2nd GNNet Workshop
Graph Neural Networking Workshop
Co-located with ACM CoNEXT 2023
December 8, 2023
We are glad to announce the “2nd Graph Neural Networking Workshop 2023”, which is organized as part of “ACM CoNEXT 2023” to be held in Paris. All accepted papers will be included in the conference proceedings and be made available in the ACM Digital Library.
The goal of GNNet is to leverage graph data representations and modern GNN technology to advance the application of AI/ML in networking. GNNet provides the first dedicated venue to present and discuss the latest advancements on GNNs and general AI/ML on graphs applied to networking problems. GNNet will bring together leaders from academia and industry to showcase recent methodological advances of GNNs and their application to networking problems, covering a wide range of applications and practical challenges for large-scale training and deployment.
We expect GNNet would serve as the meeting point for the growing community on this fascinating domain, which has currently not a specific forum for sharing and discussion.
The GNNet workshop seeks for contributions in the field of GNNs and graph-based learing applied to data communication networking problems, including the analysis of on-line and off-line massive datasets, network traffic traces, topological data, cybersecurity, performance measurements, and more. GNNet also encourages novel and out-of-the-box approaches and use cases related to the application of GNNs in networking. The workshop will allow researchers and practitioners to discuss the open issues related to the application of GNNs and graph-based learning to networking problems and to share new ideas and techniques for big data analysis and AI/ML in data communication networks.
GNNet would also include a dedicated special session where the top teams competing at the third edition of the Graph Neural Networking Challenge (https://bnn.upc.edu/challenge/gnnet2023/) would be invited to present the winning solutions of the challenge, providing an excellent complement to the main program.
Topics of Interest
We encourage both mature and positioning submissions describing systems, platforms, algorithms and applications addressing all facets of the application of GNNs and Machine learning on graphs to the analysis of data communication networks. We are particularly interested in disruptive and novel ideas that permit to unleash the power of GNNs in the networking domain. The following is a non-exhaustive list of topics:
- GNNs and graph-based learing in networking applications
- Representation Learning on networking-related graphs
- Application of GNNs to network and service management
- Application of GNNs to network security and anomaly detection
- Application of GNNs to detection of malware, botnets, intrusions, phishing, and abuse detection
- Adversarial learning for GNN-driven networking applications
- GNNs for data generation and digital twining in networking
- Temporal and dynamic GNNs in networking
- Graph-based analytics for visualization of complex networking applications
- Libraries, benchmarks, and datasets for GNN-based networking applications
- Scalability of GNNs for networking applications
- Explainability, fairness, accountability, transparency, and privacy issues in GNN-based networking
- Challenges, pitfalls, and negative results in applying GNNs to networking applications
Submissions must be original, unpublished work, and not under consideration at another conference or journal. Submitted papers must be at most six (6) pages long, including all figures, tables, references, and appendices in two-column 10pt ACM format. Papers must include authors names and affiliations for single-blind peer reviewing by the PC. Authors of accepted papers are expected to present their papers at the workshop.
All accepted papers will be included in the conference proceedings and be made available in the ACM Digital Library.
Please submit your papers at https://conext-gnnet2023.hotcrp.com
- Paper submission deadline:
September 8, 2023September 30, 2023 (extended – HARD DEADLINE)
- Paper acceptance notifications:
October 18, 2023October 21, 2023 (extended)
- Camera ready due: October 25, 2023
- Workshop date: December 8, 2023
Please note that these dates are tentative and may still change slightly in the next few weeks. Please stay tuned for further updates.
University of Siena, Italy
- Paul Almasan, Telefonica Research, Spain
- Zied Ben Houidi, Huawei Technologies Co. Ltd, France
- Lilian Berton, University of Sao Paulo, Brazil
- Albert Bifet, Telecom Paris & University of Waikato, New Zealand
- Lluís Fàbrega, Universitat de Girona, Spain
- Marco Fiore, IMDEA Networks, Spain
- Jerome François, INRIA, France
- Fabien Geyer, Technical University of Munich, Germany
- Matthias Herlich, Salzburg Research, Austria
- Brigitte Jaumard, Ericsson, Canada
- Mehrdad Kiamari, University of Southern California, USA
- Federico Larroca, Universidad de la República, Uruguay
- Alina Lazar, Youngstown State University, USA
- Ilias Leontiadis, Meta, UK
- Jens Myrup Pedersen, Aalborg University, Denmark
- Christoph Neumann, Broadpeak, France
- Xi Peng, Huawei Technologies Co. Ltd, Hong Kong, China
- Krzysztof Rusek, AGH University of Science and Technology, Poland
- Pavlos Sermpezis, Aristotle University of Thessaloniki, Greece
- Stefano Traverso, Ermes Cyber Security SRL, Italy
- Zhi-Li Zhang, University of Minnesota – Twin Cities, USA