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Artifact appendix for loglearners: identifying compromised AI functions in serverless systems
Umeå University, Faculty of Science and Technology, Department of Computing Science.
Umeå University, Faculty of Science and Technology, Department of Computing Science.ORCID iD: 0000-0002-2633-6798
Umeå University, Faculty of Science and Technology, Department of Computing Science.ORCID iD: 0000-0002-9842-7840
2026 (English)In: Proceedings: 2026 IEEE 26th International Symposium on Cluster, Cloud and Internet Computing Workshops, CCGridW 2026, Institute of Electrical and Electronics Engineers (IEEE), 2026, p. 87-88Conference paper, Published paper (Refereed)
Abstract [en]

The complete artifact for reproducing the results presented in the paper is provided. The artifact comprises source code, detection-model notebooks, an eBPF-collected system call dataset, and infrastructure scripts to recreate the testbed. It enables the reader to: (i) reproduce all detection experiments (SVM, XGBoost, 1D-CNN, Transformer, GNN) across four feature types (syscall identities, return values, parameters, and combined) and four context window sizes (250, 500, 1000, 2000) reported in Table V; (ii) reproduce the exploratory data analysis in Figures 4, 5(a), and 5(b); (iii) inspect the source code of all 30 serverless functions (Table III), including four attack payloads derived from real PyPI malware; (iv) reuse the system call dataset (~1.9 M traces) for independent research; and (v) reproduce the full testbed and data collection pipeline from scratch.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2026. p. 87-88
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:umu:diva-258447DOI: 10.1109/CCGridW69005.2026.00033Scopus ID: 2-s2.0-105046893566ISBN: 9798331570484 (print)ISBN: 9798331570477 (electronic)OAI: oai:DiVA.org:umu-258447DiVA, id: diva2:2098420
Conference
2026 IEEE 26th International Symposium on Cluster, Cloud and Internet Computing Workshops (CCGridW), Sydney, Australia, 18-21 May, 2026
Available from: 2026-09-03 Created: 2026-09-03 Last updated: 2026-09-03Bibliographically approved

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Bhutto, Adil BinElmroth, ErikBhuyan, Monowar

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