In the last few years, the phenomena of violence against workers have become very relevant, especially in Europe. These phenomena are linked to several causes and to manage them properly, it is mandatory to merge safety vision with a security perspective, even if generally the two aspects are managed by separate departments with completely different competence, vocabulary and approaches. As a consequence, there are no adequate statistics on the phenomena and, consequently, most of the countermeasure are based on qualitative assumptions. To partially overcome this limit the STW (Security of Transport Workers) project aims to collect evidence from several sources to provide a consolidated overview of the phenomena with a focus on Italy. To this end, a mixed strategy has been adopted with the aim of integrating qualitative and quantitative information coming from several sources also including information available on the Internet. Specifically, inside STW an OSINT platform has been developed to collect data from open source, i.e., mass media and social networks, in order to complement data acquired from “official” statistics collected by transport companies and law enforcement agencies. In this way we adopt the “Safety Intelligence” paradigm to improve our capability to describe the phenomena, enriching the data with information generally not available in official statistics and, moreover, allowing us to estimate the “population’s awareness” with respect to the phenomena. Specifically, in the paper we illustrate the approach used in the STW project to collect and manage data from open source.

Lombardi, M., Nobili, M., Faramondi, L., Setola, R., Ghelli, M., Persechino, B., An OSINT platform to analyse violence against workers in public transportation, 2021 International Conference on Cyber-Physical Social Intelligence (ICCSI), IEEE, Beijing, China 2021: 1-6. 10.1109/ICCSI53130.2021.9736240 [http://hdl.handle.net/10807/198021]

An OSINT platform to analyse violence against workers in public transportation

Lombardi, M;
2021

Abstract

In the last few years, the phenomena of violence against workers have become very relevant, especially in Europe. These phenomena are linked to several causes and to manage them properly, it is mandatory to merge safety vision with a security perspective, even if generally the two aspects are managed by separate departments with completely different competence, vocabulary and approaches. As a consequence, there are no adequate statistics on the phenomena and, consequently, most of the countermeasure are based on qualitative assumptions. To partially overcome this limit the STW (Security of Transport Workers) project aims to collect evidence from several sources to provide a consolidated overview of the phenomena with a focus on Italy. To this end, a mixed strategy has been adopted with the aim of integrating qualitative and quantitative information coming from several sources also including information available on the Internet. Specifically, inside STW an OSINT platform has been developed to collect data from open source, i.e., mass media and social networks, in order to complement data acquired from “official” statistics collected by transport companies and law enforcement agencies. In this way we adopt the “Safety Intelligence” paradigm to improve our capability to describe the phenomena, enriching the data with information generally not available in official statistics and, moreover, allowing us to estimate the “population’s awareness” with respect to the phenomena. Specifically, in the paper we illustrate the approach used in the STW project to collect and manage data from open source.
Inglese
9781665426213
IEEE
Lombardi, M., Nobili, M., Faramondi, L., Setola, R., Ghelli, M., Persechino, B., An OSINT platform to analyse violence against workers in public transportation, 2021 International Conference on Cyber-Physical Social Intelligence (ICCSI), IEEE, Beijing, China 2021: 1-6. 10.1109/ICCSI53130.2021.9736240 [http://hdl.handle.net/10807/198021]
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10807/198021
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact