Wei Bai

Minzu University of China

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Co-Authors

Zhisong Pan

PLA Army Engineering University

Shiming Xia

PLA Army Engineering University

Shize Guo

Beijing University of Posts and Telecommunications

Junming Guo

Minzu University of China

Mingwu Xiang

Minzu University of China

Yang Lu

State Grid Corporation of China (China)

Lei Zhang

PLA Academy of Military Science

Jinkui Li

Ningxia Medical University General Hospital

Minhao Zhu

Southwest Jiaotong University

Xingyu Zhou

North University of China

Cooperative Institutions

PLA Army Engineering University

State Grid Corporation of China (China)

Southwest Jiaotong University

Yunnan University

Minzu University of China

Chinese Academy of Sciences

Shanghai Jiao Tong University

Zhejiang University

Beijing University of Posts and Telecommunications

Sichuan University

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A New Smart Router-Throttling Method to Mitigate DDoS Attacks

IEEE Access (2019)

Shiming Xia Shize Guo Wei Bai Junyang Qiu Hao Wei

The distributed denial of service (DDoS) attack is one of the most server threats to the current Internet and brings huge losses to society. Furthermore, it is challenging to defend DDoS due to the case that the DDoS traffic can appear similar to the legitimate ones. Router throttling is an accessible approach to defend DDoS attacks. Some existing router throttling methods dynamically adjust a given threshold value to keep the server load safe. However, these methods are not ideal as they exploit the information of the current time, so the perception of time series variations is poor. The DDoS problem can be seen as a Markov decision process (MDP). Multi-agent router throttling (MART) method based on hierarchical communication mechanism has been proposed to address this problem. However, each agent is independent with each other and has no communication among them, therefore, it is hard for them to collaborate to learn an ideal policy to defend DDoS. To solve this multi-agent partially observable MDP problem, we propose a centralized reinforcement learning router throttling method based on a centralized communication mechanism. Each router sends its own traffic reading to a central router, the central router then makes a decision for each router to choose the throttling rate. We also simulate the environment of the DDoS problem more realistic while modify the reward function of the MART to make the reward function of more coherent. To decrease the communication costs, we add a deep deterministic policy gradient network for each router to decide whether or not to send information to the central agent. The experiments validate that our proposed new smart router throttling method outperforms existing methods to the DDoS instruction response.

Bandwidth throttling

One-armed router

Trinoo

Core router

10.1109/access.2019.2930803

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Citations (19)

Cerium dioxide decorated hollow carbon fiber interlayer endowing lithium-sulfur batteries with excellent synergistic adsorption-catalysis towards polysulfides

Journal of Alloys and Compounds (2025)

Jinkui Li Dengbang Jiang L. Qu Shixiang Yuan Lijun Wang

10.1016/j.jallcom.2025.179160

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Citations (0)

Delay and Energy Aware Computation Task Offloading Strategy in Power Wireless Heterogeneous Networks

Mobile Networks and Management (2020)

Wei Bai Yang Lu Donglei Zhang Jawei Li Ping Ma

Mobile Edge Computing (MEC) is regarded as a promising technology that migrates cloud computing platforms with computing and storage capabilities to the edge of the wireless access network, enabling rich applications and services in close proximity to the mobile users (MUs). There are a lot of literatures that have studied computation offloading. Different from them, this paper performs a novel research on multi-level computation offloading taking account into the heterogeneity of computation tasks and computation resource backup pool, and introducing opportunistic networks in multi-access networks simultaneously. Firstly, we describe the computation offloading model. Then, we formulate the multi-level computation offloading problem as a Stackelberg game and demonstrate the existence of the game Nash equilibrium. In order to solve above problem, we design a global optimal algorithm based on game theory. Finally, the performance of the proposed algorithm is verified by comparing with other algorithms. Simulation results corroborate that the algorithm can not only decrease the energy consumption, but also is stable.

Computation offloading

Mobile Edge Computing

Stackelberg competition

Cloudlet

10.1007/978-3-030-64002-6_7

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Citations (0)

RMMDI: A Novel Framework for Role Mining Based on the Multi-Domain Information

Security and Communication Networks (2019)

Wei Bai Zhisong Pan Shize Guo Zhe Chen

Role-based access control (RBAC) is widely adopted in network security management, and role mining technology has been extensively used to automatically generate user roles from datasets in a bottom-up way. However, almost all role mining methods discover the user roles from existing user-permission assignments, which neglect the dependency relationships between user permissions. To extend the ability of role mining technology, this paper proposes a novel role mining framework based on multi-domain information. The framework estimates the similarity between different permissions based on the fundamental information in the physical, network, and digital domains and attaches interdependent permissions to the same role. Three simulated network scenarios with different multi-domain configurations are used to validate the effectiveness of our method. The experimental results show that the method can not only capture the interdependent relationships between permissions, but also detect user roles and permissions more reasonably.

