Responses to AHP-style questionnaires regarding the publication "D-Score: An Expert-Based Method for Assessing the Detectability of IoT-Related Cyber-Attacks"
- 1. Ben-Gurion University of the Negev
Description
In order to assess in advance the detectability of IoT-related cyber-attacks by anomaly-based network intrusion detection systems, we developed an expert-based method which relies on the AHP methodology.
The online AHP-style questionnaire can be found here: https://bguprivacysurvey.limequery.com/537457
The dataset which is hereby made public, includes the (anonymous) responses of 40 cyber-security researchers and practitioners, covering 4 IoT attack scenarios.
The related publication is mentioned hereinafter; please be sure to cite it upon the use of this dataset.
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The dataset itself is free to use, however users are requested to cite the following paper, which describes in detail the research objectives as well as the data collection, preparation and analysis.
@article{MEIDAN2022103073,
title = {D-Score: An Expert-Based Method for Assessing the Detectability of IoT-Related Cyber-Attacks},
journal = {Computers & Security},
pages = {103073},
year = {2022},
issn = {0167-4048},
doi = {https://doi.org/10.1016/j.cose.2022.103073},
url = {https://www.sciencedirect.com/science/article/pii/S0167404822004655},
author = {Yair Meidan and Daniel Benatar and Ron Bitton and Dan Avraham and Asaf Shabtai}
}
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Additional details
Funding
References
- @article{MEIDAN2022103073, title = {D-Score: An Expert-Based Method for Assessing the Detectability of IoT-Related Cyber-Attacks}, journal = {Computers & Security}, pages = {103073}, year = {2022}, issn = {0167-4048}, doi = {https://doi.org/10.1016/j.cose.2022.103073}, url = {https://www.sciencedirect.com/science/article/pii/S0167404822004655}, author = {Yair Meidan and Daniel Benatar and Ron Bitton and Dan Avraham and Asaf Shabtai} }