A Survey and Evaluation of Android-Based Malware Evasion Techniques and Detection Frameworks

Inf. Comput. Pub Date : 2023-06-30 DOI:10.3390/info14070374
Parvez Faruki, R. Bhan, V. Jain, Sajal Bhatia, Nour El Madhoun, Raj Pamula
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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.
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基于android的恶意软件规避技术和检测框架的调查与评估
Android平台安全是一个活跃的研究领域,恶意软件检测技术不断发展,以识别新的恶意软件,并提高对现有恶意软件的及时和准确检测。攻击者不断负责采用创新技术来有效地避免或延长恶意软件检测。过去的研究表明,恶意软件检测系统容易受到逃避攻击,攻击者可以成功绕过现有的安全防御,将恶意软件传递到目标系统而不被检测到。防逃逸系统的演化是一个开放的研究问题。本文介绍了基于android的恶意软件规避技术的详细分类和评估,这些技术用于规避恶意软件检测。该研究将这种规避技术分为两大类,多态性和变形,并分析了基于恶意软件独特特征的隐形恶意软件检测技术。此外,本文还对基于android的恶意软件的规避检测框架及其检测方法进行了定性和系统的比较。最后,调查讨论了开放式问题和移动恶意软件检测持续研究的潜在未来方向。
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