Earticle

초록

영어

Recently, as the number of new and variant malicious codes has increased exponentially, malware warnings are being issued to PC and smartphone users. Malware is becoming more and more intelligent. Efforts to protect personal information are becoming more and more important as social issues are used to stimulate the interest of PC users and allow users to directly download malicious codes. In this way, it is difficult to prevent malicious code because malicious code infiltrates in various forms. As a countermeasure to solve these problems, many studies are being conducted to apply deep learning. In this paper, we investigate and analyze various deep learning methods to detect and classify malware.

목차

Abstract
1. INTRODUCTION
2. MALWARE AND DEEP LEARNING METHOD
2.1 Malware and Deep Learning
2.2 Deep Learning Methods
3. DEEP LEARNING METHODS FOR MALWARE CLASSIFICATION AND DETECTION
3.1 Wang and Yiu[9]
3.2 David and Netanyahu[10]
3.3 Hardy et al.[11]
3.4 McLaughlin et al.[12]
3.5 Kolosnjaji et al.[13]
3.6 Shibahara et al.[14]
3.7 Yuan et al.[15]
4. ANALYSIS OF DEEP LEARNING METHODS TOOLS FOR MALWARE CLASSIFICATION AND DETECTION
5. CONCLUSION
ACKNOWLEDGEMENT
REFERENCES

키워드

저자

• Phil-Joo Moon [ Professor, Dept. of Information & Communications, Pyeongtaek University, Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Advanced Culture Technology(IJACT)

• 간기

  계간

• pISSN

  2288-7202

• eISSN

  2288-7318

• 수록기간

  2013~2025

• 등재여부

  KCI 등재

• 십진분류

  KDC 600 DDC 700