Labelled Hacker Datasets
Document Type
Dataset
Rights
Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence
Disciplines
Computer Sciences
Abstract
These datasets were used to perform experiments with machine learning models aimed to detect hacker communication regarding software vulnerabilities. Details are at: GitHub - andlq/dataset_hacker_online_communication
More on that can be read in the paper below:
DOI
https://github.com/andlq/dataset_hacker_online_communication
Recommended Citation
Queiroz, A.L., Mckeever, S., Keegan, B.: Eavesdropping hackers: Detecting software vulnerability communication on social media using text mining. In: The Fourth International Conference on Cyber Technologies and Cyber-Systems. pp. 41-48 (2019) Queiroz, A. L., Keegan, B., and Mckeever, S.: Moving Targets: Addressing Concept Drift in Supervised Models for Hacker Communication Detection. In: International Conference on Cyber Security and Protection of Digital Services (Cyber Security). pp. 1–7 (2020) Queiroz, A. L., Mckeever, S., and Keegan, B.: Detecting hacker threats: Performance of Word and Sentence Embedding models in identifying hacker communications. In: The 27th AIAI Irish Conference on Artificial Intelligence and Cognitive Science. Volume 2563. pp. 116–127 (2019)
Publication Details
Queiroz, A. L., Keegan, B., and Mckeever, S.: Moving Targets: Addressing Concept Drift in Supervised Models for Hacker Communication Detection. In: International Conference on Cyber Security and Protection of Digital Services (Cyber Security). pp. 1–7 (2020)