MalFam: a comprehensive study on malware families with state-of-the-art CNN architectures with classifications and XAI

MalFam: a comprehensive study on malware families with state-of-the-art CNN architectures with classifications and XAI

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Haque, Abid Hossain, Jahin, Labiba Ifrit, Katib, Sheikh Yasir Hossain, Tuhee, Saiwara Mahmud, Tasnia, Maisoon
Άλλοι συγγραφείς: Hossain, Muhammad Iqbal
Μορφή: Thesis
Γλώσσα:English
Έκδοση: Brac University 2024
Θέματα:
Explainable artificial intelligence (XAI)
Convolutional neural network (CNN)
DenseNet
Inception ResNet V2
VGG16
Comparative analysis
Neural networks (Computer science)
Artificial intelligence
Διαθέσιμο Online:http://hdl.handle.net/10361/22824

Διαδίκτυο

http://hdl.handle.net/10361/22824

Παρόμοια τεκμήρια