5,687 research outputs found
Device-Centric Monitoring for Mobile Device Management
The ubiquity of computing devices has led to an increased need to ensure not
only that the applications deployed on them are correct with respect to their
specifications, but also that the devices are used in an appropriate manner,
especially in situations where the device is provided by a party other than the
actual user. Much work which has been done on runtime verification for mobile
devices and operating systems is mostly application-centric, resulting in
global, device-centric properties (e.g. the user may not send more than 100
messages per day across all applications) being difficult or impossible to
verify. In this paper we present a device-centric approach to runtime verify
the device behaviour against a device policy with the different applications
acting as independent components contributing to the overall behaviour of the
device. We also present an implementation for Android devices, and evaluate it
on a number of device-centric policies, reporting the empirical results
obtained.Comment: In Proceedings FESCA 2016, arXiv:1603.0837
In-Vivo Bytecode Instrumentation for Improving Privacy on Android Smartphones in Uncertain Environments
In this paper we claim that an efficient and readily applicable means to
improve privacy of Android applications is: 1) to perform runtime monitoring by
instrumenting the application bytecode and 2) in-vivo, i.e. directly on the
smartphone. We present a tool chain to do this and present experimental results
showing that this tool chain can run on smartphones in a reasonable amount of
time and with a realistic effort. Our findings also identify challenges to be
addressed before running powerful runtime monitoring and instrumentations
directly on smartphones. We implemented two use-cases leveraging the tool
chain: BetterPermissions, a fine-grained user centric permission policy system
and AdRemover an advertisement remover. Both prototypes improve the privacy of
Android systems thanks to in-vivo bytecode instrumentation.Comment: ISBN: 978-2-87971-111-
CamFlow: Managed Data-sharing for Cloud Services
A model of cloud services is emerging whereby a few trusted providers manage
the underlying hardware and communications whereas many companies build on this
infrastructure to offer higher level, cloud-hosted PaaS services and/or SaaS
applications. From the start, strong isolation between cloud tenants was seen
to be of paramount importance, provided first by virtual machines (VM) and
later by containers, which share the operating system (OS) kernel. Increasingly
it is the case that applications also require facilities to effect isolation
and protection of data managed by those applications. They also require
flexible data sharing with other applications, often across the traditional
cloud-isolation boundaries; for example, when government provides many related
services for its citizens on a common platform. Similar considerations apply to
the end-users of applications. But in particular, the incorporation of cloud
services within `Internet of Things' architectures is driving the requirements
for both protection and cross-application data sharing.
These concerns relate to the management of data. Traditional access control
is application and principal/role specific, applied at policy enforcement
points, after which there is no subsequent control over where data flows; a
crucial issue once data has left its owner's control by cloud-hosted
applications and within cloud-services. Information Flow Control (IFC), in
addition, offers system-wide, end-to-end, flow control based on the properties
of the data. We discuss the potential of cloud-deployed IFC for enforcing
owners' dataflow policy with regard to protection and sharing, as well as
safeguarding against malicious or buggy software. In addition, the audit log
associated with IFC provides transparency, giving configurable system-wide
visibility over data flows. [...]Comment: 14 pages, 8 figure
PlaceRaider: Virtual Theft in Physical Spaces with Smartphones
As smartphones become more pervasive, they are increasingly targeted by
malware. At the same time, each new generation of smartphone features
increasingly powerful onboard sensor suites. A new strain of sensor malware has
been developing that leverages these sensors to steal information from the
physical environment (e.g., researchers have recently demonstrated how malware
can listen for spoken credit card numbers through the microphone, or feel
keystroke vibrations using the accelerometer). Yet the possibilities of what
malware can see through a camera have been understudied. This paper introduces
a novel visual malware called PlaceRaider, which allows remote attackers to
engage in remote reconnaissance and what we call virtual theft. Through
completely opportunistic use of the camera on the phone and other sensors,
PlaceRaider constructs rich, three dimensional models of indoor environments.
Remote burglars can thus download the physical space, study the environment
carefully, and steal virtual objects from the environment (such as financial
documents, information on computer monitors, and personally identifiable
information). Through two human subject studies we demonstrate the
effectiveness of using mobile devices as powerful surveillance and virtual
theft platforms, and we suggest several possible defenses against visual
malware
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