Z
Zheng Yan
Researcher at Shanghai Jiao Tong University
Publications - 490
Citations - 12887
Zheng Yan is an academic researcher from Shanghai Jiao Tong University. The author has contributed to research in topics: Computer science & Cloud computing. The author has an hindex of 47, co-authored 420 publications receiving 8786 citations. Previous affiliations of Zheng Yan include Helsinki University of Technology & Huawei.
Papers
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Proceedings ArticleDOI
A Security Formal Model for Multiple Channels Communication
TL;DR: A multiple channel syntax and the corresponding semantic rules for the security analysis of heterogeneous networks are defined based on the basic syntax of Applied Pi Calculus and the results present that the method can support the formal security evaluation of heterogeneity networks.
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ADCaDeM: A Novel Method of Calculating Attack Damage Based on Differential Manifolds
TL;DR: Wang et al. as mentioned in this paper proposed a method called ADCaDeM to enable quantitative attack damage calculation based on a differential manifold, which can calculate attack behavioral utility in a physical way, such as computing the work done in physics.
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Improving proximal policy optimization with alpha divergence
TL;DR: The alpha-PPO as mentioned in this paper reformulates the primary PPO as a linearly combined form to control the trade-off between two terms, and replaces the Kullback-Leibler divergence with a parametric alpha divergence to measure the difference of two policies more effectively.
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Supplementary Damping Control of PSS and HVDC-SDC for Low-Frequency Oscillation Suppression in AC/DC Inter-connected System
TL;DR: In this paper , the mechanism of HVDC supplementary damping controller (HVDC-SDC) to enhance the damping of power system, and establishes the low-frequency oscillation suppression scheme in AC/DC inter-connected system.
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TrustGuard: GNN-based Robust and Explainable Trust Evaluation with Dynamicity Support
TL;DR: Li et al. as mentioned in this paper proposed TrustGuard, a GNN-based accurate trust evaluation model that supports trust dynamicity, is robust against typical attacks, and provides explanations through visualization, which can explain its evaluation results by visualizing both spatial and temporal views.