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RICCI, S. SIKORA, M. PARKER, S. LENDAK, I. DANIDOU, Y. CHATZOPOULOU, A. BADONNEL, R. ALKSNYS, D.
Originální název
Job Adverts Analyzer for Cybersecurity Skills Needs Evaluation
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
This article presents a new free web-based application, the Cybersecurity Job Ads Analyzer, which has been created to collect and analyse job adverts using a machine learning algorithm. This algorithm enables the detection of the skills required in advertised cybersecurity work positions. The application is both interactive and dynamic allowing for automated analyses and for the underlying database of job adverts to be easily updated. Through the Cybersecurity Job Ads Analyzer, it is possible to explore the skills required over time, and thereby enable academia and other training providers to better understand and address the needs of the industry. We will describe in detail the user interface and technical background of the application, as well as highlight the preliminary statistical results we have obtained from analysing the current database of job adverts.
Klíčová slova
Cybersecurity Education;Skills;Work Roles;Machine Learning;Job Ads Analyzer
Autoři
RICCI, S.; SIKORA, M.; PARKER, S.; LENDAK, I.; DANIDOU, Y.; CHATZOPOULOU, A.; BADONNEL, R.; ALKSNYS, D.
Vydáno
23. 8. 2022
Nakladatel
ACM
ISBN
978-1-4503-9670-7
Kniha
ARES '22: Proceedings of the 17th International Conference on Availability, Reliability and Security
Strany od
1
Strany do
10
Strany počet
URL
https://dl.acm.org/doi/10.1145/3538969.3543821
BibTex
@inproceedings{BUT178195, author="Sara {Ricci} and Marek {Sikora} and Simon {Parker} and Imre {Lendak} and Yianna {Danidou} and Argyro {Chatzopoulou} and Remi {Badonnel} and Donatas {Alksnys}", title="Job Adverts Analyzer for Cybersecurity Skills Needs Evaluation", booktitle="ARES '22: Proceedings of the 17th International Conference on Availability, Reliability and Security", year="2022", pages="1--10", publisher="ACM", doi="10.1145/3538969.3543821", isbn="978-1-4503-9670-7", url="https://dl.acm.org/doi/10.1145/3538969.3543821" }