Malware Detection Using Byte Streams of Different File Formats-Reference-Cited by-同舟云学术

Malware Detection Using Byte Streams of Different File Formats

Author:

Jeong Young-Seob¹^ORCID,Lee Sang-Min²,Kim Jong-Hyun²,Woo Jiyoung³^ORCID,Kang Ah Reum⁴^ORCID

Affiliation:

1. Department of Computer Engineering, Chungbuk National University, Cheongju-si, South Korea

2. Electronics and Telecommunications Research Institute, Daejeon, South Korea

3. Department of Big Data Engineering, Soonchunhyang University, Asan-si, South Korea

4. Department of Information Security, Pai Chai University, Daejeon, South Korea

Funder

Institute of Information and communications Technology Planning and Evaluation IITP

Chungbuk National University BK21 program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

Reference24 articles.

1. EMBER: An open dataset for training static PE malware machine learning models;anderson;arXiv 1804 04637,2018

4. Batch normalization: Accelerating deep network training by reducing internal covariate shift;ioffe;Proc 32nd Int Conf Mach Learn,2015

5. Dropout: A simple way to prevent neural networks from overfitting;srivastava;J Mach Learn Res,2014

Cited by 2 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