An Adaptable Ensemble Architecture for Malware Detection-Reference-Cited by-同舟云学术

An Adaptable Ensemble Architecture for Malware Detection

Published:2021-08-29 Issue: Volume: Page:647-659
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
Short-container-title:

Author:

Mane D. T.,Kumbharkar P. B.,Javheri Santosh B.,Moorthy Rahul

Publisher

Springer Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-3071-2_53

Reference21 articles.

1. AV-TEST GmbH, Malware Statistics (2020). https://www.av-test.org/en/statistics/malware.html. Accessed 13 Mar 2020

2. D. Lackey, Data Statistics (2019). https://blazon.online/data-marketing/how-much-data-do-we-create-every-day-the-mind-blowing-stats-everyone-should-read.html. Accessed 13 Mar 2020

3. K. He, X. Zhang, S. Ren, J. Sun, Deep residual learning for image recognition, in 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 27–30 June 2016

4. K. Simonyan, A. Zisserman, Very deep convolutional networks for large-scale image recognition. CoRR, abs/1409.1556 (2015)

5. V.P.V. Laxmi, M.S. Gaur, Survey on Malware detection methods, in Proceeding of the 2nd Annual India Software Engineering Conference, 23–26 Feb 2009

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Survey of Recent Advances in Deep Learning Models for Detecting Malware in Desktop and Mobile Platforms;ACM Computing Surveys;2024-01-22

2. Image-Based Malware Detection Using α-Cuts and Binary Visualisation;Applied Sciences;2023-04-06

3. Image-Based Plant Seedling Classification Using Ensemble Learning;Proceedings of the 6th International Conference on Advance Computing and Intelligent Engineering;2022-09-22