Open Internet by MindsNet

Detecting Attacks from Aggregated Multi-Endpoint Data with Deep Learning Models

Current deep learning models for attack detection are primarily designed for single endpoint data. There is a need for research on using DL models to analyze and detect attacks from aggregated multi-endpoint data at a central server. This challenge involves developing effective models that can handle complex, distributed data sources.

Computing & Technology, Computer Science, Machine Learning