A survey of trustworthy federated learning: Issues, solutions, and challenges
Trustworthy artificial intelligence (TAI) has proven invaluable in curbing potential negative
repercussions tied to AI applications. Within the TAI spectrum, federated learning (FL) …
repercussions tied to AI applications. Within the TAI spectrum, federated learning (FL) …
Recent methodological advances in federated learning for healthcare
For healthcare datasets, it is often impossible to combine data samples from multiple sites
due to ethical, privacy, or logistical concerns. Federated learning allows for the utilization of …
due to ethical, privacy, or logistical concerns. Federated learning allows for the utilization of …
{UBA-Inf}: Unlearning Activated Backdoor Attack with {Influence-Driven} Camouflage
Machine-Learning-as-a-Service (MLaaS) is an emerging product to meet the market
demand. However, end users are required to upload data to the remote server when using …
demand. However, end users are required to upload data to the remote server when using …
Vertical federated learning for effectiveness, security, applicability: A survey
Vertical Federated Learning (VFL) is a privacy-preserving distributed learning paradigm
where different parties collaboratively learn models using partitioned features of shared …
where different parties collaboratively learn models using partitioned features of shared …
Approaching Expressive and Secure Vertical Federated Learning With Embedding Alignment in Intelligent IoT Systems
L Li, K Hu, X Zhu, S Jiang, L Weng… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
In the context of vertical federated learning (VFL), agents utilize multimodal data on their
edge devices to corporately train and inference with the deep learning models. However, in …
edge devices to corporately train and inference with the deep learning models. However, in …
A Lightweight and Accuracy-Lossless Privacy-Preserving Method in Federated Learning
Z Liu, C Yang, Y Ding, H Liang… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
The emergence of Big Data and Artificial Intelligence (AI) marks a significant milestone in
technological advancement, impacting various sectors and transforming the essence of …
technological advancement, impacting various sectors and transforming the essence of …
Attackers Are Not the Same! Unveiling the Impact of Feature Distribution on Label Inference Attacks
As a distributed machine learning paradigm, vertical federated learning enables multiple
passive parties with distinct features and an active party with labels to train a model …
passive parties with distinct features and an active party with labels to train a model …
分割学习数据隐私研究综述
秦轶群， 马晓静， 付佳韵， 胡平一， 徐鹏… - 网络与信息安全 …, 2024 - infocomm-journal.com
随着机器学习的快速发展, 以其为核心的人工智能技术已经应用于生活的各个领域,
但人们也日益担忧机器学习会泄露隐私信息. 为了保护国家和公民的信息安全, 我国颁布了 …
但人们也日益担忧机器学习会泄露隐私信息. 为了保护国家和公民的信息安全, 我国颁布了 …