Captured record
report:3980:titleHeadline captured
arXiv — Cryptography & Security (cs.CR) recorded this headline on Sep 1, 2026. No lawful structured evidence is available yet to explain the underlying event.
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Headline captured
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Captured record
report:3980:titlearXiv — Cryptography & Security (cs.CR) recorded this headline on Sep 1, 2026. No lawful structured evidence is available yet to explain the underlying event.
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source brief
source-authored · cleanedarXiv:2608.28889v1 Announce Type: new Abstract: Detecting SQL Injection (SQLi) attacks ranks among the most critical challenges in web application security. This research conducted a systematic literature review to identify the research gaps in this domain and responsively designed and optimised a DistilBERT-Stacked Ensemble pipeline to improve detection efficiency and robustness while reducing false-positive and false-negative rates. Comprehensive pre-processing and tokenisation were performed, DistilBERT embeddings were extracted, and machine-learning and ensemble classifiers were trained an
Cleaned from source-provided descriptive text. This is not independent Forensia analysis. Open the original for the publisher's complete reporting.· sha256:c63b3723dde82a3d…
indicators · 2
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evidence set
2 recordsEnhancing Web Application Firewalls with BERT-GNN for SQL Injection Detection
Enhancing Web Application Firewalls with Machine Learning for SQL Injection Detection
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