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APENet:Advanced Cyber Security Attack Detection with Attentive Path-Encoding in IoT Networks Using SHAP Based Explainability

Muhammad Mujahid Fatima Alshannaq Shaha Al-Otaibi Tanzila Saba

Computers, Materials & Continua2026，Vol.89Issue(10)：P.807-822,16.

Computers, Materials & Continua2026，Vol.89Issue(10)：P.807-822,16.DOI:10.32604/cmc.2026.084273

APENet:Advanced Cyber Security Attack Detection with Attentive Path-Encoding in IoT Networks Using SHAP Based Explainability

Muhammad Mujahid ¹Fatima Alshannaq ¹Shaha Al-Otaibi ²Tanzila Saba¹

作者信息

1. Artificial Intelligence&Data Analytics Lab,CCIS,Prince Sultan University,Riyadh,Saudi Arabia
2. Department of Information Systems,College of Computer and Information Sciences,Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia
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摘要

关键词

Intrusion detection/cybersecurity/explainability/imbalance data/IoT/artificial intelligence

分类

信息技术与安全科学

引用本文复制引用

Muhammad Mujahid,Fatima Alshannaq,Shaha Al-Otaibi,Tanzila Saba..APENet:Advanced Cyber Security Attack Detection with Attentive Path-Encoding in IoT Networks Using SHAP Based Explainability[J].Computers, Materials & Continua,2026,89(10):P.807-822,16.

基金项目

funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2026R136),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia. （PNURSP2026R136）

Computers, Materials & Continua

ISSN：1546-2218

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