New Research on Detecting Misreporting Attacks in XR Networks to be Presented at CNSM 2025

We are pleased to announce that a new research paper from the City University of New York (CUNY), leveraging the ILLIXR platform, has been accepted for publication at the 21st International Conference on Network and Service Management (CNSM 2025). The paper introduces the first hybrid ML framework capable of detecting and mitigating stealthy misreporting attacks in software-defined networks (SDNs) that host immersive XR workloads, highlighting ILLIXR’s expanding role in advancing secure and trustworthy immersive computing.

Paper Title: Detection of Misreporting Attacks on Software-Defined Immersive Environments
Authors: S. Saha, M. N. Absur, S. Yousefi, and S. Debroy 

Summary:
This work presents a hybrid machine-learning framework that detects stealthy misreporting attacks in SDN-based XR pipelines, where malicious switches falsify network loads to mislead controllers and degrade user experience. Using ILLIXR integrated with the NSF FABRIC testbed, the study reproduces realistic adversarial scenarios and traces their impact from network telemetry to application-level XR quality of experience (QoE).