ISAnWin: inductive generalized zero-shot learning using deep CNN for malware detection across windows and android platforms

ISAnWin: inductive generalized zero-shot learning using deep CNN for malware detection across windows and android platforms

Effective malware detection is critical to safeguarding digital ecosystems from evolving cyber threats. However, the scarcity of labeled training data, particularly for cross-family malware detection, poses a significant challenge. This research proposes a novel architecture ConvNet-6 to be used in...

Full description

Saved in:
Bibliographic Details
Main Authors: Umm-e-Hani Tayyab, Faiza Babar Khan, Asifullah Khan, Muhammad Hanif Durad, Farrukh Aslam Khan, Aftab Ali
Format: Article
Language:English
Published: PeerJ Inc. 2024-12-01
Series:PeerJ Computer Science
Subjects:
Malware detection
PE malware
Android malware
End-point protection
Artificial intelligence
Deep learning
Online Access:https://peerj.com/articles/cs-2604.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items