Android Malware Detection via (Somewhat) Robust Irreversible Feature Transformations

• Published in: IEEE transactions on information forensics and security Vol. 15; pp. 3511 - 3525
• Main Authors: Han, Qian, Subrahmanian, V. S., Xiong, Yanhai
• Format: Journal Article
• Language: English
• Published: New York IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Android; Androids; Banking; Banking Trojans; Classification; Computer viruses; Feature extraction; feature transformation; Humanoid robots; machine learning; Malware; malware detection; Mobile operating systems; Robustness; rooting malware; Spyware; Transformations (mathematics)
• ISSN: 1556-6013; 1556-6021
• DOI: 10.1109/TIFS.2020.2975932

As the most widely used OS on earth, Android is heavily targeted by malicious hackers. Though much work has been done on detecting Android malware, hackers are becoming increasingly adept at evading ML classifiers. We develop <inline-formula> <tex-math notation="LaTeX">\textsf {FARM} </tex-math></inline-formula>, a Feature transformation based A nd R oid M alware detector. <inline-formula> <tex-math notation="LaTeX">\textsf {FARM} </tex-math></inline-formula> takes well-known features for Android malware detection and introduces three new types of feature transformations that transform these features irreversibly into a new feature domain. We first test <inline-formula> <tex-math notation="LaTeX">\textsf {FARM} </tex-math></inline-formula> on 6 Android classification problems separating goodware and "other malware" from 3 classes of malware: rooting malware, spyware, and banking trojans. We show that <inline-formula> <tex-math notation="LaTeX">\textsf {FARM} </tex-math></inline-formula> beats standard baselines when no attacks occur. Though we cannot guess all possible attacks that an adversary might use, we propose three realistic attacks on <inline-formula> <tex-math notation="LaTeX">\textsf {FARM} </tex-math></inline-formula> and show that <inline-formula> <tex-math notation="LaTeX">\textsf {FARM} </tex-math></inline-formula> is very robust to these attacks in all classification problems. Additionally, <inline-formula> <tex-math notation="LaTeX">\textsf {FARM} </tex-math></inline-formula> has automatically identified two malware samples which were not previously classified as rooting malware by any of the 61 anti-viruses on VirusTotal. These samples were reported to Google's Android Security Team who subsequently confirmed our findings.