ICFICE 2019
Current Result Document :
| 한글제목(Korean Title) |
Change of malicious code API call pattern extraction using RNN and LSTM |
| 영문제목(English Title) |
Change of malicious code API call pattern extraction using RNN and LSTM |
| 저자(Author) |
Young-Bok Cho
Ki-Ju Kim
Jeong-Ah Ku
Sung-Hee Woo
|
| 원문수록처(Citation) |
VOL 11 NO. 01 PP. 0277 ~ 0280 (2019. 06) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
Existing malicious code and detection technologies analyze known malicious code with much time and effort, update it afterwards, detect malicious codes and prevent malicious codes from exploiting new and variant malicious codes. These malicious codes are rapidly changing into various variants to avoid detection of the vaccine. Among the dynamic analysis, methods used to more effectively detect and classify these strains of malware, malicious code family classifies a typical API call pattern by applying CNN. which it is used for natural language processing.
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| 키워드(Keyword) |
NN
Recurrent neural networks
API Call Patten
Malware
Malware API
Machine Learning
Deep Learning
LSTM
|
| 파일첨부 |
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