May, 8th 2023
Room 124
9:00-9:15 Opening & Introduction
9:15-10:45 Session 1: Security and Intrusion Detection I
Performance Analysis of Deep-Learning Based Open Set Recognition Algorithms for Network Intrusion Detection Systems
Gaspard Baye, University of Massachusetts, USA.
Priscila Silva, University of Massachusetts, USA.
Alexandre Broggi, University of Massachusetts, USA.
Lance Fiondella, University of Massachusetts, USA.
Nathaniel Bastian, United States Military Academy, West Point, USA.
Gokhan Kul, University of Massachusetts, USA.
Investigating adversarial attacks against Random Forest-based network attack detection systems
Philippe Owezarski, LAAS-CNRS, France.
Early detection of intrusion in sdn
Md. Shamim Towhid, University of Regina, Canada.
Nashid Shahriar, University of Regina, Canada.
10:45-11:00 Break
11:00-12:30 Session 2: Cloud Computing and Anomaly Detection
A Stacking Learning-Based QoE Model for Cloud Gaming
Daniel Soares, Universidade Federal de Minas Gerais, Brazil.
Marcos Carvalho, Universidade Federal de Minas Gerais, Brazil.
Daniel F. Macedo, Universidade Federal de Minas Gerais, Brazil.
Efficient Periodicity Analysis for Real-Time Anomaly Detection
Yusufu Shehu, Moogsoft Ltd., UK.
Robert Harper, Moogsoft Ltd., UK.
On the Temporal Behaviour of a Large-Scale Microservice Architecture
Giles Winchester, University of Sussex, UK.
George Parisis, University of Sussex, UK.
Luc Berthouze, University of Sussex, UK.
12:30-13:30 Lunch
13:30-15:00 Session 3: Machine Learning for Network Management
Trust Me: Explainable ML in Self-Organized Network Management
Faiaz Nazmetdinov, Ilmenau University of Technology, Germany.
Diego Preciado, Ilmenau University of Technology, Germany.
Andreas Mitschele-Thiel, AiVader GmbH, Germany
Graph-based Interpretable Anomaly Detection Framework for Network Slice Management in Beyond 5G Networks
Ashima Chawla, Ericsson, Network Management, Ireland.
Anne-Marie Bosneag, Ericsson, Network Management, Ireland.
Anestis Dalgkitsis, Iquadrat Informatica S.L., Spain.
Autoscaling Packet Core Network Functions with Deep Reinforcement Learning
Jatinder Singh, Orange Innovation Networks, India.
Shantanu Verma, Orange Innovation Networks, India.
Yoichi Matsuo, NTT Network Service Systems Laboratories, Japan.
Francesca Fossati, Sorbonne Universite, France.
Guillaume Fraysse, Orange Innovation Networks, France.
15:00-15:30 Break
15:30-17:00 Session 4: Security and Intrusion Detection II
Data-Centric Machine Learning Approach for Early Ransomware Detection and Attribution
Aldin Vehabovic, University of South Florida, USA.
Hadi Zanddizari, University of Texas San Antonio, USA.
Nasir Ghani, University of South Florida, USA.
Farooq Shaikh, University of South Florida, USA.
Elias Bou-Harb, University of Texas San Antonio, USA.
Morteza Safaei Pour, San Diego State University, USA.
Jorge Crichigno, University of South Carolina, USA.
Towards In-Network Semantic Analysis: A Case Study involving Spam Classification
Cyprien Gueyraud, Illinois Institute of Technology, USA.
Nik Sultana, Illinois Institute of Technology, USA.
Auto-tuning of Hyper-parameters for Detecting Network Intrusions via Meta-learning
Omar Anser, Inria Nancy Grand Est, France.
Jérôme François, Inria Nancy Grand Est, France.
Isabelle Chrisment, Inria Nancy Grand Est, France.
For more information on the IEEE/IFIP NOMS 2023 program click on the link provided below.