Attributing Open-Source Contributions is Critical but Difficult: A Systematic Analysis of GitHub Practices and Their Impact on Software Supply Chain Security
Jan-Ulrich Holtgrave
Network and Distributed System Security (NDSS) Symposium 2025 · Day 3 · Github + OSN Security
In an era of increasing data privacy regulations, the "right to be forgotten" has become a critical challenge for machine learning systems. This technical article synthesizes key insights from a session at the NDSS Symposium, which explored the burgeoning field of machine unlearning. The talks presented diverse yet complementary approaches to ensuring data privacy, intellectual property protection, and model hygiene by effectively removing the influence of specific data points or experiences from trained models.
AI review
Three competent academic contributions to the machine unlearning problem — RL-specific unlearning is legitimately underexplored, and the certified unlearnability framework is the most interesting piece here. None of it is groundbreaking enough to define the conversation, but it's real work done by people who clearly understand the problem space.