176 research outputs found
Ring Signature from Bonsai Tree: How to Preserve the Long-Term Anonymity
Signer-anonymity is the central feature of ring signatures, which enable a
user to sign messages on behalf of an arbitrary set of users, called the ring,
without revealing exactly which member of the ring actually generated the
signature. Strong and long-term signer-anonymity is a reassuring guarantee for
users who are hesitant to leak a secret, especially if the consequences of
identification are dire in certain scenarios such as whistleblowing. The notion
of \textit{unconditional anonymity}, which protects signer-anonymity even
against an infinitely powerful adversary, is considered for ring signatures
that aim to achieve long-term signer-anonymity. However, the existing
lattice-based works that consider the unconditional anonymity notion did not
strictly capture the security requirements imposed in practice, this leads to a
realistic attack on signer-anonymity.
In this paper, we present a realistic attack on the unconditional anonymity
of ring signatures, and formalize the unconditional anonymity model to strictly
capture it. We then propose a lattice-based ring signature construction with
unconditional anonymity by leveraging bonsai tree mechanism. Finally, we prove
the security in the standard model and demonstrate the unconditional anonymity
through both theoretical proof and practical experiments
Scholar-Friend Recommendation in Online Academic Community
The research project proposes a scholar-friend recommendation approach to help researchers find their scholar-friends by integrating multi-dimensional social networks
Learning Discriminative Representations for Skeleton Based Action Recognition
Human action recognition aims at classifying the category of human action
from a segment of a video. Recently, people have dived into designing GCN-based
models to extract features from skeletons for performing this task, because
skeleton representations are much more efficient and robust than other
modalities such as RGB frames. However, when employing the skeleton data, some
important clues like related items are also discarded. It results in some
ambiguous actions that are hard to be distinguished and tend to be
misclassified. To alleviate this problem, we propose an auxiliary feature
refinement head (FR Head), which consists of spatial-temporal decoupling and
contrastive feature refinement, to obtain discriminative representations of
skeletons. Ambiguous samples are dynamically discovered and calibrated in the
feature space. Furthermore, FR Head could be imposed on different stages of
GCNs to build a multi-level refinement for stronger supervision. Extensive
experiments are conducted on NTU RGB+D, NTU RGB+D 120, and NW-UCLA datasets.
Our proposed models obtain competitive results from state-of-the-art methods
and can help to discriminate those ambiguous samples. Codes are available at
https://github.com/zhysora/FR-Head.Comment: Accepted by CVPR2023. 10 pages, 5 figures, 5 table
High-Dimensional Quantum Key Distribution based on Multicore Fiber using Silicon Photonic Integrated Circuits
Quantum Key Distribution (QKD) provides an efficient means to exchange
information in an unconditionally secure way. Historically, QKD protocols have
been based on binary signal formats, such as two polarisation states, and the
transmitted information efficiency of the quantum key is intrinsically limited
to 1 bit/photon. Here we propose and experimentally demonstrate, for the first
time, a high-dimensional QKD protocol based on space division multiplexing in
multicore fiber using silicon photonic integrated lightwave circuits. We
successfully realized three mutually unbiased bases in a four-dimensional
Hilbert space, and achieved low and stable quantum bit error rate well below
both coherent attack and individual attack limits. Compared to previous
demonstrations, the use of a multicore fiber in our protocol provides a much
more efficient way to create high-dimensional quantum states, and enables
breaking the information efficiency limit of traditional QKD protocols. In
addition, the silicon photonic circuits used in our work integrate variable
optical attenuators, highly efficient multicore fiber couplers, and
Mach-Zehnder interferometers, enabling manipulating high-dimensional quantum
states in a compact and stable means. Our demonstration pave the way to utilize
state-of-the-art multicore fibers for long distance high-dimensional QKD, and
boost silicon photonics for high information efficiency quantum communications.Comment: Please see the complementary work arXiv:1610.01682 (2016
Robust utility maximization with intractable claims
We study a continuous-time expected utility maximization problem in which the
investor at maturity receives the value of a contingent claim in addition to
the investment payoff from the financial market. The investor knows nothing
about the claim other than its probability distribution, hence an ``intractable
claim''. In view of the lack of necessary information about the claim, we
consider a robust formulation to maximize her utility in the worst scenario. We
apply the quantile formulation to solve the problem, expressing the quantile
function of the optimal terminal investment income as the solution of certain
variational inequalities of ordinary differential equations. In the case of an
exponential utility, the problem reduces to a (non-robust) rank--dependent
utility maximization with probability distortion whose solution is available in
the literature
Evaluating emotional labor from a career management perspective
Emotional labor claims its significance as the key indicator both of the psychological health of contemporary employees, and the productivity of service-based businesses depending upon genuine emotional input of employees. By far, research on emotional labor of employees in an organizational context is still lacking. This study aims to explore the relationships among emotional labor, organizational support, career competences and career commitment to investigate how emotional labor interacts with the organizational context and affects the career management of the employee. Data were collected from a sample of 387 frontline employees working at two luxury hotel brands in China. Structural equation modeling (SEM) was utilized to estimate the relationships among the constructs. It is demonstrated by the findings that organizational support mediates positively on emotional labor, which exerts positive influences on career competences and career commitment. Sound handling of emotional labor, boosted by a supportive organizational environment, has been ascertained to positively predict long-term career paths of the employees at the company. This study provides insights into how the tourism and hospitality industry can optimize the functions of emotional labor for in enhancing service quality and customer satisfaction, as well as promoting the psychological well-being of the employees
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