AI-Driven Cybersecurity in Critical Infrastructure (2015–2025) — Bibliometric Package

This repository contains the data and derived outputs used in the paper:

“AI-Driven Cybersecurity in Critical Infrastructure: A Bibliometric Analysis (2015–2025)”
(Energy / Transport / Water sector stratification; OT/ICS/SCADA focus)

Data sources

• Scopus (query executed in TITLE-ABS-KEY)
• Web of Science Core Collection (query executed in TS / Topic)
• Time window: 2015–2025
• Document types: Article and Proceedings Paper
• Language: English

Search queries

Exact Scopus and Web of Science query strings are provided in queries.md.

Corpus construction (PRISMA-guided accounting)

1. Records were retrieved from Scopus and Web of Science using boolean queries designed around:
   • AI methods (e.g., machine learning, deep learning, federated learning, XAI)
   • OT/ICS/SCADA / critical infrastructure context
   • cybersecurity objectives (e.g., intrusion/anomaly/threat detection; false data injection)
2. Collections were created and merged in Biblioshiny/bibliometrix.
3. Deduplication was performed primarily via DOI, supported by title matching.
4. Final merged corpus size: n = 1,862 unique documents.

Sector stratification

Sector tagging was performed using a rule-based multi-label approach on a concatenated metadata field:

• TEXT_ALL = Title + Abstract + Author Keywords

Three boolean flags were created:

• Sector_Energy
• Sector_Transport
• Sector_Water

Resulting sub-corpora (multi-label allowed):

• Energy: N = 716
• Transport: N = 1,131
• Water: N = 233

Contents

Core corpus

• SCOPUS + WoS COLLECTIONS.xlsx — merged, deduplicated dataset (n=1862)

Sector subsets

• Energy_Data.xlsx
• Transport_Data.xlsx
• Water_Data.xlsx

Bibliometric outputs (tables)

• Most_Global_Cited_Documents_bibliometrix_2026-01-02.xlsx
• Thematic Evolution - TABLE.xlsx
• Thematic Map - TABLE - ENERGY.xlsx
• Thematic Map - Clusters - ENERGY.xlsx
• Thematic Map - TABLE - TRANSPORT (Author's keywords).xlsx
• Thematic Map - Clusters - TRANSPORT (Author's keywords).xlsx
• Thematic Map - TABLE - WATER (Author's keywords).xlsx
• Thematic Map - Clusters - WATER (Author's keywords).xlsx

Figures (black & white for conference submission)

• Thematic Map - Author's keywords - TRANSPORT B&W.png
• Thematic Map - Author's keywords - WATER B&W.png
• Thematic Evolution - ENERGY B&W.png
• Thematic Map - ENERGY B&W.png

How to reproduce (high-level)

1. Import the Scopus/WoS collections into Biblioshiny/bibliometrix.
2. Merge collections and deduplicate (DOI + title match).
3. Create TEXT_ALL as Title+Abstract+Author Keywords and apply sector tagging rules.
4. For each sector subset, run conceptual structure / thematic map analysis using Author Keywords.
5. For Energy sector thematic evolution, run thematic evolution using All Keywords with a cut-point at 2020.

Notes

• This repository is intended to provide access to the merged corpus and derived tables used to generate figures and results in the paper.
• Deduplication evidence/logs are available in deduplication_log.md.