Deep Learning for Android Malware Defenses: a Systematic Literature Review. (arXiv:2103.05292v2 [cs.CR] UPDATED)

Malicious applications (particularly those targeting the Android platform)
pose a serious threat to developers and end-users. Numerous research efforts
have been devoted to developing effective approaches to defend against Android
malware. However, given the explosive growth of Android malware and the
continuous advancement of malicious evasion technologies like obfuscation and
reflection, Android malware defense approaches based on manual rules or
traditional machine learning may not be effective. In recent years, a dominant
research field called deep learning (DL), which provides …

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