A survey on federated unlearning: Challenges, methods, and future directions

Z Liu, Y Jiang, J Shen, M Peng, KY Lam… - ACM Computing …, 2023 - dl.acm.org
In recent years, the notion of “the right to be forgotten”(RTBF) has become a crucial aspect of
data privacy for digital trust and AI safety, requiring the provision of mechanisms that support …

Guaranteeing Data Privacy in Federated Unlearning with Dynamic User Participation

Z Liu, Y Jiang, W Jiang, J Guo, J Zhao… - arXiv preprint arXiv …, 2024 - arxiv.org
Federated Unlearning (FU) is gaining prominence for its capacity to eliminate influences of
Federated Learning (FL) users' data from trained global FL models. A straightforward FU …

Trustworthy, Responsible, and Safe AI: A Comprehensive Architectural Framework for AI Safety with Challenges and Mitigations

C Chen, Z Liu, W Jiang, GS Qi, KKY Lam - arXiv preprint arXiv:2408.12935, 2024 - arxiv.org
AI Safety is an emerging area of critical importance to the safe adoption and deployment of
AI systems. With the rapid proliferation of AI and especially with the recent advancement of …