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

导出 LinkOut

翻译打印收藏纠错

第一作者： Umm-E-Hani,Tayyab

第一单位： Department of Computer & Information Sciences, Pakistan Institute of Engineering and Applied Sciences, Islamabad, Pakistan.

作者： Umm-E-Hani,Tayyab ^[1] ; Faiza Babar,Khan ^[1] ; Asifullah,Khan ^[2] ; Muhammad Hanif,Durad ^[1] ; Farrukh Aslam,Khan ^[3] ; Aftab,Ali ^[4]

作者单位： Department of Computer & Information Sciences, Pakistan Institute of Engineering and Applied Sciences, Islamabad, Pakistan. ^[1] Pattern Recognition Lab, Pakistan Institute of Engineering & Applied Sciences, Islamabad, Pakistan. ^[2] Center of Excellence in Information Assurance, King Saud University, Riyadh, Saudi Arabia. ^[3] School of Computing, Ulster University, Belfast, United Kingdom. ^[4]

关键词 Algorithms and analysis of algorithms Android malware Artificial intelligence Data mining and machine learning Data science Deep learning End-point protection Malware detection PE malware Zero-shot learning

DOI 10.7717/peerj-cs.2604

PMID 39896375

发布时间 2025-02-04

翻译满意度评价：

准确一般字义偏差语意偏离译文作用小提交

浏览0

PeerJ. Computer science

2024年10卷

e2604页

相似文献

中文期刊
外文期刊
学位论文
会议论文

检索历史清除

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

PeerJ. Computer science

相似文献

PeerJ. Computer science

相关期刊

参考文献：
指定格式：	NoteExpress EndNote RefWorks NoteFirst

检索历史 清除

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

PeerJ. Computer science

相似文献

PeerJ. Computer science

相关期刊

检索历史清除