The Tweet Advantage: An Empirical Analysis of 0-Day Vulnerability Information Shared on Twitter - ICT Systems Security and Privacy Protection
Conference Papers Year : 2018

The Tweet Advantage: An Empirical Analysis of 0-Day Vulnerability Information Shared on Twitter

Abstract

In the last couple of years, the number of software vulnerabilities and corresponding incidents increased significantly. In order to stay up-to-date about these new emerging threats, organizations have demonstrated an increased willingness to exchange information and knowledge about vulnerabilities, threats, incidents and countermeasures. Apart from dedicated sharing platforms or databases, information on vulnerabilities is frequently shared on Twitter and other social media platforms. So far, little is known about the obtainable time advantage of vulnerability information shared on social media platforms. To close this gap, we identified 709,880 relevant Tweets and subsequently analyzed them. We found that information with high relevance for affected organizations is shared on Twitter often long before any official announcement or patch has been made available by vendors. Twitter is used as a crowdsourcing platform by security experts aggregating vulnerability information and referencing a multitude of public available webpages in their Tweets. Vulnerability information shared on Twitter can improve organizations reaction to newly discovered vulnerabilities and therefore help mitigating threats.
Fichier principal
Vignette du fichier
472722_1_En_15_Chapter.pdf (340.17 Ko) Télécharger le fichier
Origin Files produced by the author(s)
Loading...

Dates and versions

hal-02023722 , version 1 (21-02-2019)

Licence

Identifiers

Cite

Clemens Sauerwein, Christian Sillaber, Michael M. Huber, Andrea Mussmann, Ruth Breu. The Tweet Advantage: An Empirical Analysis of 0-Day Vulnerability Information Shared on Twitter. 33th IFIP International Conference on ICT Systems Security and Privacy Protection (SEC), Sep 2018, Poznan, Poland. pp.201-215, ⟨10.1007/978-3-319-99828-2_15⟩. ⟨hal-02023722⟩
136 View
382 Download

Altmetric

Share

More