Code for Tiresias: Predicting Security Events Through Deep Learning
doi:10.4121/4e12761f-716a-4ea6-b08c-a6a6e459893d.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future.
For a link that will always point to the latest version, please use
doi: 10.4121/4e12761f-716a-4ea6-b08c-a6a6e459893d
doi: 10.4121/4e12761f-716a-4ea6-b08c-a6a6e459893d
Datacite citation style:
van Ede, Thijs (2023): Code for Tiresias: Predicting Security Events Through Deep Learning. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/4e12761f-716a-4ea6-b08c-a6a6e459893d.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Software
This repository contains the code for for Tiresias that was implemented as part of the IEEE S&P DeepCASE paper [PDF], it provides a Pytorch implementation of Tiresias [PDF]. We ask people to cite both works when using the software for academic research papers.
history
- 2023-10-26 first online, published, posted
publisher
4TU.ResearchData
associated peer-reviewed publication
DeepCASE: Semi-Supervised Contextual Analysis of Security Events
references
organizations
University of Twente (Semantics Cybersecurity & Services)
DATA
To access the source code, use the following command:
git clone https://data.4tu.nl/v3/datasets/55fc9c66-c70f-4fdb-bbcf-797caf6bccaf.git
