Dates: 2018 - ongoing
Contact: aloga ifca.unican.es
Areas: computing
Tags: time series , deep learning
Links:
This project intends to improve classical Intrusion Detection Systems (IDS) using Deep Learning tools.
The idea is to be able to filter the massive amounts of alerts generated by traditional IDS (eg. Snort) in order to provide a more curated and relevant subset that can be analyzed by network supervisors.
An initial implementation was carried out during the DEEP Hybrid DataCloud project under the Massive Online Data Streams (MODS) usecase.