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ANTEATER: A Filter-then-Scrutinize Architecture for End-to-End Attack Investigation

Summary: ANTEATER cascades lightweight flow-based filtering with a three-agent LLM scrutinizer over provenance graphs. It reconstructs long-term, stealthy attacks and generates structured analyst-ready reports while controlling LLM cost and context length. (summarized by gpt-5.6-luna on Jul 26 2026)

Paper ID
h9e8709b17b66882e
Venue
SIGMOD
Year
2026
Pagerank
4.9793485e-05
Overall Rank
10,410 | 30.01%
DOI
10.1145/3802012

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Authors

BibTeX Citation

@inproceedings{ren_sigmod26,
        title = {{ANTEATER: A Filter-then-Scrutinize Architecture for End-to-End Attack Investigation}},
        author = {Ren, Yiming and Wang, Haoqiang and Li, Linghao and Chen, Haoyang and Si, Chengxiang and Zhou, Zhou and Liu, Qingyun},
        series = {{SIGMOD} '26},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3802012},
        url = {https://dl.acm.org/doi/10.1145/3802012},
        year = {2026}
}

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
3,449 Robust and Transferable Log-based Anomaly Detection 2023 SIGMOD 7.2931951e-05
5,351 Pluto: Sample Selection for Robust Anomaly Detection on Polluted Log Data 2024 SIGMOD 6.1667315e-05
5,838 PreLog: A Pre-trained Model for Log Analytics 2024 SIGMOD 5.9752181e-05
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