Papers › Euler: Detecting Network Lateral Movement via Scalable Temporal Link Prediction
Euler: Detecting Network Lateral Movement via Scalable Temporal Link Prediction
Isaiah J. King, H. Howie Huang
Lateral movement is a key stage of system compromise used by advanced persistent threats. Detecting it is no simple task. When network host logs are abstracted into discrete temporal graphs, the problem can be reframed as anomalous edge detection in an evolving network. Research in modern deep graph learning techniques has produced many creative and complicated models for this task. However, as is the case in many machine learning fields, the generality of models is of paramount importance for accuracy and scalability during training and inference. In this paper, we propose a formalized approach to this problem with a framework we call EULER. It consists of a model-agnostic graph neural network stacked upon a model-agnostic sequence encoding layer such as a recurrent neural network. Models built according to the EULER framework can easily distribute their graph convolutional layers across multiple machines for large performance improvements. Additionally, we demonstrate that EULER-based models are competitive, or better than many state-of-the-art approaches to anomalous link detection and prediction. As anomaly-based intrusion detection systems, EULER models can efficiently identify anomalous connections between entities with high precision and outperform other unsupervised techniques for anomalous lateral movement detection.
Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Dynamic Link Prediction | DBLP Temporal | Euler | AP | 89.03 | #2 of 7 | Archive leaderboard | report |
| Dynamic Link Prediction | DBLP Temporal | Euler | AUC | 86.54 | #2 of 7 | Archive leaderboard | report |
| Dynamic Link Prediction | Enron Emails | Euler | AP | 94.10 | #1 of 7 | Archive leaderboard | report |
| Dynamic Link Prediction | Enron Emails | Euler | AUC | 93.15 | #1 of 7 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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