Substructure-aware Log Anomaly Detection
Summary: SLAD detects code-file-level log anomalies by mining representative graph substructures with Monte Carlo Tree Search, then distilling and softly pruning them for node inference. It preserves subtle event/structural/location changes while achieving 15× faster inference than substructure-based methods. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yanni Tang (University of Auckland)
- 2. Zhuoxing Zhang (University of Auckland)
- 3. Kaiqi Zhao (University of Auckland)
- 4. Lanting Fang (Southeast University)
- 5. Zhenhua Li (Southwest University)
- 6. Wu Chen (Southwest University)
BibTeX Citation
@article{tang_vldb25,
title = {{Substructure-aware Log Anomaly Detection}},
author = {Tang, Yanni and Zhang, Zhuoxing and Zhao, Kaiqi and Fang, Lanting and Li, Zhenhua and Chen, Wu},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {2},
pages = {213--225},
doi = {10.14778/3705829.3705840},
url = {https://doi.org/10.14778/3705829.3705840},
year = {2025}
}Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,692 | Unseen Anomaly Detection from System Logs | 2026 | SIGMOD | 4.9793485e-05 |
| 11,303 | LLMLog: Advanced Log Template Generation via LLM-driven Multi-Round Annotation | 2025 | VLDB | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,622 | Algorithm and System Co-design for Efficient Subgraph-based Graph Representation Learning | 2022 | VLDB | 6.4982876e-05 |
| 4,686 | A Demonstration of AutoOD: A Self-Tuning Anomaly Detection System | 2022 | VLDB | 6.4708106e-05 |
| 5,677 | SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning | 2023 | VLDB | 6.041013e-05 |
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| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 4,594 | AS-Parser: Log Parsing Based on Adaptive Segmentation | 2023 | SIGMOD |
| 2 | 6,197 | GraphAn: Graph-based Subsequence Anomaly Detection | 2020 | VLDB |
| 3 | 6,066 | Streaming Anomaly Detection Using Randomized Matrix Sketching | 2016 | VLDB |
| 4 | 9,386 | Behavior Query Discovery in System-Generated Temporal Graphs | 2016 | VLDB |
| 5 | 11,303 | LLMLog: Advanced Log Template Generation via LLM-driven Multi-Round Annotation | 2025 | VLDB |
| 6 | 11,799 | ADOps: An Anomaly Detection Pipeline in Structured Logs | 2023 | VLDB |
| 7 | 11,343 | CoLA: Model Collaboration for Log-based Anomaly Detection | 2025 | VLDB |
| 8 | 5,838 | PreLog: A Pre-trained Model for Log Analytics | 2024 | SIGMOD |
| 9 | 10,692 | Unseen Anomaly Detection from System Logs | 2026 | SIGMOD |
| 10 | 3,449 | Robust and Transferable Log-based Anomaly Detection | 2023 | SIGMOD |