : Privacy-preserving Face Recognition

Jianli Bai, Xiaowu Zhang, Xiangfu Song +4

Face recognition is a widely-used technique for identification or verification, where a verifier checks whether a face image matches anyone stored in a database. However, in scenar…

cs.CR20238 cited

Zero-Knowledge Proof-based Practical Federated Learning on Blockchain

Zhibo Xing, Zijian Zhang, Meng Li +4

Since the concern of privacy leakage extremely discourages user participation in sharing data, federated learning has gradually become a promising technique for both academia and i…