Unsafe exposure analysis of mobile in-app advertisements

By Michael C. Grace, Wu Zhou, Xuxian Jiang, Ahmad-Reza Sadeghi. Wireless Network Security, 2012

538 citations recorded by the source corpus.

Subfields: Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/446b1664275bb9a5d28d07970c1971f1719ff7e3

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Citations in the corpus

Dissecting Android Malware: Characterization and Evolution (2012, background): “AdRisk [45] systematically identifies potential risks from in-app advertisement libraries.”
Reliable Third-Party Library Detection in Android and its Security Applications (2016, methodology): “Other approaches analyse private data exfiltration [14, 33] and security vulnerabilities in authentication/authorization SDKs [41].”
A Machine-learning Approach for Classifying and Categorizing Android Sources and Sinks (2014, background): “Unsurprisingly, as already found by different researchers [4], [31], [32] current malware is leaking privacy information such as location information or the address book.”
Effective inter-component communication mapping in Android with Epicc: an essential step towards holistic security analysis (2013, background): “perform a study of the dangers caused by 100 ad libraries found in a sample of 100,000 applications [20] through a reachability analysis on disassembled bytecode.”
*droid (2016, methodology): “However, this feature has also been used suspiciously by ad libraries [Grace et al. 2012].”
The Long-Standing Privacy Debate: Mobile Websites vs Mobile Apps (2017, background): “in [22], studied 100,000 apps and found that ad libraries are embedded in 52.”
Following Devil's Footprints: Cross-Platform Analysis of Potentially Harmful Libraries on Android and iOS (2016, background): “A lot of effort has been made to analyze and detect Android PHAs, most of which aims at detecting the code [37], [38], [39], [40], [41], [42], [43], [44], [45] for performing potentially harmful behaviors (e.g., stealing the user’s sensitive information), and protecting the Android system from…”
Brahmastra: Driving Apps to Test the Security of Third-Party Components (2014, methodology): “AdRisk [22] is a static analysis tool to examine advertising libraries integrated with Android apps.”
Amandroid: A Precise and General Inter-component Data Flow Analysis Framework for Security Vetting of Android Apps (2014, background): “There has been a long line of works on applying static analysis for Android security problems [6, 8, 11, 14, 17, 20, 23, 25].”
Free for All! Assessing User Data Exposure to Advertising Libraries on Android (2016, methodology): “To make things worse, some ad libraries load code dynamically, [18] which allow them to indirectly update their logic without dependency on the frequency of their host app’s updates.”
On the security relevance of weights in deep learning. (2020, background): “The idea that trusting libraries can be recognized as a threat [9, 1, 18] has also been recognized in ML [23, 40].”
Information Flow Analysis of Android Applications in DroidSafe (2015, background): “Sensitive information leaks, as implemented by malicious or misused code (such as advertising libraries) in Android applications, constitute one of the most prominent security threats to the Android ecosystem [1, 2].”
Vetting undesirable behaviors in android apps with permission use analysis (2013, background): “Considering these permissions are required by most legitimate advertising libraries [37], most users choose to grant these permissions without any idea about how these permissions will be used.”
SoK: Privacy on Mobile Devices – It’s Complicated (2016, background): “Call/SMS (Logs) [30] [33] [57] [56] [104][105] [106][107] [106][107]”
TaintDroid (2010, unknown): “Since this study, there have been many news stories and academic works providing further investigation [Enck et al. 2011; Grace et al. 2012; Hornyack et al. 2011].”
AppIntent: analyzing sensitive data transmission in android for privacy leakage detection (2013, background): “Given sensitive data transmission, AppIntent derives the input data and user interaction inputs that lead to the transmission.”
: Privacy on Mobile Devices – It ’ s Complicated (2016, background): “Call/SMS (Logs) [30] [33] [57] [56] [104][105] [106][107] [106][107]”
Android Security: A Survey of Issues, Malware Penetration, and Defenses (2015, background): “AdRisk [130] detected a few aggressive ad libraries performing targeted advertisements at the cost of the”