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A Comprehensive Survey of Privacy-preserving Federated Learning
ACM Computing Surveys, 2021 The past four years have witnessed the rapid development of federated learning (FL). However, new privacy concerns have also emerged during the aggregation of the distributed intermediate results.
Xuefei Yin, Yanming Zhu, Jiankun Hu
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Privacy-preserving association rule mining via multi-key fully homomorphic encryption
Journal of King Saud University: Computer and Information Sciences, 2023 Association rule mining is an efficient method to mine the association relationships between different items from large transaction databases, but is vulnerable to privacy leakage as operates over users’ sensitive data directly.
Peiheng Jia +4 more
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Fairness and Privacy-Preserving in Federated Learning: A Survey [PDF]
Information Fusion, 2023 Federated learning (FL) as distributed machine learning has gained popularity as privacy-aware Machine Learning (ML) systems have emerged as a technique that prevents privacy leakage by building a global model and by conducting individualized training of
T. Rafi +3 more
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ZOCB and ZOTR: Tweakable Blockcipher Modes for Authenticated Encryption with Full Absorption
IACR Transactions on Symmetric Cryptology, 2019 We define ZOCB and ZOTR for nonce-based authenticated encryption with associated data, and analyze their provable security. These schemes use a tweakable blockcipher (TBC) as the underlying primitive, and fully utilize its input to process a plaintext ...
Zhenzhen Bao +2 more
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SoK: Privacy-Preserving Data Synthesis [PDF]
IEEE Symposium on Security and Privacy, 2023 As the prevalence of data analysis grows, safeguarding data privacy has become a paramount concern. Consequently, there has been an upsurge in the development of mechanisms aimed at privacy-preserving data analyses.
Yuzheng Hu +9 more
semanticscholar +1 more source
Boomerang Connectivity Table Revisited. Application to SKINNY and AES
IACR Transactions on Symmetric Cryptology, 2019 The boomerang attack is a variant of differential cryptanalysis which regards a block cipher E as the composition of two sub-ciphers, i.e., E = E1 o E0, and which constructs distinguishers for E with probability p2q2 by combining differential trails for ...
Ling Song, Xianrui Qin, Lei Hu
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Privacy Preserving Data Mining
Advances in Information Security, 2015 Recent interest in data collection and monitoring using data mining for security and business-related applications has raised privacy. Privacy Preserving Data Mining (PPDM) techniques require data modification to disinfect them from sensitive information
J. Vaidya, Yu Zhu, C. Clifton
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THE-X: Privacy-Preserving Transformer Inference with Homomorphic Encryption [PDF]
Findings, 2022 As more and more pre-trained language models adopt on-cloud deployment, the privacy issues grow quickly, mainly for the exposure of plain-text user data (e.g., search history, medical record, bank account).
Tianyu Chen +8 more
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The Novel Location Privacy-Preserving CKD for Mobile Crowdsourcing Systems
IEEE Access, 2018 With the development of mobile devices, mobile crowdsourcing has become the research hotspot in mobile crowd sensing networks (MCSS). How to protect the location privacy of mobile user in location-based services is a key problem in MCSS.
Zhongyang Chi +3 more
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End-to-end privacy preserving deep learning on multi-institutional medical imaging
Nature Machine Intelligence, 2021 Using large, multi-national datasets for high-performance medical imaging AI systems requires innovation in privacy-preserving machine learning so models can train on sensitive data without requiring data transfer.
Georgios Kaissis +13 more
semanticscholar +1 more source