B-droid: A Static Taint Analysis Framework for Android Applications

被引:0
|
作者
ALmotairy, Rehab [1 ]
Daadaa, Yassine [1 ]
机构
[1] Al Imam Mohammad Ibn Saud Islamic Univ IMSIU, Coll Comp & Informat Sci, Riyadh, Saudi Arabia
关键词
Static analysis; taint analysis; fuzz testing; android applications; mobile malwares; data flow analysis;
D O I
10.14569/IJACSA.2021.0120150
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Android is currently the most popular smartphone operating system in use, with its success attributed to the large number of applications available from the Google Play Store. However, these contain issues relating to the storage of the user's sensitive data, including contacts, location, and the phone's unique identifier (DIED. Use of these applications therefore risks exfiltration of this data, including unauthorized tracking of users' behavior and violation of their privacy. Sensitive data leaks are currently detected with taint analysis approaches. This paper addresses these issues by proposing a new static taint analysis framework specifically for Android platforms, termed "B-Droid". B-Droid is based on static taint analysis using a large set of sources and sinks techniques, side by side with the fuzz testing concept, in order to detect privacy leaks, whether malicious or unintentional by analyses the behavior of Applications Under Test (AUTs). This has the potential to offer improved precision in comparison to earlier approaches. To ensure the quality of our analysis, we undertook an evaluation testing a variety of Android applications installed on a mobile after filtering according to the relevant permissions. We found that B-Droid efficiently detected five of the most prevalent commercial spyware applications on the market, as well as issuing an immediate warning to the user, so that they can decide not to continue with the AUTs. This paper provides a detailed analysis of this method, along with its implementation and results.
引用
收藏
页码:421 / 430
页数:10
相关论文
共 50 条
  • [41] Multi-source Taint Analysis Technique for Privacy Leak Detection of Android Apps
    Wang L.
    Zhou Q.
    He D.-J.
    Li L.
    Feng X.-B.
    Ruan Jian Xue Bao/Journal of Software, 2019, 30 (02): : 211 - 230
  • [42] Static analysis of Android programs
    Payet, Etienne
    Spoto, Fausto
    INFORMATION AND SOFTWARE TECHNOLOGY, 2012, 54 (11) : 1192 - 1201
  • [43] Security Analysis of IoT Frameworks using Static Taint Analysis
    Yavuz, Tuba
    Brant, Christopher
    CODASPY'22: PROCEEDINGS OF THE TWELVETH ACM CONFERENCE ON DATA AND APPLICATION SECURITY AND PRIVACY, 2022, : 203 - 213
  • [44] LLM-Powered Static Binary Taint Analysis
    Liu, Puzhuo
    Sun, Chengnian
    Zheng, Yaowen
    Feng, Xuan
    Qin, Chuan
    Wang, Yuncheng
    Xu, Zhenyang
    Li, Zhi
    Di, Peng
    Jiang, Yu
    Sun, Limin
    ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY, 2025, 34 (03)
  • [45] Application of static taint analysis in RASP protection strategy
    Ji Miao
    Yin Ming
    Zhou Huiying
    PROCEEDINGS OF THE 2022 INTERNATIONAL CONFERENCE ON CYBER SECURITY, CSW 2022, 2022, : 40 - 45
  • [46] EstiDroid: Estimate API Calls of Android Applications Using Static Analysis Technology
    Fan, Wenhao
    Zhang, Daishuai
    Chen, Ye
    Wu, Fan
    Liu, Yuan'an
    IEEE ACCESS, 2020, 8 (08): : 105384 - 105398
  • [47] Static program analysis assisted dynamic taint tracking for software vulnerability discovery
    Zhang, Ruoyu
    Huang, Shiqiu
    Qi, Zhengwei
    Guan, Haibing
    COMPUTERS & MATHEMATICS WITH APPLICATIONS, 2012, 63 (02) : 469 - 480
  • [48] Leveraging Historical Versions of Android Apps for Efficient and Precise Taint Analysis
    Cai, Haipeng
    Jenkins, John
    2018 IEEE/ACM 15TH INTERNATIONAL CONFERENCE ON MINING SOFTWARE REPOSITORIES (MSR), 2018, : 265 - 269
  • [49] Overview of Information Flow Tracking Techniques Based on Taint Analysis for Android
    Lokhande, Bhushan
    Dhavale, Sunita
    2014 INTERNATIONAL CONFERENCE ON COMPUTING FOR SUSTAINABLE GLOBAL DEVELOPMENT (INDIACOM), 2014, : 749 - 753
  • [50] Static and Dynamic Analysis of Android Malware
    Kapratwar, Ankita
    Di Troia, Fabio
    Stamp, Mark
    ICISSP: PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON INFORMATION SYSTEMS SECURITY AND PRIVACY, 2017, : 653 - 662