Visual-friendly concept protection via selective adversarial perturbations

X Mi, F Tang, J Cao, P Li, Y Liu - arxiv preprint arxiv:2408.08518, 2024 - arxiv.org
Personalized concept generation by tuning diffusion models with a few images raises
potential legal and ethical concerns regarding privacy and intellectual property rights …

Spider: A semi-supervised continual learning-based network intrusion detection system

SK Amalapuram, BR Tamma… - IEEE INFOCOM 2024 …, 2024 - ieeexplore.ieee.org
Network intrusion detection (NID) aims to identify unusual network traffic patterns
(distribution shifts) that require NID systems to evolve continuously. While prior art …

Improving Data-aware and Parameter-aware Robustness for Continual Learning

H **ao, F Lyu - arxiv preprint arxiv:2405.17054, 2024 - arxiv.org
The goal of Continual Learning (CL) task is to continuously learn multiple new tasks
sequentially while achieving a balance between the plasticity and stability of new and old …

Adversarially Robust Continual Learning with Anti-Forgetting Loss

K Mukai, S Kumano, N Michel, L **ao… - … Conference on Image …, 2024 - ieeexplore.ieee.org
Existing continual learning methods focus on preventing catastrophic forgetting but often
overlook the challenge of adversarial examples in image classification. In this study, we …