31,761 research outputs found
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
Verifying Policy Enforcers
Policy enforcers are sophisticated runtime components that can prevent
failures by enforcing the correct behavior of the software. While a single
enforcer can be easily designed focusing only on the behavior of the
application that must be monitored, the effect of multiple enforcers that
enforce different policies might be hard to predict. So far, mechanisms to
resolve interferences between enforcers have been based on priority mechanisms
and heuristics. Although these methods provide a mechanism to take decisions
when multiple enforcers try to affect the execution at a same time, they do not
guarantee the lack of interference on the global behavior of the system. In
this paper we present a verification strategy that can be exploited to discover
interferences between sets of enforcers and thus safely identify a-priori the
enforcers that can co-exist at run-time. In our evaluation, we experimented our
verification method with several policy enforcers for Android and discovered
some incompatibilities.Comment: Oliviero Riganelli, Daniela Micucci, Leonardo Mariani, and Yli\`es
Falcone. Verifying Policy Enforcers. Proceedings of 17th International
Conference on Runtime Verification (RV), 2017. (to appear
Controlling the Deficit: The Debate Continues
Looks at budget cuts proposed by House Republicans and the president's framework with respect to savings in healthcare spending, Social Security and other entitlement spending, and discretionary spending; tax policy; and the Budget Control Act
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