ThreatPredict: From Global Social and Technical Big Data to Cyber Threat Forecast - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Chapitre D'ouvrage Année : 2020

ThreatPredict: From Global Social and Technical Big Data to Cyber Threat Forecast

Résumé

Predicting the next threats that may occurs in the Internet is a multifaceted problem as the predictions must be enough precise and given as most as possible in advance to be exploited efficiently, for example to setup defensive measures. The ThreatPredict project aims at building predictive models by integrating exogenous sources of data using machine learning algorithms. This paper reports the most notable results using technical data from security sensors or contextual information about darkweb cyber-criminal markets and data breaches.
Fichier principal
Vignette du fichier
TPspringer2019_full_hal.pdf (1.45 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03036928 , version 1 (02-12-2020)

Identifiants

Citer

Jérôme François, Frédéric Beck, Ghita Mezzour, Kathleen M Carley, Abdelkader Lahmadi, et al.. ThreatPredict: From Global Social and Technical Big Data to Cyber Threat Forecast. Advanced Technologies for Security Applications, Springer, pp.45-54, 2020, Advanced Technologies for Security Applications. Proceedings of the NATO Science for Peace and Security 'Cluster Workshop on Advanced Technologies, ⟨10.1007/978-94-024-2021-0_5⟩. ⟨hal-03036928⟩
121 Consultations
212 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More