44,469 research outputs found
Security of a biometric identity-based encryption scheme
Biometric identity-based encryption (Bio-IBE) is a kind of fuzzy
identity-based encryption (fuzzy IBE) where a ciphertext encrypted under an
identity w' can be decrypted using a secret key corresponding to the identity w
which is close to w' as measured by some metric. Recently, Yang et al. proposed
a constant-size Bio-IBE scheme and proved that it is secure against adaptive
chosen-ciphertext attack (CCA2) in the random oracle model. Unfortunately, in
this paper, we will show that their Bio-IBE scheme is even not chosen-plaintext
secure. Specifically, user w using his secret key is able to decrypt any
ciphertext encrypted under an identity w' even though w is not close to w'.Comment: Journal version of the paper will be appearing in International
Journal of Network Securit
Kinematic properties of the dual AGN system J0038+4128 based on long-slit spectroscopy
The study of kiloparsec-scale dual active galactic nuclei (AGN) will provide
important clues to understand the co-evolution between the host galaxies and
their central supermassive black holes undergoing a merging process. We present
long-slit spectroscopy of the J00384128, a kiloparsec-scale dual AGN
candidate discovered by Huang et al. recently, using the Yunnan Faint Object
Spectrograph and Camera (YFOSC) mounted on Li-Jiang 2.4-m telescope at Yunnan
observatories. From the long-slit spectra, we find that the average relative
line-of-sight (LOS) velocity between the two nuclei (J00384128N and
J00384128S) is about 150 km s. The LOS velocities of the emission
lines from the gas ionized by the nuclei activities and of the absorption lines
from stars governed by the host galaxies for different regions of the
J00384128 exhibit the same trend. The same velocities trend indicates that
the gaseous disks are co-rotating with the stellar disks in this ongoing merge
system. We also find several knots/giant HII regions scattered around the two
nuclei with strong star formation revealed by the observed line ratios from the
spectra. Those regions are also detected clearly in HST -band and HST
-band images.Comment: 12 pages, 5 figures, 3 tables, Research in Astronomy and Astrophysics
accepte
Reliable Energy-Efficient Routing Algorithm for Vehicle-Assisted Wireless Ad-Hoc Networks
We investigate the design of the optimal routing path in a moving vehicles
involved the internet of things (IoT). In our model, jammers exist that may
interfere with the information exchange between wireless nodes, leading to
worsened quality of service (QoS) in communications. In addition, the transmit
power of each battery-equipped node is constrained to save energy. We propose a
three-step optimal routing path algorithm for reliable and energy-efficient
communications. Moreover, results show that with the assistance of moving
vehicles, the total energy consumed can be reduced to a large extend. We also
study the impact on the optimal routing path design and energy consumption
which is caused by path loss, maximum transmit power constrain, QoS
requirement, etc.Comment: 6 pages, 5 figures, rejected by IEEE Globecom 2017,resubmit to IEEE
WCNC 201
STA: Spatial-Temporal Attention for Large-Scale Video-based Person Re-Identification
In this work, we propose a novel Spatial-Temporal Attention (STA) approach to
tackle the large-scale person re-identification task in videos. Different from
the most existing methods, which simply compute representations of video clips
using frame-level aggregation (e.g. average pooling), the proposed STA adopts a
more effective way for producing robust clip-level feature representation.
Concretely, our STA fully exploits those discriminative parts of one target
person in both spatial and temporal dimensions, which results in a 2-D
attention score matrix via inter-frame regularization to measure the
importances of spatial parts across different frames. Thus, a more robust
clip-level feature representation can be generated according to a weighted sum
operation guided by the mined 2-D attention score matrix. In this way, the
challenging cases for video-based person re-identification such as pose
variation and partial occlusion can be well tackled by the STA. We conduct
extensive experiments on two large-scale benchmarks, i.e. MARS and
DukeMTMC-VideoReID. In particular, the mAP reaches 87.7% on MARS, which
significantly outperforms the state-of-the-arts with a large margin of more
than 11.6%.Comment: Accepted as a conference paper at AAAI 201
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