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Role of artificial neural networks in fortifying cybersecurity: A review.

Bibliographic Details
Title: Role of artificial neural networks in fortifying cybersecurity: A review.
Authors: Yadav, Avantika, Aggarwal, Vishesh, Bansal, Sulabh
Source: AIP Conference Proceedings; 2025, Vol. 3253 Issue 1, p1-13, 13p
Subject Terms: Artificial neural networks, Digital technology, Cyberterrorism, Anomaly detection (Computer security), Internet security, Intrusion detection systems (Computer security)
Abstract: The paper explores the indispensable role of Artificial Neural Networks (ANNs) in bolstering cybersecurity, with a particular emphasis on three domains: intrusion detection, malware classification, and anomaly detection. ANNs, renowned for their capacity to distinguish intricate patterns, are at the forefront of revolutionizing cyber defence mechanisms. Through an exhaustive examination of recent advancements and illustrative case studies, this paper underscores the efficacy of ANNs in countering evolving cyber threats. Moreover, it illuminates their broader implications in the realm of digital security, including applications in pattern recognition, speech analysis, and image identification. In an era marked by increasing digital vulnerabilities, this paper underscores the significance of ANNs as a powerful tool for fortifying our cyber infrastructure and protecting sensitive data. [ABSTRACT FROM AUTHOR]
Copyright of AIP Conference Proceedings is the property of American Institute of Physics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Role of artificial neural networks in fortifying cybersecurity: A review.
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  Data: <searchLink fieldCode="AR" term="%22Yadav%2C+Avantika%22">Yadav, Avantika</searchLink><br /><searchLink fieldCode="AR" term="%22Aggarwal%2C+Vishesh%22">Aggarwal, Vishesh</searchLink><br /><searchLink fieldCode="AR" term="%22Bansal%2C+Sulabh%22">Bansal, Sulabh</searchLink>
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  Data: AIP Conference Proceedings; 2025, Vol. 3253 Issue 1, p1-13, 13p
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  Data: <searchLink fieldCode="DE" term="%22Artificial+neural+networks%22">Artificial neural networks</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+technology%22">Digital technology</searchLink><br /><searchLink fieldCode="DE" term="%22Cyberterrorism%22">Cyberterrorism</searchLink><br /><searchLink fieldCode="DE" term="%22Anomaly+detection+%28Computer+security%29%22">Anomaly detection (Computer security)</searchLink><br /><searchLink fieldCode="DE" term="%22Internet+security%22">Internet security</searchLink><br /><searchLink fieldCode="DE" term="%22Intrusion+detection+systems+%28Computer+security%29%22">Intrusion detection systems (Computer security)</searchLink>
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  Data: The paper explores the indispensable role of Artificial Neural Networks (ANNs) in bolstering cybersecurity, with a particular emphasis on three domains: intrusion detection, malware classification, and anomaly detection. ANNs, renowned for their capacity to distinguish intricate patterns, are at the forefront of revolutionizing cyber defence mechanisms. Through an exhaustive examination of recent advancements and illustrative case studies, this paper underscores the efficacy of ANNs in countering evolving cyber threats. Moreover, it illuminates their broader implications in the realm of digital security, including applications in pattern recognition, speech analysis, and image identification. In an era marked by increasing digital vulnerabilities, this paper underscores the significance of ANNs as a powerful tool for fortifying our cyber infrastructure and protecting sensitive data. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of AIP Conference Proceedings is the property of American Institute of Physics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1063/5.0248254
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      – Code: eng
        Text: English
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        PageCount: 13
        StartPage: 1
    Subjects:
      – SubjectFull: Artificial neural networks
        Type: general
      – SubjectFull: Digital technology
        Type: general
      – SubjectFull: Cyberterrorism
        Type: general
      – SubjectFull: Anomaly detection (Computer security)
        Type: general
      – SubjectFull: Internet security
        Type: general
      – SubjectFull: Intrusion detection systems (Computer security)
        Type: general
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      – TitleFull: Role of artificial neural networks in fortifying cybersecurity: A review.
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            NameFull: Aggarwal, Vishesh
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            NameFull: Bansal, Sulabh
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            – D: 11
              M: 01
              Text: 2025
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              Y: 2025
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