Permission

Similarity (geometry)

10.1155/2019/8085303

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Citations (9)

Self-lubricating filler of grinding-stone toward alleviating rail grinding induced white etching layer

Tribology International (2022)

Wulin Zhang Changbao Liu Wei Bai Jun Zhang Xiaoqiang Fan

Filler (materials)

10.1016/j.triboint.2022.108169

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Citations (4)

The Technology of NAT and the Research of its Traverse Solutions

Wei Bai

The technology of NAT has been widely used in many domains, but the problem, how to solve the problem of NAT traverse, must be adverted in the application. This paper introduces the technology of NAT and the problem of NAT traverse, and shows the problem that would be met in the application for NAT traverse with a example, and ana- lyzes the solutions and its limitation which can be used to realize NAT traverse at present in the last.

Traverse

Nat

NAT traversal

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Citations (1)

Discover the Hidden Attack Path in Multi-domain Cyberspace Based on Reinforcement Learning

arXiv (Cornell University) (2021)

Lei Zhang Wei Bai Wei Li Shiming Xia Qibin Zheng

In this work, we present a learning-based approach to analysis cyberspace security configuration. Unlike prior methods, our approach has the ability to learn from past experience and improve over time. In particular, as we train over a greater number of agents as attackers, our method becomes better at discovering hidden attack paths for previously methods, especially in multi-domain cyberspace. To achieve these results, we pose discovering attack paths as a Reinforcement Learning (RL) problem and train an agent to discover multi-domain cyberspace attack paths. To enable our RL policy to discover more hidden attack paths and shorter attack paths, we ground representation introduction an multi-domain action select module in RL. Our objective is to discover more hidden attack paths and shorter attack paths by our proposed method, to analysis the weakness of cyberspace security configuration. At last, we designed a simulated cyberspace experimental environment to verify our proposed method, the experimental results show that our method can discover more hidden multi-domain attack paths and shorter attack paths than existing baseline methods.

10.48550/arxiv.2104.07195

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Citations (1)

Application of cost-sensitive LSTM in water level prediction for nuclear reactor pressurizer

Nuclear Engineering and Technology (2019)

Jin Zhang Xiaolong Wang Cheng Zhao Wei Bai Jun Shen

Applying an accurate parametric prediction model to identify abnormal or false pressurizer water levels (PWLs) is critical to the safe operation of marine pressurized water reactors (PWRs). Recently, deep-learning-based models have proved to be a powerful feature extractor to perform high-accuracy prediction. However, the effectiveness of models still suffers from two issues in PWL prediction: the correlations shifting over time between PWL and other feature parameters, and the example imbalance between fluctuation examples (minority) and stable examples (majority). To address these problems, we propose a cost-sensitive mechanism to facilitate the model to learn the feature representation of later examples and fluctuation examples. By weighting the standard mean square error loss with a cost-sensitive factor, we develop a Cost-Sensitive Long Short-Term Memory (CSLSTM) model to predict the PWL of PWRs. The overall performance of the CSLSTM is assessed by a variety of evaluation metrics with the experimental data collected from a marine PWR simulator. The comparisons with the Long Short-Term Memory (LSTM) model and the Support Vector Regression (SVR) model demonstrate the effectiveness of the CSLSTM.

Feature (linguistics)

Pressurizer

10.1016/j.net.2019.12.025

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Citations (30)

Incremental attribute based particle swarm optimization

Wei Bai Shi Cheng Emmanuel M. Tadjouddine Sheng-Uei Guan

An incremental-attribute based particle swarm optimization (IAPSO) which utilizes incremental learning strategy in function optimization is presented in this paper. Traditionally, particle swarm optimization (PSO) searches all the dimensions at the same time. Decomposition strategy is utilized in IAPSO to decompose the whole search space (D-dimension) into D numbers of one-dimensional space. In this approach, incremental learning strategy optimizes the function by searching the D-dimensional space one by one. Experimental results show that IAPSO gets more accurate and stable results than standard PSO in multimodal problems. IAPSO could avoid the "local optima", i.e., it has better "exploration" ability than standard PSO.

10.1109/icnc.2012.6234699

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Citations (12)

Research on the Identifier Technology of Electric Internet of Things Based on IPv6

Wei Bai Yang Lu Yaming Wen Tao Feng Xin Xv

The Internet of Things identifier is the basic supporting technology to realize the precise interaction between things. With the advancement of the construction of the electric Internet of Things, the number of various terminal devices connected to the network has increased sharply, and the types are complex and diverse. There are many types of existing electric equipment identifier systems, and their compatibility is poor. With the access of a large number of terminal devices of the electric Internet of Things, the amount of data in the identifier system is huge, which will cause huge operation and maintenance costs and resource occupation. In response to the above problems, this paper proposes an IPv6 identifier scheme that supports large-scale electric equipment of the electric Internet of Things, designs the registration and network access procedures of the identifier, and then proposes an optimization mechanism for electric Internet of Things communication service transmission based on the ipv6 identifier. Experiments have proved that the identifier scheme and transmission optimization mechanism proposed in this paper can effectively reduce the communication delay and packet loss rate of the business in the electric Internet of Things, and achieve efficient support for the electric Internet of Things business.

IPv6 address

10.1109/ictc51749.2021.9441625

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Citations (2)