47 research outputs found
Keeping Context In Mind: Automating Mobile App Access Control with User Interface Inspection
Recent studies observe that app foreground is the most striking component
that influences the access control decisions in mobile platform, as users tend
to deny permission requests lacking visible evidence. However, none of the
existing permission models provides a systematic approach that can
automatically answer the question: Is the resource access indicated by app
foreground? In this work, we present the design, implementation, and evaluation
of COSMOS, a context-aware mediation system that bridges the semantic gap
between foreground interaction and background access, in order to protect
system integrity and user privacy. Specifically, COSMOS learns from a large set
of apps with similar functionalities and user interfaces to construct generic
models that detect the outliers at runtime. It can be further customized to
satisfy specific user privacy preference by continuously evolving with user
decisions. Experiments show that COSMOS achieves both high precision and high
recall in detecting malicious requests. We also demonstrate the effectiveness
of COSMOS in capturing specific user preferences using the decisions collected
from 24 users and illustrate that COSMOS can be easily deployed on smartphones
as a real-time guard with a very low performance overhead.Comment: Accepted for publication in IEEE INFOCOM'201
Maximizing System Throughput Using Cooperative Sensing in Multi-Channel Cognitive Radio Networks
In Cognitive Radio Networks (CRNs), unlicensed users are allowed to access
the licensed spectrum when it is not currently being used by primary users
(PUs). In this paper, we study the throughput maximization problem for a
multi-channel CRN where each SU can only sense a limited number of channels. We
show that this problem is strongly NP-hard, and propose an approximation
algorithm with a factor at least where is a system
parameter reflecting the sensing capability of SUs across channels and their
sensing budgets. This performance guarantee is achieved by exploiting a nice
structural property of the objective function and constructing a particular
matching. Our numerical results demonstrate the advantage of our algorithm
compared with both a random and a greedy sensing assignment algorithm
Concurrent Channel Probing and Data Transmission in Full-duplex MIMO Systems
An essential step for achieving multiplexing gain in MIMO downlink systems is
to collect accurate channel state information (CSI) from the users.
Traditionally, CSIs have to be collected before any data can be transmitted.
Such a sequential scheme incurs a large feedback overhead, which substantially
limits the multiplexing gain especially in a network with a large number of
users. In this paper, we propose a novel approach to mitigate the feedback
overhead by leveraging the recently developed Full-duplex radios. Our approach
is based on the key observation that using Full-duplex radios, when the
base-station (BS) is collecting CSI of one user through the uplink channel, it
can use the downlink channel to simultaneously transmit data to other
(non-interfering) users for which CSIs are already known. By allowing
concurrent channel probing and data transmission, our scheme can potentially
achieve a higher throughput compared to traditional schemes using Half-duplex
radios. The new flexibility introduced by our scheme, however, also leads to
fundamental challenges in achieving throughout optimal scheduling. In this
paper, we make an initial effort to this important problem by considering a
simplified group interference model. We develop a throughput optimal scheduling
policy with complexity , where is the number of users and
is the number of user groups. To further reduce the complexity, we propose a
greedy policy with complexity that not only achieves at least 2/3
of the optimal throughput region, but also outperforms any feasible Half-duplex
solutions. We derive the throughput gain offered by Full-duplex under different
system parameters and show the advantage of our algorithms through numerical
studies.Comment: Technical repor