Adaptive Machine Learning-Based Threat Intelligence in Nuclear Facilities (AML-TIN): A Framework for Enhanced Cybersecurity in Nuclear Computing Environments

Alaa M. Alotaibi; Farid Ahmed; Sai Puppala; Sajedul Talukder; Syed Bahauddin Alam

doi:10.13182/T130-44913

Adaptive Machine Learning-Based Threat Intelligence in Nuclear Facilities (AML-TIN): A Framework for Enhanced Cybersecurity in Nuclear Computing Environments

Alaa M. Alotaibi, Farid Ahmed, Sai Puppala, Sajedul Talukder, Syed Bahauddin Alam

Research output: Contribution to journal › Conference article › peer-review

Original language	English (US)
Pages (from-to)	258-260
Number of pages	3
Journal	Transactions of the American Nuclear Society
Volume	130
Issue number	1
DOIs	https://doi.org/10.13182/T130-44913
State	Published - 2024
Event	2024 Annual Conference on Transactions of the American Nuclear Society, ANS 2024 - Las Vegas, United States Duration: Jun 16 2024 → Jun 19 2024

ASJC Scopus subject areas

Nuclear Energy and Engineering
Safety, Risk, Reliability and Quality

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10.13182/T130-44913

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Adaptive Machine Learning-Based Threat Intelligence in Nuclear Facilities (AML-TIN): A Framework for Enhanced Cybersecurity in Nuclear Computing Environments. / Alotaibi, Alaa M.; Ahmed, Farid; Puppala, Sai et al.
In: Transactions of the American Nuclear Society, Vol. 130, No. 1, 2024, p. 258-260.

Research output: Contribution to journal › Conference article › peer-review

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author = "Alotaibi, {Alaa M.} and Farid Ahmed and Sai Puppala and Sajedul Talukder and Alam, {Syed Bahauddin}",

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Adaptive Machine Learning-Based Threat Intelligence in Nuclear Facilities (AML-TIN): A Framework for Enhanced Cybersecurity in Nuclear Computing Environments

ASJC Scopus subject areas

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Library availability

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