Uncovering Memorization in Timeseries Imputation models: LBRM Membership Inference and its link to attribute Leakage

ArXi:2603.24213v1 Announce Type: new Deep learning models for time series imputation are now essential in fields such as healthcare, the Internet of Things (IoT), and finance. However, their deployment raises critical privacy concerns. Beyond the well-known issue of unintended memorization, which has been extensively studied in generative models, we nstrate that time series models are vulnerable to inference attacks in a black-box setting. In this work, we