Unleashing the Power of Unlabeled Data: A Self-supervised Learning Framework for Cyber Attack Detection in Smart Grids

no code implementations • 22 May 2024 • Hanyu Zeng, Pengfei Zhou, Xin Lou, Zhen Wei Ng, David K. Y. Yau, Marianne Winslett

Different from existing approaches, the proposed framework does not rely on large amounts of well-curated labeled data but makes use of the massive unlabeled data in the wild which are easily accessible.

Cyber Attack Detection Self-Supervised Learning

Self-evolving Autoencoder Embedded Q-Network

no code implementations • 18 Feb 2024 • J. Senthilnath, Bangjian Zhou, Zhen Wei Ng, Deeksha Aggarwal, Rajdeep Dutta, Ji Wei Yoon, Aye Phyu Phyu Aung, Keyu Wu, Min Wu, XiaoLi Li

During the evolution of the autoencoder architecture, a bias-variance regulatory strategy is employed to elicit the optimal response from the RL agent.

Decision Making Reinforcement Learning (RL)