首页> 外文会议>IEEE/ACM International Conference on Software Engineering >A Large-Scale Empirical Study on the Effects of Code Obfuscations on Android Apps and Anti-Malware Products
【24h】

A Large-Scale Empirical Study on the Effects of Code Obfuscations on Android Apps and Anti-Malware Products

机译:大规模实证研究代码混淆对Android应用和反恶意软件产品的影响

获取原文

摘要

The Android platform has been the dominant mobile platform in recent years resulting in millions of apps and security threats against those apps. Anti-malware products aim to protect smartphone users from these threats, especially from malicious apps. However, malware authors use code obfuscation on their apps to evade detection by anti-malware products. To assess the effects of code obfuscation on Android apps and anti-malware products, we have conducted a large-scale empirical study that evaluates the effectiveness of the top anti-malware products against various obfuscation tools and strategies. To that end, we have obfuscated 3,000 benign apps and 3,000 malicious apps and generated 73,362 obfuscated apps using 29 obfuscation strategies from 7 open-source, academic, and commercial obfuscation tools. The findings of our study indicate that (1) code obfuscation significantly impacts Android anti-malware products; (2) the majority of anti-malware products are severely impacted by even trivial obfuscations; (3) in general, combined obfuscation strategies do not successfully evade anti-malware products more than individual strategies; (4) the detection of anti-malware products depend not only on the applied obfuscation strategy but also on the leveraged obfuscation tool; (5) anti-malware products are slow to adopt signatures of malicious apps; and (6) code obfuscation often results in changes to an app's semantic behaviors.
机译:近年来,Android平台一直是主导的移动平台,导致数百万的应用和安全威胁对这些应用程序。反恶意软件产品旨在保护智能手机用户免受这些威胁的影响,尤其是恶意应用程序。但是,恶意软件作者在其应用程序上使用代码混淆来逃避防恶意软件产品的检测。为评估代码混淆对Android应用程序和反恶意软件产品的影响,我们进行了大规模的实证研究,该研究评估了顶级反恶意软件产品对各种混淆工具和策略的有效性。为此,我们已经使用了7个开源,学术和商业混淆工具的29个混淆策略制定了3,000个良性应用和3,000个恶意应用程序,并使用了29个混淆策略生成了73,362个混淆的应用程序。我们的研究结果表明(1)代码混淆显着影响Android反恶意软件产品; (2)大多数反恶意软件产品甚至甚至琐碎的混淆都受到严重影响; (3)一般而言,组合的混淆策略不仅仅是逃避抗恶意软件产品,而不是个人策略; (4)防恶意软件产品的检测不仅取决于所应用的混淆策略,还取决于杠杆式混淆工具; (5)防恶意软件产品采用恶意应用的签名缓慢; (6)代码混淆通常会导致应用程序的语义行为的变化。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号