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A New Encrypted Traffic Identification Model Based on VAE-LSTM-DRN

computers, Materials & Continua 2024年第1期78卷 569-588页

作者： Haizhen Wang Jinying Yan Na Jia College of Computer and Control Engineering Qiqihar UniversityQiqihar161006China Heilongjiang Key Laboratory of Big Data Network Security Detection and Analysis Qiqihar UniversityQiqiharChina

Encrypted traffic identification pertains to the precise acquisition and categorization of data from traffic datasets containing imbalanced and obscured *** extraction of encrypted traffic attributes and their subsequent identification presents a formidable *** existing models have predominantly relied on direct extraction of encrypted traffic data from imbalanced datasets,with the dataset’s imbalance significantly affecting the model’s *** the present study,a new model,referred to as UD-VLD(Unbalanced Dataset-VAE-LSTM-DRN),was proposed to address above *** proposed model is an encrypted traffic identification model for handling unbalanced *** encoder of the variational autoencoder(VAE)is combined with the decoder and Long-short term Memory(LSTM)in UD-VLD model to realize the data enhancement processing of the original unbalanced *** enhanced data is processed by transforming the deep residual network(DRN)to address neural network gradient-related ***,the data is classified and *** UD-VLD model integrates the related techniques of deep learning into the encrypted traffic recognition technique,thereby solving the processing problem for unbalanced *** UD-VLD model was tested using the publicly available Tor dataset and VPN *** UD-VLD model is evaluated against other comparative models in terms of accuracy,loss rate,precision,recall,F1-score,total time,and ROC *** results reveal that the UD-VLD model exhibits better performance in both binary and multi classification,being higher than other encrypted traffic recognition models that exist for unbalanced ***,the evaluation performance indicates that the UD-VLD model effectivelymitigates the impact of unbalanced data on traffic *** can serve as a novel solution for encrypted traffic identification.

关键词： Data enhancement LSTM deep residual network VAE

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Leveraging Data Fitting and Trust Assessment to Improve the Security of Industrial Networks 43

Leveraging Data Fitting and Trust Assessment to Improve the ...

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43rd Chinese control Conference, CCC 2024

作者： Zhang, Heng Wang, Yinchu Xue, Yawen Deng, Ruilong Li, Hongran Zhang, Jian Jiangsu Ocean University School of Computer Engineering China Zhejiang University College of Control Science and Engineering China

ISBN: (纸本)9789887581581

Industrial network control systems (INCSs) are easy to be targeted by attackers due to their high economic value. Most of the existing defense methods are deployed at the network boundary, which causes high-security risks to INCS once an attacker enters the system. In addition, many existing intrusion detection systems (IDSs) build detection models based on historical data. When INCS lacks sufficient historical data, it is difficult to build detection models with high accuracy. In this paper, we propose a trust assessment model for INCS based on Fourier series fitting employing concept of zero trust to assess the real-time trust of INCS. The model alerts when INCS has low trust. We test two data injection attacks in the experiment to prove the effectiveness of our approach. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Network intrusion

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Attention-based Vision Knowledge Adaptation for Constrained Continual Learning

Attention-based Vision Knowledge Adaptation for Constrained ...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Guo, Bicheng Zhou, Conghao Liu, Haoyu He, Shibo Chen, Jiming Shen, Xuemin Zhejiang University College of Control Science and Engineering China University of Waterloo Department of Electrical and Computer Engineering Canada

ISBN: (纸本)9798350351255

The demand for continual machine learning in the context of limited computational resources and data availability is critical in the evolving landscape of the connected digital world. Current network applications predominantly rely on deep learning models that require labor/computation-intensive training processes. These models often struggle to effectively adapt to new data while preserving performance on previously acquired knowledge. In this paper, we introduce a lightweight framework for continual knowledge adaptation and learning designed to address these challenges. To prevent disruption of existing services, we propose an attention-based adapter that integrates seamlessly with the existing vision model to encode new incoming data. The weights of the original model are kept fixed during the adaptation process, ensuring the preservation of previously learned knowledge. Furthermore, to enhance learning efficiency and accelerate convergence with new data, we implement a knowledge fusion mechanism that facilitates interaction between existing knowledge and information from new data. Our framework is modular, enabling flexible deployment across distributed devices. The adapter and knowledge fusion module are implemented at each stage with minimal trainable parameters, optimizing resource usage. Extensive experiments and ablation studies validate the effectiveness of the proposed framework. © 2024 IEEE.

