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803 results on '"Yao, Yu"'

3. Hyper-Laplacian Regularized Multi-View Subspace Clustering With a New Weighted Tensor Nuclear Norm

Author

Qingjiang Xiao, Shiqiang Du, Jinmei Song, Yao Yu, and Yixuan Huang

Subjects
Multi-view subspace clustering, hyper-Laplacian graph, low-rank tensor, weighted tensor nuclear norm, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

In this paper, we present a hyper-Laplacian regularized method WHLR-MSC with a new weighted tensor nuclear norm for multi-view subspace clustering. Specifically, we firstly stack the subspace representation matrices of the different views into a tensor, which neatly captures the higher-order correlations between the different views. Secondly, in order to make all the singular values have different contributions in tensor nuclear norm based on tensor-Singular Value Decomposition (t-SVD), we use weighted tensor nuclear norm to constrain the constructed tensor, which can obtain the class discrimination information of the sample distribution more accurately. Third, from a geometric point of view, the data are usually sampled from a low-dimensional manifold embedded in a high-dimensional ambient space, the WHLR-MSC model uses hyper-Laplacian graph regularization to capture the local geometric structure of the data. An effective algorithm for solving the optimization problem of WHLR-MSC model is proposed. Extensive experiments on five benchmark image datasets show the effectiveness of our proposed WHLR-MSC method.

Published
2021
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38. A Robust Adversarial Network-Based End-to-End Communications System with Strong Generalization Ability Against Adversarial Attacks

Author

Dong, Yudi, Wang, Huaxia, and Yao, Yu-Dong

Subjects
Signal Processing (eess.SP), FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Signal Processing, Machine Learning (cs.LG)
Abstract

We propose a novel defensive mechanism based on a generative adversarial network (GAN) framework to defend against adversarial attacks in end-to-end communications systems. Specifically, we utilize a generative network to model a powerful adversary and enable the end-to-end communications system to combat the generative attack network via a minimax game. We show that the proposed system not only works well against white-box and black-box adversarial attacks but also possesses excellent generalization capabilities to maintain good performance under no attacks. We also show that our GAN-based end-to-end system outperforms the conventional communications system and the end-to-end communications system with/without adversarial training., 5 pages letter

Published
2022

44. The Intelligent Offense and Defense Mechanism of Internet of Vehicles Based on the Differential Game-IP Hopping

Author

Jingtang Luo, Yao Yu, Xiaolong Yang, Qifu Tyler Sun, Min Zhang, and Yun He

Subjects
General Computer Science, Computer science, business.industry, General Engineering, ComputingMilieux_LEGALASPECTSOFCOMPUTING, The Internet of vehicles, Adversary, IP hopping, Mechanism (engineering), symbols.namesake, privacy security, Nash equilibrium, Differential game, symbols, General Materials Science, Moving target defense, The Internet, lcsh:Electrical engineering. Electronics. Nuclear engineering, business, a differential game, moving target defense, lcsh:TK1-9971, Ip address, Computer network, Vulnerability (computing)
Abstract

The Road Side Unit (RSU) is an important part of the Internet of Vehicles (IoV), which collects a large number of user's privacy information and connects vehicles to the Internet. The current RSU is running with static configurations, and the adversary can get enough time to analyze the vulnerability of the RSU and launch attacks, which poses a huge threat to the privacy security of the IoV. Under this asymmetrical condition, the attackers occupy a predominant position, and it is difficult to fully defend. To solve the above asymmetry offense-defense problem, we adopt the moving target defense (MTD) to dynamically change the IP address of the RSU, which increases the difficulty of the attacker's attack. However, due to the unreasonable selection of the RSU's IP hopping frequency, it is difficult for the RSU's IP hopping to exert its defense effect or it may introduce excessive defense overheads. Given the above issue, we propose an intelligent offense and defense mechanism based on a differential game approach, which can adaptively adjust the RSU's IP hopping frequency and maximize its defense benefits. First, based on the offense and defense relationship, we model the RSU's IP hopping frequency intelligent arrangement as a differential game (i.e., IP hopping game) in which the attacker attempts to maximize his potential benefits, and the RSU manages to maximize its defense benefits. On this basis, we calculate a potential Nash equilibrium of the IP hopping game. Finally, simulation results show our proposed mechanism can adaptively adjust the RSU's IP hopping frequency according to the attack frequency and effectively defend attacks. Compared with the mechanisms with a fixed IP hopping frequency, our proposed mechanism can make up for the ineffectiveness of the fixed low-frequency IP hopping defense and avoid the excessive defense overheads of the fixed high-frequency IP hopping defense.

Published
2020

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