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<p>Neuro-symbolic artificial intelligence (NSAI) integrates neural learning with symbolic reasoning to address complex cybersecurity challenges through interpretable and adaptive solutions. This study presents the scientometric mapping of NSAI research in cybersecurity, analyzing publications from Scopus database spanning 2016–2025. Through keyword co-occurrence, bibliographic coupling, and systematic literature review, we identify four thematic clusters and reveal dominant integration paradigms. Our findings show rapid field growth, with Learning-for-Reasoning architectures as the predominant approach. Network intrusion detection and malware analysis emerge as mature domains, while autonomous cyber defense and IoT security remain underexplored. Significant research gaps remain in developing computational efficiency benchmarks, standardized evaluation frameworks, and explainability mechanisms. This integrated approach provides strategic insights for advancing NSAI-driven cybersecurity research and practice.</p>

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Charting the evolution of neuro-symbolic AI in cybersecurity: a scientometric perspective

  • 期刊论文

  • 发表日期：

    2026年3月8日

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  • Shama,
  • Sarika Jain

摘要

Neuro-symbolic artificial intelligence (NSAI) integrates neural learning with symbolic reasoning to address complex cybersecurity challenges through interpretable and adaptive solutions. This study presents the scientometric mapping of NSAI research in cybersecurity, analyzing publications from Scopus database spanning 2016–2025. Through keyword co-occurrence, bibliographic coupling, and systematic literature review, we identify four thematic clusters and reveal dominant integration paradigms. Our findings show rapid field growth, with Learning-for-Reasoning architectures as the predominant approach. Network intrusion detection and malware analysis emerge as mature domains, while autonomous cyber defense and IoT security remain underexplored. Significant research gaps remain in developing computational efficiency benchmarks, standardized evaluation frameworks, and explainability mechanisms. This integrated approach provides strategic insights for advancing NSAI-driven cybersecurity research and practice.