Earticle

초록

영어

AI technologies are being applied in many areas as well as in modern malware detection technologies. However, adversarial attacks to such AI-applied malware detection technologies become one of major problems as it is in computer vision with AI. There has been a lot of effort on developing adversary-robust malware detection technologies, but it remains immature yet. In this paper, we review the state-of-theart in AI-applied malware detection technologies to identify limitations and shortcomings. We also present some directions for future research enhancing robustness against adversarial attacks.

목차

Abstract
I. INTRODUCTION
II. BACKGROUND
A. AI-applied Malware Detection
B. Adversarial Attacks
III. TOWARD ADVERSARY-ROBUST MALWARE DETECTION
A. Adversarial Training
B. Adversarial Detection
IV. SHORTCOMINGS AND RESEARCH DIRECTIONS
V. CONCLUSION
REFERENCES

저자

• BooJoong Kang [ University of Southampton Southampton, United Kingdom ]

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