Taming Information-Stealing Smartphone Applications (on Android)

By Yajin Zhou, Xinwen Zhang, Xuxian Jiang, Vincent W. Freeh. Trust and Trustworthy Computing, 2011

463 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/75d70671eee7ead26c5636fe5d1e00fef5d993b3

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Citations in the corpus

TaintDroid (2010, background): “TISSA [Zhou et al. 2011], MockDroid [Beresford et al.”
These aren't the droids you're looking for: retrofitting android to protect data from imperious applications (2011, methodology): “present a similar system that uses shadow data to provide a“privacy mode” for untrusted applications [27].”
PScout: analyzing the Android permission specification (2012, unknown): “deny individual permissions for an application [31,37].”
RiskRanker: scalable and accurate zero-day android malware detection (2012, background): “A raft of follow-up work then sought to address theseinformation leaksby alteringtheframeworksinvolved: Apex [48],MockDroid [32],TISSA[57]andAppFence [46] all o.er extensions to the Android framework to provide .nergrained control over an app s access to potentially sensitive resources.”
Expectation and purpose: understanding users' mental models of mobile app privacy through crowdsourcing (2012, methodology): “This was quickly followed by research exploring solutions that offered users finer grain control over the use of these APIs [8-10].”
Systematic Detection of Capability Leaks in Stock Android Smartphones (2012, background): “The type and the volume of information kept in the phone naturally lead to various concerns [13, 14, 27, 42] about the safety of this private information, including the way it is managed and accessed.”
Modeling Users' Mobile App Privacy Preferences: Restoring Usability in a Sea of Permission Settings (2014, background): “Perhaps because of this research, iOS and Android have now started to offer their users somewhat finer control over mobile app permissions, enabling them for instance to toggle permissions on and off on an app-byapp basis (e.g. iOS5 and above, and also App Ops in Android 4.3).”
Leakiness and creepiness in app space: perceptions of privacy and mobile app use (2014, background): “Other researchers have argued that it is important to redesign the EULA to help users be more aware of what is going on in their smartphones [25,41].”
Detecting repackaged smartphone applications in third-party android marketplaces (2012, background): “Apex [37], MockDroid [6], and TISSA [44] enhance the Android infrastructure so that users can better control the access to specific resources or permission at runtime themselves.”
Dissecting Android Malware: Characterization and Evolution (2012, background): “Specifically, Apex [46], MockDroid [47], TISSA [48] and AppFence [49] extend the current Android framework to provide find-grained controls of system resources accessed by untrusted third-party apps.”
Uranine: Real-time Privacy Leakage Monitoring without System Modification for Android (2015, background): “A number of works additionally prevent access of private information or supply fake data to apps [5, 40, 23].”
MADAM: Effective and Efficient Behavior-based Android Malware Detection and Prevention (2018, background): “privacy leaking [7] [8], or privilege escalation (jail-breaking) [5] [9].”
Unsafe exposure analysis of mobile in-app advertisements (2012, background): “TISSA [33] similarly protects user information, but instead does so by modifying the Android framework to support user-de.ned information disclosure policies; sensitive APIs can return false information under such a scheme instead of simply failing.”
Hey, You, Get Off of My Market: Detecting Malicious Apps in Official and Alternative Android Markets (2012, background): “Apex [47], MockDroid [28], TISSA [54] and AppFence [42] revise the current Android framework or runtime to better provide fine-grained controls of resources accessed by third-party untrusted apps.”