policy
Network-Anomaly-Detection-using-RL-model-and-Autoencoders
kumarpiyushraj · PyTorch
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Overview
Name
Network-Anomaly-Detection-using-RL-model-and-Autoencoders
Author
kumarpiyushraj
Framework
PyTorch
License
unknown
Skill type
other
Evidence level
untested
Task description
This project presents an integrated anomaly detection framework combining Autoencoders and Proximal Policy Optimization (PPO) reinforcement learning. Three types of Autoencoders—FeedForward, Denoising, and Convolutional—are used for feature extraction and reconstruction error analysis. Each model is
Spaces
Action space
other · 0-dim · 0Hz
Observation space
- type: other
Links
HuggingFace repo
null
Paper (arXiv)
null
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