works on

From the 1 of 6 linked papers with an AI index.

most citedIdentifying Backdoored Graphs in Graph Neural Network Training: An Explanation-Based Approach with Novel Metrics

3 citations · 3 across the 5 of their papers we have counts for

collaborators

6 papers

eess.SY2026

Matched Disturbance Rejection for Port-Hamiltonian Systems with Coupled Dynamics

M. Reza J. Harandi

This paper investigates the rejection of matched disturbances generated by coupled port-Hamiltonian (PH) dynamics in previously stabilized PH systems. The disturbance dynamics are…

cs.CR2026

Early Detection of Distributed Backdoors in Multi-Agent LLM Systems: A Characterization Study

Diego Fernandez Arias, Dev Prashant Mistry, Ren Wang +1

Multi-agent LLM systems can be attacked by a payload that no single agent ever holds in full: a poisoned tool hides encrypted fragments in its observations, spreads them across sev…

cs.CR2026

When Local Monitors Miss Compositional Harm: Diagnosing Distributed Backdoors in Multi-Agent Systems

Yibo Hu, Ren Wang

The paper shows that runtime monitors checking each step of multi-agent LLM systems can miss attacks that are split across agents, because each fragment looks benign on its own, an…

cs.CR2026

MoCo-EA: Exploiting Adversarial Mode Connectivity for Efficient Evolutionary Attacks

Hyo Seo Kim, Gang Luo, Can Chen +3

Evolutionary algorithms for adversarial attacks leverage population-based search to discover perturbations without gradient information, but suffer from inefficient crossover opera…

cs.CR2026

Watermarking Graph Neural Networks via Explanations for Ownership Protection

Jane Downer, Yingdan Shi, Ziyan Liu +2

Graph Neural Networks (GNNs) are widely deployed in industry, making their intellectual property valuable. However, protecting GNNs from unauthorized use remains a challenge. Water…

cs.LG20263 cited

Identifying Backdoored Graphs in Graph Neural Network Training: An Explanation-Based Approach with Novel Metrics

Jane Downer, Ren Wang, Binghui Wang

Graph Neural Networks (GNNs) have gained popularity in numerous domains, yet they are vulnerable to backdoor attacks that can compromise their performance and ethical application.…