An overview of implementing security and privacy in federated learning
K Hu, S Gong, Q Zhang, C Seng, M **a… - Artificial Intelligence …, 2024 - Springer
Federated learning has received a great deal of research attention recently, with privacy
protection becoming a key factor in the development of artificial intelligence. Federated …
protection becoming a key factor in the development of artificial intelligence. Federated …
Synthetic data in biomedicine via generative artificial intelligence
The creation and application of data in biomedicine and healthcare often face privacy
constraints, bias, distributional shifts, underrepresentation of certain groups and data …
constraints, bias, distributional shifts, underrepresentation of certain groups and data …
Synthetic data, real errors: how (not) to publish and use synthetic data
Generating synthetic data through generative models is gaining interest in the ML
community and beyond, promising a future where datasets can be tailored to individual …
community and beyond, promising a future where datasets can be tailored to individual …
A survey of what to share in federated learning: Perspectives on model utility, privacy leakage, and communication efficiency
Federated learning (FL) has emerged as a secure paradigm for collaborative training among
clients. Without data centralization, FL allows clients to share local information in a privacy …
clients. Without data centralization, FL allows clients to share local information in a privacy …
Beyond privacy: Navigating the opportunities and challenges of synthetic data
Generating synthetic data through generative models is gaining interest in the ML
community and beyond. In the past, synthetic data was often regarded as a means to private …
community and beyond. In the past, synthetic data was often regarded as a means to private …
Challenges and remedies to privacy and security in aigc: Exploring the potential of privacy computing, blockchain, and beyond
Artificial Intelligence Generated Content (AIGC) is one of the latest achievements in AI
development. The content generated by related applications, such as text, images and …
development. The content generated by related applications, such as text, images and …
Unraveling Attacks to Machine Learning-Based IoT Systems: A Survey and the Open Libraries Behind Them
The advent of the Internet of Things (IoT) has brought forth an era of unprecedented
connectivity, with an estimated 80 billion smart devices expected to be in operation by the …
connectivity, with an estimated 80 billion smart devices expected to be in operation by the …
Why tabular foundation models should be a research priority
Recent text and image foundation models are incredibly impressive, and these models are
attracting an ever-increasing portion of research resources. In this position piece we aim to …
attracting an ever-increasing portion of research resources. In this position piece we aim to …
Synthetic data for privacy-preserving clinical risk prediction
Synthetic data promise privacy-preserving data sharing for healthcare research and
development. Compared with other privacy-enhancing approaches—such as federated …
development. Compared with other privacy-enhancing approaches—such as federated …
Auditing and generating synthetic data with controllable trust trade-offs
Real-world data often exhibits bias, imbalance, and privacy risks. Synthetic datasets have
emerged to address these issues by enabling a paradigm that relies on generative AI …
emerged to address these issues by enabling a paradigm that relies on generative AI …