[D] Foundational papers for Graph Adversarial Learning?

I've been self teaching myself graph theory and have really been enjoying it. My job is going to take a pivot towards adversarial ML, so I was curious on the applications of graph theory and adversarial ML. I found the following resource: https://github.com/safe-graph/graph-adversarial-learning-literature which seems to be quite useful. Though, I'd like to make sure I have the fundamentals covered first before diving into anything published in the last year or two.

Does anyone have recommended papers I could read …

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