Get your Foes Fooled: Proximal Gradient Split Learning for Defense against Model Inversion Attacks on IoMT data. (arXiv:2201.04569v1 [cs.CR])

The past decade has seen a rapid adoption of Artificial Intelligence (AI),
specifically the deep learning networks, in Internet of Medical Things (IoMT)
ecosystem. However, it has been shown recently that the deep learning networks
can be exploited by adversarial attacks that not only make IoMT vulnerable to
the data theft but also to the manipulation of medical diagnosis. The existing
studies consider adding noise to the raw IoMT data or model parameters which
not only reduces the overall performance …

arxiv attacks data defense gradient learning