International Workshop on Graph-based network Security (GraSec) in conjunction with IFIP/IEEE International Symposium on Integrated Network Management IM2021

About GraSec

Most of the existing security monitoring solutions cannot cope with unknown and complex attacks due to the continual apparition of new threats, botnet propagation and command-and-control mechanisms. Recently, botnet detection systems which leverage communication graph analysis using machine learning have gained attention to overcome these limitations. Graph-based modeling and mining approaches have been proposed and provide interesting results.

Graph-based modeling offers the advantage of understanding complex attacks and determining the root cause of an attack. However, existing graph mining tools for anomaly detection over streaming events are not adapted for cyber-security problems while the corresponding data continuously appears in the form of complex graphs.

The workshop serves to bring together people from industry and academia including researchers, developers, and practitioners from a variety of fields working on graphs and their applications to network security and cybersecurity in general as well as blockchain. Moreover, the workshop allows attendees to share and discuss their latest findings from both theoretical and practical perspectives in several techniques and methods for graph modeling, mining, learning, and visualizing. The main goal of GraSec is to present research and experience results in graph applications on network and cybersecurity as well as the defensive and offensive tools.


GraSec 2020


Click here to download the Call for Papers in a PDF.


  • Graph modeling/mining/learning-based intrusion/botnet/threats detection
  • Graph learning-driven access controls, security policies, etc.
  • Attack graphs modeling, analysis, etc.
  • Sampling and summarizing techniques of graphs for network and cybersecurity.
  • Big graph analytics, parallel algorithms for dynamic/big graph analysis on HPC (CPU-GPU) systems.
  • Autoencoders, representation learning for graphs
  • Graph embedding techniques and applications on network data.
  • Visualization of dynamic and large-scale graphs
  • Detection of threats with evolving behaviors using graphs
  • Novel applications of static/dynamic and large graphs in cybersecurity, blockchain, cryptocurrency, robot, etc.


Paper submissions must present original, unpublished research, development or experiences. Only original papers that have not been published or submitted for publication elsewhere can be submitted. Each submission must be written in English, accompanied by a 50 to 200 words abstract that clearly outlines the scope and contributions of the paper. Self-plagiarized papers will be rejected without further review.

Submissions must be in IEEE 2-column style. There is a length limitation of 6 pages for regular papers, and 4 pages for short papers. Page limit includes title, abstract, all figures, tables, and references.

Authors should submit their papers via JEMS:


At least one of the authors have to register to the IFIP/IEEE IM 2021 conference and resent the paper (links will be provided later).

Accepted regular papers, they will have a 25 minutes time slot for oral presentation (including Q&A) at assigned time slot. Accepted short papers, they will have a 20 minutes time slot for oral presentation (including Q&A).


Paper Submission Deadline (extended): January 8th, 2021  January 22, 2021, January 29, 2021 (Firm)
Notification of Acceptance:  February 18th, 2021
Camera-ready submissions:  March 5th, 2021

Workshop Date: May, 2021


Papers accepted for GraSec 2021 will be included in the conference proceedings, IEEE Xplore, IFIP database and EI Index. IFIP and IEEE reserve the right to remove any paper from the IFIP database and IEEE Xplore if the paper is not presented at the workshop.


  • Sofiane Lagraa (SnT, University of Luxembourg)
  • Radu State (SnT, University of Luxembourg)
  • Hamida Seba (LIRIS, University of Lyon, France)
  • Martin Husák (Masaryk University, Czech Republic)

Contact us:

  • Sofiane Lagraa: sofiane.lagraa [a t]
  • Martin Husák: husakm [a t]


Technical Program Committee (TPC):

  • Fabian Böhm, University of Regensburg, Germany
  • Jay Yang, Rochester Institute of Technology, USA
  • Pavol Sokol, Pavol Jozef Šafárik University in Košic, Slovakia
  • Li-Chun Zhang, University of Oslo, Norway
  • Pierre Parrend, ECAM Strasbourg-Europe, France
  • Cristina Alcaraz, University of Malaga, Spain
  • Erisa Karafili, University of Southampton, United Kingdom
  • Mohammed Haddad, University of Lyon, France.
  • Lucian Andrei TRESTIOREANU, University of Luxembourg, Luxembourg