Structural detection of android malware using embedded call graphs

This paper proposes a method for malware detection based on efficient embeddings of function call graphs with an explicit feature map inspired by a linear-time graph kernel that outperforms several related approaches and detects 89% of the malware with few false alarms, while also allowing to pin-point malicious code structures within Android applications.