9,912 research outputs found
ACMiner: Extraction and Analysis of Authorization Checks in Android's Middleware
Billions of users rely on the security of the Android platform to protect
phones, tablets, and many different types of consumer electronics. While
Android's permission model is well studied, the enforcement of the protection
policy has received relatively little attention. Much of this enforcement is
spread across system services, taking the form of hard-coded checks within
their implementations. In this paper, we propose Authorization Check Miner
(ACMiner), a framework for evaluating the correctness of Android's access
control enforcement through consistency analysis of authorization checks.
ACMiner combines program and text analysis techniques to generate a rich set of
authorization checks, mines the corresponding protection policy for each
service entry point, and uses association rule mining at a service granularity
to identify inconsistencies that may correspond to vulnerabilities. We used
ACMiner to study the AOSP version of Android 7.1.1 to identify 28
vulnerabilities relating to missing authorization checks. In doing so, we
demonstrate ACMiner's ability to help domain experts process thousands of
authorization checks scattered across millions of lines of code
ACMiner: Extraction and Analysis of Authorization Checks inAndroid’s Middleware
Billions of users rely on the security of the Android platform to protect phones, tablets, and many different types of consumer electronics. While Android’s permission model is well studied, the enforcementof the protection policy has received relatively little attention. Much of this enforcement is spread across system services,taking the form of hard-coded checks within their implementations.In this paper, we propose Authorization Check Miner (ACMiner),a framework for evaluating the correctness of Android’s access control enforcement through consistency analysis of authorization checks. ACMiner combines program and text analysis techniques to generate a rich set of authorization checks, mines the corresponding protection policy for each service entry point, and uses association rule mining at a service granularity to identify inconsistencies that may correspond to vulnerabilities. We used ACMiner to study the AOSP version of Android 7.1.1 to identify 28 vulnerabilities relating to missing authorization checks. In doing so, we demonstrate ACMiner’s ability to help domain experts process thousands of authorization checks scattered across millions of lines of code
Policy Enforcement with Proactive Libraries
Software libraries implement APIs that deliver reusable functionalities. To
correctly use these functionalities, software applications must satisfy certain
correctness policies, for instance policies about the order some API methods
can be invoked and about the values that can be used for the parameters. If
these policies are violated, applications may produce misbehaviors and failures
at runtime. Although this problem is general, applications that incorrectly use
API methods are more frequent in certain contexts. For instance, Android
provides a rich and rapidly evolving set of APIs that might be used incorrectly
by app developers who often implement and publish faulty apps in the
marketplaces. To mitigate this problem, we introduce the novel notion of
proactive library, which augments classic libraries with the capability of
proactively detecting and healing misuses at run- time. Proactive libraries
blend libraries with multiple proactive modules that collect data, check the
correctness policies of the libraries, and heal executions as soon as the
violation of a correctness policy is detected. The proactive modules can be
activated or deactivated at runtime by the users and can be implemented without
requiring any change to the original library and any knowledge about the
applications that may use the library. We evaluated proactive libraries in the
context of the Android ecosystem. Results show that proactive libraries can
automati- cally overcome several problems related to bad resource usage at the
cost of a small overhead.Comment: O. Riganelli, D. Micucci and L. Mariani, "Policy Enforcement with
Proactive Libraries" 2017 IEEE/ACM 12th International Symposium on Software
Engineering for Adaptive and Self-Managing Systems (SEAMS), Buenos Aires,
Argentina, 2017, pp. 182-19
ConXsense - Automated Context Classification for Context-Aware Access Control
We present ConXsense, the first framework for context-aware access control on
mobile devices based on context classification. Previous context-aware access
control systems often require users to laboriously specify detailed policies or
they rely on pre-defined policies not adequately reflecting the true
preferences of users. We present the design and implementation of a
context-aware framework that uses a probabilistic approach to overcome these
deficiencies. The framework utilizes context sensing and machine learning to
automatically classify contexts according to their security and privacy-related
properties. We apply the framework to two important smartphone-related use
cases: protection against device misuse using a dynamic device lock and
protection against sensory malware. We ground our analysis on a sociological
survey examining the perceptions and concerns of users related to contextual
smartphone security and analyze the effectiveness of our approach with
real-world context data. We also demonstrate the integration of our framework
with the FlaskDroid architecture for fine-grained access control enforcement on
the Android platform.Comment: Recipient of the Best Paper Awar
Automatically Securing Permission-Based Software by Reducing the Attack Surface: An Application to Android
A common security architecture, called the permission-based security model
(used e.g. in Android and Blackberry), entails intrinsic risks. For instance,
applications can be granted more permissions than they actually need, what we
call a "permission gap". Malware can leverage the unused permissions for
achieving their malicious goals, for instance using code injection. In this
paper, we present an approach to detecting permission gaps using static
analysis. Our prototype implementation in the context of Android shows that the
static analysis must take into account a significant amount of
platform-specific knowledge. Using our tool on two datasets of Android
applications, we found out that a non negligible part of applications suffers
from permission gaps, i.e. does not use all the permissions they declare
The Transitivity of Trust Problem in the Interaction of Android Applications
Mobile phones have developed into complex platforms with large numbers of
installed applications and a wide range of sensitive data. Application security
policies limit the permissions of each installed application. As applications
may interact, restricting single applications may create a false sense of
security for the end users while data may still leave the mobile phone through
other applications. Instead, the information flow needs to be policed for the
composite system of applications in a transparent and usable manner. In this
paper, we propose to employ static analysis based on the software architecture
and focused data flow analysis to scalably detect information flows between
components. Specifically, we aim to reveal transitivity of trust problems in
multi-component mobile platforms. We demonstrate the feasibility of our
approach with Android applications, although the generalization of the analysis
to similar composition-based architectures, such as Service-oriented
Architecture, can also be explored in the future
Static Analysis for Extracting Permission Checks of a Large Scale Framework: The Challenges And Solutions for Analyzing Android
A common security architecture is based on the protection of certain
resources by permission checks (used e.g., in Android and Blackberry). It has
some limitations, for instance, when applications are granted more permissions
than they actually need, which facilitates all kinds of malicious usage (e.g.,
through code injection). The analysis of permission-based framework requires a
precise mapping between API methods of the framework and the permissions they
require. In this paper, we show that naive static analysis fails miserably when
applied with off-the-shelf components on the Android framework. We then present
an advanced class-hierarchy and field-sensitive set of analyses to extract this
mapping. Those static analyses are capable of analyzing the Android framework.
They use novel domain specific optimizations dedicated to Android.Comment: IEEE Transactions on Software Engineering (2014). arXiv admin note:
substantial text overlap with arXiv:1206.582
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