用于资源受限应用程序的基于CNN的轻量级恶意软件图像分类

IF 1.1 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Innovations in Systems and Software Engineering Pub Date : 2022-07-13 DOI:10.1007/s11334-022-00461-7

Ashlesha Hota, Subir Panja, A. Nag

引用次数: 0

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Lightweight CNN-based malware image classification for resource-constrained applications

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来源期刊

Innovations in Systems and Software Engineering COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

3.80

自引率

8.30%

发文量

期刊介绍： Innovations in Systems and Software Engineering: A NASA Journal addresses issues and innovations in Systems Engineering, Systems Integration, Software Engineering, Software Development and other related areas that are specifically of interest to NASA. The journal includes peer-reviewed world-class technical papers on topics of research, development and practice related to NASA''s missions and projects, topics of interest to NASA for future use, and topics describing problem areas for NASA together with potential solutions. Papers that do not address issues related to NASA are of course very welcome, provided that they address topics that NASA might like to consider for the future. Papers are solicited from NASA and government employees, contractors, NASA-supported academic and industrial partners, and non-NASA-supported academics and industrialists both in the USA and worldwide. The journal includes updates on NASA innovations, articles on NASA initiatives, papers looking at educational activities, and a State-of-the-Art section that gives an overview of specific topic areas in a comprehensive format written by an expert in the field.