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Journal ArticleDOI

TaintDroid: An Information-Flow Tracking System for Realtime Privacy Monitoring on Smartphones

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TLDR
TaintDroid as mentioned in this paper is an efficient, system-wide dynamic taint tracking and analysis system capable of simultaneously tracking multiple sources of sensitive data by leveraging Android's virtualized execution environment.
Abstract
Today’s smartphone operating systems frequently fail to provide users with visibility into how third-party applications collect and share their private data. We address these shortcomings with TaintDroid, an efficient, system-wide dynamic taint tracking and analysis system capable of simultaneously tracking multiple sources of sensitive data. TaintDroid enables realtime analysis by leveraging Android’s virtualized execution environment. TaintDroid incurs only 32p performance overhead on a CPU-bound microbenchmark and imposes negligible overhead on interactive third-party applications. Using TaintDroid to monitor the behavior of 30 popular third-party Android applications, in our 2010 study we found 20 applications potentially misused users’ private information; so did a similar fraction of the tested applications in our 2012 study. Monitoring the flow of privacy-sensitive data with TaintDroid provides valuable input for smartphone users and security service firms seeking to identify misbehaving applications.

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Proceedings ArticleDOI

TaintDroid: an information-flow tracking system for realtime privacy monitoring on smartphones

TL;DR: Using TaintDroid to monitor the behavior of 30 popular third-party Android applications, this work found 68 instances of misappropriation of users' location and device identification information across 20 applications.
Proceedings ArticleDOI

Dissecting Android Malware: Characterization and Evolution

TL;DR: Systematize or characterize existing Android malware from various aspects, including their installation methods, activation mechanisms as well as the nature of carried malicious payloads reveal that they are evolving rapidly to circumvent the detection from existing mobile anti-virus software.
Proceedings ArticleDOI

DREBIN: Effective and Explainable Detection of Android Malware in Your Pocket.

TL;DR: DREBIN is proposed, a lightweight method for detection of Android malware that enables identifying malicious applications directly on the smartphone and outperforms several related approaches and detects 94% of the malware with few false alarms.
Proceedings ArticleDOI

FlowDroid: precise context, flow, field, object-sensitive and lifecycle-aware taint analysis for Android apps

TL;DR: FlowDroid is presented, a novel and highly precise static taint analysis for Android applications that successfully finds leaks in a subset of 500 apps from Google Play and about 1,000 malware apps from the VirusShare project.
Proceedings ArticleDOI

Android permissions: user attention, comprehension, and behavior

TL;DR: It is found that current Android permission warnings do not help most users make correct security decisions, however, a notable minority of users demonstrated both awareness of permission warnings and reasonable rates of comprehension.
References
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Proceedings ArticleDOI

TaintDroid: an information-flow tracking system for realtime privacy monitoring on smartphones

TL;DR: Using TaintDroid to monitor the behavior of 30 popular third-party Android applications, this work found 68 instances of misappropriation of users' location and device identification information across 20 applications.
Journal ArticleDOI

Language-based information-flow security

TL;DR: A structured view of research on information-flow security is given, particularly focusing on work that uses static program analysis to enforce information- flow policies, and some important open challenges are identified.
Journal ArticleDOI

A lattice model of secure information flow

TL;DR: The model provides a unifying view of all systems that restrict information flow, enables a classification of them according to security objectives, and suggests some new approaches to formulating the requirements of secure information flow among security classes.
Proceedings Article

Dynamic Taint Analysis for Automatic Detection, Analysis, and Signature Generation of Exploits on Commodity Software

TL;DR: TaintCheck as mentioned in this paper performs dynamic taint analysis by performing binary rewriting at run time, which can reliably detect most types of exploits and produces no false positives for any of the many different programs that were tested.
Proceedings ArticleDOI

JFlow: practical mostly-static information flow control

TL;DR: The new language JFlow is described, an extension to the Java language that adds statically-checked information flow annotations and provides several new features that make information flow checking more flexible and convenient than in previous models.
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