401 research outputs found
Sound and Precise Malware Analysis for Android via Pushdown Reachability and Entry-Point Saturation
We present Anadroid, a static malware analysis framework for Android apps.
Anadroid exploits two techniques to soundly raise precision: (1) it uses a
pushdown system to precisely model dynamically dispatched interprocedural and
exception-driven control-flow; (2) it uses Entry-Point Saturation (EPS) to
soundly approximate all possible interleavings of asynchronous entry points in
Android applications. (It also integrates static taint-flow analysis and least
permissions analysis to expand the class of malicious behaviors which it can
catch.) Anadroid provides rich user interface support for human analysts which
must ultimately rule on the "maliciousness" of a behavior.
To demonstrate the effectiveness of Anadroid's malware analysis, we had teams
of analysts analyze a challenge suite of 52 Android applications released as
part of the Auto- mated Program Analysis for Cybersecurity (APAC) DARPA
program. The first team analyzed the apps using a ver- sion of Anadroid that
uses traditional (finite-state-machine-based) control-flow-analysis found in
existing malware analysis tools; the second team analyzed the apps using a
version of Anadroid that uses our enhanced pushdown-based
control-flow-analysis. We measured machine analysis time, human analyst time,
and their accuracy in flagging malicious applications. With pushdown analysis,
we found statistically significant (p < 0.05) decreases in time: from 85
minutes per app to 35 minutes per app in human plus machine analysis time; and
statistically significant (p < 0.05) increases in accuracy with the
pushdown-driven analyzer: from 71% correct identification to 95% correct
identification.Comment: Appears in 3rd Annual ACM CCS workshop on Security and Privacy in
SmartPhones and Mobile Devices (SPSM'13), Berlin, Germany, 201
Enter Sandbox: Android Sandbox Comparison
Expecting the shipment of 1 billion Android devices in 2017, cyber criminals
have naturally extended their vicious activities towards Google's mobile
operating system. With an estimated number of 700 new Android applications
released every day, keeping control over malware is an increasingly challenging
task. In recent years, a vast number of static and dynamic code analysis
platforms for analyzing Android applications and making decision regarding
their maliciousness have been introduced in academia and in the commercial
world. These platforms differ heavily in terms of feature support and
application properties being analyzed. In this paper, we give an overview of
the state-of-the-art dynamic code analysis platforms for Android and evaluate
their effectiveness with samples from known malware corpora as well as known
Android bugs like Master Key. Our results indicate a low level of diversity in
analysis platforms resulting from code reuse that leaves the evaluated systems
vulnerable to evasion. Furthermore the Master Key bugs could be exploited by
malware to hide malicious behavior from the sandboxes.Comment: In Proceedings of the Third Workshop on Mobile Security Technologies
(MoST) 2014 (http://arxiv.org/abs/1410.6674
Mobile recommender apps with privacy management for accessible and usable technologies
The paper presents the preliminary results of an ongoing survey of the use of computers and mobile devices, interest in recommender apps and knowledge and concerns about privacy issues amongst English and Italian speaking disabled people. Participants were found to be regular users of computers and mobile devices for a range of applications. They were interested in recommender apps for household items, computer software and apps that met their accessibility and other requirements. They showed greater concerns about controlling access to personal data of different types than this data being retained by the computer or mobile device. They were also willing to make tradeoffs to improve device performance
An Empirical Study on Android-related Vulnerabilities
Mobile devices are used more and more in everyday life. They are our cameras,
wallets, and keys. Basically, they embed most of our private information in our
pocket. For this and other reasons, mobile devices, and in particular the
software that runs on them, are considered first-class citizens in the
software-vulnerabilities landscape. Several studies investigated the
software-vulnerabilities phenomenon in the context of mobile apps and, more in
general, mobile devices. Most of these studies focused on vulnerabilities that
could affect mobile apps, while just few investigated vulnerabilities affecting
the underlying platform on which mobile apps run: the Operating System (OS).
Also, these studies have been run on a very limited set of vulnerabilities.
In this paper we present the largest study at date investigating
Android-related vulnerabilities, with a specific focus on the ones affecting
the Android OS. In particular, we (i) define a detailed taxonomy of the types
of Android-related vulnerability; (ii) investigate the layers and subsystems
from the Android OS affected by vulnerabilities; and (iii) study the
survivability of vulnerabilities (i.e., the number of days between the
vulnerability introduction and its fixing). Our findings could help OS and apps
developers in focusing their verification & validation activities, and
researchers in building vulnerability detection tools tailored for the mobile
world
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