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关于安卓恶意软件检测工具对抗代码混淆技术的评估

On the evaluation of android malware detectors against code-obfuscation techniques.

作者信息

Nawaz Umair, Aleem Muhammad, Lin Jerry Chun-Wei

机构信息

Computer Sciences, National University of Computer and Emerging Sciences, Islamabad, Islamabad, Pakistan.

Computer Sciences, Western Norway University of Applied Sciences, Bergen, Norway.

出版信息

PeerJ Comput Sci. 2022 Jun 21;8:e1002. doi: 10.7717/peerj-cs.1002. eCollection 2022.

Abstract

The Android mobile platform is the most popular and dominates the cell phone market. With the increasing use of Android, malware developers have become active in circumventing security measures by using various obfuscation techniques. The obfuscation techniques are used to hide the malicious code in the Android applications to evade detection by anti-malware tools. Some attackers use the obfuscation techniques in isolation, while some attackers use a mixed approach (., employing multiple obfuscation techniques simultaneously). Therefore, it is crucial to analyze the impact of the different obfuscation techniques, both when they are used in isolation and when they are combined as hybrid techniques. Several studies have suggested that the obfuscation techniques may be more effective when used in a mixed pattern. However, in most of the related works, the obfuscation techniques used for analysis are either based on individual or a combination of primitive obfuscation techniques. In this work, we provide a comprehensive evaluation of anti-malware tools to gauge the impact of complex hybrid code-obfuscations techniques on malware detection capabilities of the prominent anti-malware tools. The evaluation results show that the inter-category-wise hybridized code obfuscation results in more evasion as compared to the individual or simple hybridized code obfuscations (using multiple and similar code obfuscations) which most of the existing related work employed for the evaluation. Obfuscation techniques significantly impact the detection rate of any anti-malware tool. The remarkable result ., almost 100% best detection rate is observed for the seven out of 10 tools when analyzed using the individual obfuscation techniques, four out of 10 tools on category-wise obfuscation, and not a single anti-malware tool attained full detection (., 100%) for inter-category obfuscations.

摘要

安卓移动平台是最受欢迎的,并且主导着手机市场。随着安卓系统使用的增加,恶意软件开发者通过使用各种混淆技术来规避安全措施变得活跃起来。这些混淆技术被用于在安卓应用中隐藏恶意代码,以逃避反恶意软件工具的检测。一些攻击者单独使用混淆技术,而一些攻击者则采用混合方法(例如,同时使用多种混淆技术)。因此,分析不同混淆技术单独使用以及作为混合技术组合使用时的影响至关重要。多项研究表明,混淆技术以混合模式使用时可能更有效。然而,在大多数相关工作中,用于分析的混淆技术要么基于单个原始混淆技术,要么是原始混淆技术的组合。在这项工作中,我们对反恶意软件工具进行了全面评估,以衡量复杂的混合代码混淆技术对知名反恶意软件工具的恶意软件检测能力的影响。评估结果表明,与大多数现有相关工作用于评估的单独或简单混合代码混淆(使用多种且类似的代码混淆)相比,跨类别混合代码混淆导致更多的逃避检测情况。混淆技术对任何反恶意软件工具的检测率都有显著影响。显著的结果是,当使用单独的混淆技术进行分析时,10个工具中有7个观察到几乎100%的最佳检测率,在按类别进行混淆时,10个工具中有4个达到该检测率,而对于跨类别混淆,没有一个反恶意软件工具能实现完全检测(即100%)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7694/9299270/1d01bc545c63/peerj-cs-08-1002-g001.jpg

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