Document Type
Peer-Reviewed Article
Publication Date
2023
Abstract
Android platform security is an active area of research where malware detection techniques continuously evolve to identify novel malware and improve the timely and accurate detection of existing malware. Adversaries are constantly in charge of employing innovative techniques to avoid or prolong malware detection effectively. Past studies have shown that malware detection systems are susceptible to evasion attacks where adversaries can successfully bypass the existing security defenses and deliver the malware to the target system without being detected. The evolution of escape-resistant systems is an open research problem. This paper presents a detailed taxonomy and evaluation of Android-based malware evasion techniques deployed to circumvent malware detection. The study characterizes such evasion techniques into two broad categories, polymorphism and metamorphism, and analyses techniques used for stealth malware detection based on the malware’s unique characteristics. Furthermore, the article also presents a qualitative and systematic comparison of evasion detection frameworks and their detection methodologies for Android-based malware. Finally, the survey discusses open-ended questions and potential future directions for continued research in mobile malware detection.
DOI
10.3390/info14070374
Recommended Citation
Faruki, P., Bhan, R., Jain, V., Bhatia, S., El Madhoun, N., & Pamula, R. (2023). A survey and evaluation of android-based malware evasion techniques and detection frameworks. Information, 14(7), 374. Doi: 10.3390/info14070374
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Comments
This article belongs to the Special Issue Malware Behavior Analysis Applying Machine Learning.
Open Access under Creative Commons Attribution (CC BY) license