Introducing a Comprehensive, Continuous, and Collaborative Survey of Intrusion Detection Datasets
Author:
Affiliation:
1. Cyber Analysis & Defense, Fraunhofer FKIE, Germany
2. Security and Privacy in Industrial Cooperation, RWTH Aachen University, Germany and Cyber Analysis & Defense, Fraunhofer FKIE, Germany
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3675741.3675754
Reference59 articles.
1. The base-rate fallacy and the difficulty of intrusion detection
2. PWNJUTSU: A Dataset and a Semantics-Driven Approach to Retrace Attack Campaigns
3. A Survey of Intrusion Detection Systems Leveraging Host Data
4. Dainius Čeponis and Nikolaj Goranin. 2018. Towards a robust method of dataset generation of malicious activity for anomaly-based HIDS training and presentation of AWSCTD dataset. Baltic Journal of Modern Computing (2018).
5. COMIDDS contributors. 2024. COMIDDS: A comprehensive survey of datasets for research in host-based and/or network-based intrusion detection, with a focus on enterprise networks – GitHub. https://github.com/fkie-cad/COMIDDS
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