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Investigating the applications of artificial intelligence in cyber security

Author

Listed:
  • Naveed Naeem Abbas

    (The Islamia University of Bahawalpur)

  • Tanveer Ahmed

    (COMSATS University)

  • Syed Habib Ullah Shah

    (The Islamia University of Bahawalpur)

  • Muhammad Omar

    (The Islamia University of Bahawalpur)

  • Han Woo Park

    (YeungNam University)

Abstract

Artificial Intelligence (AI) provides instant insights to pierce through the noise of thousands of daily security alerts. The recent literature focuses on AI’s application to cyber security but lacks visual analysis of AI applications. Structural changes have been observed in cyber security since the emergence of AI. This study promotes the development of theory about AI in cyber security, helps researchers establish research directions, and provides a reference that enterprises and governments can use to plan AI applications in the cyber security industry. Many countries, institutions and authors are densely connected through collaboration and citation networks. Artificial neural networks, an AI technique, gave birth to today’s research on cloud cyber security. Many research hotspots such as those on face recognition and deep neural networks for speech recognition may create future hotspots on emerging technology, such as on artificial intelligence systems for security. This study visualizes the structural changes, hotspots and emerging trends in AI studies. Five evaluation factors are used to judge the hotspots and trends of this domain and a heat map is used to identify the areas of the world that are generating research on AI applications in cyber security. This study is the first to provide an overall perspective of hotspots and trends in the research on AI in the cyber security domain.

Suggested Citation

  • Naveed Naeem Abbas & Tanveer Ahmed & Syed Habib Ullah Shah & Muhammad Omar & Han Woo Park, 2019. "Investigating the applications of artificial intelligence in cyber security," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 1189-1211, November.
    • Handle: RePEc:spr:scient:v:121:y:2019:i:2:d:10.1007_s11192-019-03222-9
    DOI: 10.1007/s11192-019-03222-9
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    References listed on IDEAS

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    Cited by:

    1. Xiaoli Wang & Yun Liu & Lingdi Chen & Yifan Zhang, 2022. "Correlation Monitoring Method and model of Science-Technology-Industry in the AI Field: A Case of the Neural Network," SAGE Open, , vol. 12(4), pages 21582440221, December.
    2. Ricardo Arencibia-Jorge & Rosa Lidia Vega-Almeida & José Luis Jiménez-Andrade & Humberto Carrillo-Calvet, 2022. "Evolutionary stages and multidisciplinary nature of artificial intelligence research," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5139-5158, September.
    3. Li, Munan & Wang, Wenshu & Zhou, Keyu, 2021. "Exploring the technology emergence related to artificial intelligence: A perspective of coupling analyses," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    4. Yifan Song & Takashi Natori & Xintao Yu, 2024. "Tracing the Evolution of E-Government: A Visual Bibliometric Analysis from 2000 to 2023," Administrative Sciences, MDPI, vol. 14(7), pages 1-25, June.

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