Exploring the intersection of machine learning and explainable artificial intelligence: An analysis and validation of ML models through XAI for intrusion detection

Exploring the intersection of machine learning and explainable artificial intelligence: An analysis and validation of ML models through XAI for intrusion detection

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.

Bibliografiska uppgifter
Huvudupphovsmän: Rahman, Masroor, Navid, Reshad Karim, Hossain Bhuyain, Md Muballigh, Hasan, Farnaz Fawad, Nup, Naima Ahmed
Övriga upphovsmän: Hossain, Dr. Muhammad Iqbal
Materialtyp: Lärdomsprov
Språk:English
Publicerad: Brac University 2023
Ämnen:
Machine learning
Explainable Artificial Intelligence (XAI)
ToN-IoT
Windows OS
Data analysis
Intrusion detection
Neural networks (Computer science)
Artificial intelligence
Länkar:http://hdl.handle.net/10361/19351

Internet

http://hdl.handle.net/10361/19351

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