Adversarial Defenses on Graph: Heuristic and Certified

This blog post provides an overview of adversarial defense techniques on graph-structured data.

In the slides (linked below), I introduce both heuristic defenses and certified defenses for graphs. I particularly focus on randomized smoothing (RS)-based certified defense methods, which have become popular due to their generality and ease of implementation.

Additionally, I describe my own approach, CiDer, which is a black-box method for certifying node classification models. Compared with standard RS-based approaches, CiDer avoids retraining and finetuning of the model, and instead relies on black-box decision outputs and statistical testing to produce certified guarantees.

📄 Download slides overviewing graph adversarial defenses

📘 Read the full CiDer paper (INFOCOM 2025)

Reference

Liang, Xiaoyu, Haohua Du, Wen Ma, Ye Tian, and Xiaoya Xu. “CiDer: A Black-box Approach to Classify Node with Certified Robustness Guarantees.” In IEEE INFOCOM 2025-IEEE Conference on Computer Communications, 2025.