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Predicting future threats

Predicting attacks can help to prevent them or at least reduce their impact. Nowadays, existing attack prediction methods make accurate predictions only hours in advance or cannot predict geo-politically motivated attacks. ThreatPredict aims to predict different attack types days in advance. It develops machine-learning algorithms that capture spatio-temporal dynamics of cyber-attacks and global social, geo-political and technical events. Various sources of information are collected, enriched and correlated such as honeypot data, darknet, GDELT, Twitter, and vulnerability databases. In addition to warning about attacks, this project will improve our understanding of the effect of global events on cyber-security.

Predicting future threats

Predicting attacks can help to prevent them or at least reduce their impact. Nowadays, existing attack prediction methods make accurate predictions only hours in advance or cannot predict geo-politically motivated attacks. ThreatPredict aims to predict different attack types days in advance. It develops machine-learning algorithms that capture spatio-temporal dynamics of cyber-attacks and global social, geo-political and technical events. Various sources of information are collected, enriched and correlated such as honeypot data, darknet, GDELT, Twitter, and vulnerability databases. In addition to warning about attacks, this project will improve our understanding of the effect of global events on cyber-security.

International Project

This project involved three countries with three academic partners to deliver high-quality research: Inria in France, International University of Rabat in Morocco, and Carnegie Mellon University in USA.

Partners

Funding

News

Paper acceptation at ISI 2018 conference

We are happy to announce our papers acceptation at ISI 2018 conference, the IEEE Intelligence and Security Informatics (ISI) 2018. The name of the papers is :  Exploratory Data Analysis of a Network Telescope Traffic and Prediction of Port Probing Rates. Analysis of Hacking Related Trade in the Darkweb. Have a look at participating authors: Mehdi … Continue reading "Paper acceptation at ISI 2018 conference"

ThreatPredict at NetSoft18 conference

ThreatPredict @ IEEE NetSoft18

ThreatPredict was represented at IEEE Netsoft 2018, in the ETSN workshop: https://project.inria.fr/etsn/. Jérôme François was presenting results about methods to mine known relations between attack and vulnerability descriptions to enhance their classification and predict unknown relations.

ThreatPredict at RESSI Conference 2018

The ThreatPredict project was presented by Jérôme François at RESSI  Conference 2018.  RESSI is a major French event in network and system security bringing together more than 60 researchers and practitioners this year with a lot of live interaction. The presentation introduced the main challenges the project targets to tackle as well as first results … Continue reading "ThreatPredict at RESSI Conference 2018"

Publications

2018

  • Quang-Vinh Dang, Jérôme François. Utilizing attack enumerations to study SDN/NFV vulnerabilities. IEEE ETSN – Emerging Trends in Softwarized Networks, Jun 2018, Montreal, Canada
  • Kathleen M. Carley, Guido Cervone, Nitin Agarwal, Huan Liu, 2018, Social Cyber-Security, In Proceedings of the International Conference SBP-BRiMS 2018, Halil Bisgin, Ayaz Hyder, Chris Dancy, and Robert Thomson (Eds.) July 10-13, 2018 Washington DC, Springer.
  • Geoffrey Dobson and Kathleen M. Carley, 2018, A Computational Model of Cyber Situational Awareness, In Proceedings of the International Conference SBP-BRiMS 2018, Halil Bisgin, Ayaz Hyder, Chris Dancy, and Robert Thomson (Eds.) July 10-13, 2018 Washington DC, Springer.
  • Ghita Mezzour, Kathleen M. Carley, L. Richard Carley. Remote Assessment of Countries’ Cyber Weapon Capabilities. Social Network Analysis and Mining (R&R)
  • T. Tang, S.A.R. Zaidi, D. McLernon, L. Mhamdi, M. Ghogho, “Deep Recurrent Neural Network for Intrusion Detection in SDN-based Networks, IEEE International Conference on Network Softwarization (NetSoft 2018), Montreal, Canada, June 2018.

Follow us on Twitter

Our paper “Exploratory #DataAnalysis of a #Network #TelescopeTraffic and #Prediction of #PortProbingRates” was accepted in @ieeeisiconf #ieeeisi18 💪
@Inria_Nancy @UIRabat more information will come so stay posted!

The ThreatPredict project funded by NATO SPS is now on Twitter! Inria in France, International University of Rabat in Morocco, and Carnegie Mellon University in USA will predict future threats in Internet. Have a look at https://t.co/GB1j3mC0f4

YAY, #NATO_SPS project “ThreatPredict: From Global Social and Technical Big Data to Cyber Threat Forecast” got funded #uir #inria #cmu

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