A Query System for Efficiently Investigating Complex Attack Behaviors for Enterprise Security
Summary: AIQL is a domain-specific query system for investigating APTs in massive host-monitoring data. Its attack-aware language, storage model, and semantics-driven execution engine express attack behaviors directly and optimize investigation queries. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Peng Gao (University of California Berkeley)
- 2. Xusheng Xiao (Case Western Reserve University)
- 3. Zhichun Li (NEC Corporation)
- 4. Kangkook Jee (University of Texas)
- 5. Fengyuan Xu (Nanjing University)
- 6. Sanjeev R. Kulkarni (Princeton University)
- 7. Prateek Mittal (Princeton University)
BibTeX Citation
@article{gao_vldb19,
title = {{A Query System for Efficiently Investigating Complex Attack Behaviors for Enterprise Security}},
author = {Gao, Peng and Xiao, Xusheng and Li, Zhichun and Jee, Kangkook and Xu, Fengyuan and Kulkarni, Sanjeev R. and Mittal, Prateek},
journal = {PVLDB},
series = {{VLDB} '19},
volume = {12},
number = {12},
pages = {1802--1805},
doi = {10.14778/3352063.3352070},
url = {https://doi.org/10.14778/3352063.3352070},
year = {2019}
}Incoming Citations (Sorted by Pagerank)
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,655 | A System for Automated Open-Source Threat Intelligence Gathering and Management | 2021 | SIGMOD | 5.093636e-05 |
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