A situation based predictive approach for cybersecurity intrusion detection and prevention using machine learning and deep learning algorithms in wireless sensor networks of industry 4.0

Fatima Al-Quayed; Zulfiqar Ahmad; Mamoona Humayun

doi:10.1109/ACCESS.2024.3372187

A situation based predictive approach for cybersecurity intrusion detection and prevention using machine learning and deep learning algorithms in wireless sensor networks of industry 4.0

Fatima Al-Quayed
, Zulfiqar Ahmad
, Mamoona Humayun

School of Arts, Humanities, and Social Sciences

Research output: Contribution to journal › Article › peer-review

Original language	Undefined
Journal	IEEE Access
DOIs	https://doi.org/10.1109/ACCESS.2024.3372187
Publication status	Published - 2024

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10.1109/ACCESS.2024.3372187

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title = "A situation based predictive approach for cybersecurity intrusion detection and prevention using machine learning and deep learning algorithms in wireless sensor networks of industry 4.0",

author = "Fatima Al-Quayed and Zulfiqar Ahmad and Mamoona Humayun",

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language = "Undefined",

journal = "IEEE Access",

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T1 - A situation based predictive approach for cybersecurity intrusion detection and prevention using machine learning and deep learning algorithms in wireless sensor networks of industry 4.0

AU - Al-Quayed, Fatima

AU - Ahmad, Zulfiqar

AU - Humayun, Mamoona

PY - 2024

Y1 - 2024

UR - https://doi.org/10.1109/ACCESS.2024.3372187

U2 - 10.1109/ACCESS.2024.3372187

DO - 10.1109/ACCESS.2024.3372187

M3 - Article

JO - IEEE Access

JF - IEEE Access

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A situation based predictive approach for cybersecurity intrusion detection and prevention using machine learning and deep learning algorithms in wireless sensor networks of industry 4.0

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