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

Mahmoud M. Hammad, Joshua Garcia, S. Malek
{"title":"A Large-Scale Empirical Study on the Effects of Code Obfuscations on Android Apps and Anti-Malware Products","authors":"Mahmoud M. Hammad, Joshua Garcia, S. Malek","doi":"10.1145/3180155.3180228","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":6560,"journal":{"name":"2018 IEEE/ACM 40th International Conference on Software Engineering (ICSE)","volume":"23 1","pages":"421-431"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"56","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE/ACM 40th International Conference on Software Engineering (ICSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3180155.3180228","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 56

Abstract

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.
代码混淆对Android应用和反恶意软件产品影响的大规模实证研究
近年来,Android平台一直是占主导地位的移动平台,导致数以百万计的应用程序和针对这些应用的安全威胁。反恶意软件产品旨在保护智能手机用户免受这些威胁,尤其是来自恶意应用程序的威胁。然而,恶意软件的作者在他们的应用程序上使用代码混淆来逃避反恶意软件产品的检测。为了评估代码混淆对Android应用和反恶意软件产品的影响,我们进行了一项大规模的实证研究,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,我们混淆了3000个良性应用程序和3000个恶意应用程序,并使用来自7个开源,学术和商业混淆工具的29种混淆策略生成了73362个混淆应用程序。研究结果表明:(1)代码混淆显著影响Android反恶意软件产品;(2)大多数反恶意软件产品即使受到微不足道的混淆也会受到严重影响;(3)总的来说,组合混淆策略比单个策略更不能成功地逃避反恶意软件产品;(4)反恶意软件产品的检测不仅依赖于应用的混淆策略,还依赖于利用的混淆工具;(5)反恶意软件产品采用恶意应用签名的速度较慢;(6)代码混淆通常会导致应用的语义行为发生变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信