关键词： Adversarial machine learning

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Distortion Evaluation of EMP Sensors Using Associated-Hermite Functions

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computers, Materials & Continua 2023年第1期74卷 1093-1105页

作者： Rupo Ma Siping Gao College of Command and Control Engineering Army Engineering UniversityNanjing210007China Department of Computer Information and Cyber Security Jiangsu Police InstituteNanjing210031China Department of Electrical and Computer Engineering National University of Singapore119260Singapore

Electromagnetic pulse(EMP)is a kind of transient electromagnetic phenomenon with short rise time of the leading edge and wide spectrum,which usually disrupts communications and damages electronic equipment and *** is challenging for an EMP sensor to measure a wideband electromagnetic pulse without distortion for the whole ***,analyzing the distortion of EMP measurement is crucial to evaluating the sensor distortion characteristics and correcting the measurement *** fidelity is usually employed to evaluate the distortion of an ***,this metric depends on specific signal waveforms,thus is unsuitable for evaluating and analyzing the distortion of EMP *** this paper,an associated-hermite-function based distortion analysis method including system transfer matrices and distortion rates is proposed,which is general and independent from individual *** system transfer matrix and distortion rate can be straightforwardly calculated by the signal orthogonal transformation coefficients using associated-hermite *** of a sensor *** is then visualized via the system transfer matrix,which is convenient in quantitative analysis of the *** of a current probe,a coaxial pulse voltage probe and a B-field sensor were performed,based on which the feasibility and effectiveness of the proposed distortion analysis method is successfully verified.

关键词： Electromagnetic pulse associated-hermite functions system transfer matrix distortion rate

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A Review of Security and Information control in Blockchain-Integrated IoT Applications 3

A Review of Security and Information Control in Blockchain-I...

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3rd IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Cholke, Abhijeet Mandhare, V.V. Vikhe, P.S. Matoshri College of Engineering & Research Centre Department of Computer Engineering Nashik India Pravara Rural Engineering College Department of Computer Engineering Loni Ahmednagar India Pravara Rural Engineering College Department of Instrumentation and Control Engineering Loni Ahmednagar India

ISBN: (纸本)9798350354348

The convergence of the Internet of Things (IoT) and blockchain technologies has gained substantial traction in recent years, owing to the rapid advancement of communication technologies worldwide. This research introduces a prototype model that seamlessly integrates an IoT platform with blockchain technology to ensure the integrity of data. The prototype establishes a decentralized framework for IoT devices, underpinned by a private blockchain infrastructure capable of replicating device data and validating transactions among devices through a consensus mechanism. Nevertheless, the implementation of this concept necessitates a closer examination of various considerations. One crucial aspect to address is transforming data generated by diverse IoT devices into a format compatible with the blockchain. This research takes a proactive approach to effective data management within the blockchain. Initially, we collect data from IoT devices and systematically store it in a blockchain-compatible manner. The custom blockchain and smart contract components define the data access policies for end-users. Within this model, we categorize IoT appliances responsible for different services into distinct sets of chains. These sets of chains collaboratively exchange data while adhering to a comprehensive access control *** research endeavors to harmonize IoT and blockchain technologies through a prototype that safeguards data integrity. It tackles the challenge of data conversion from various IoT devices into a blockchain-compatible format and outlines a sophisticated data management strategy. By delineating access policies and segmenting IoT appliances into specialized sets of chains, this model aims to facilitate secure and efficient data sharing among decentralized IoT devices. © 2024 IEEE.

关键词： Data integrity

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Recommendation System Based on Perceptron and Graph Convolution Network

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computers, Materials & Continua 2024年第6期79卷 3939-3954页

作者： Zuozheng Lian Yongchao Yin Haizhen Wang College of Computer and Control Engineering Qiqihar UniversityQiqihar161006China Heilongjiang Key Laboratory of Big Data Network Security Detection and Analysis Qiqihar UniversityQiqihar161006China

The relationship between users and items,which cannot be recovered by traditional techniques,can be extracted by the recommendation algorithm based on the graph convolution *** current simple linear combination of these algorithms may not be sufficient to extract the complex structure of user interaction *** paper presents a new approach to address such issues,utilizing the graph convolution network to extract association *** proposed approach mainly includes three modules:Embedding layer,forward propagation layer,and score prediction *** embedding layer models users and items according to their interaction information and generates initial feature vectors as input for the forward propagation *** forward propagation layer designs two parallel graph convolution networks with self-connections,which extract higher-order association relevance from users and items separately by multi-layer graph ***,the forward propagation layer integrates the attention factor to assign different weights among the hop neighbors of the graph convolution network fusion,capturing more comprehensive association relevance between users and items as input for the score prediction *** score prediction layer introduces MLP(multi-layer perceptron)to conduct non-linear feature interaction between users and items,***,the prediction score of users to items is *** recall rate and normalized discounted cumulative gain were used as evaluation *** proposed approach effectively integrates higher-order information in user entries,and experimental analysis demonstrates its superiority over the existing algorithms.

关键词： Recommendation system graph convolution network attention mechanism multi-layer perceptron

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A DDoS Identification Method for Unbalanced Data CVWGG

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computers, Materials & Continua 2024年第12期81卷 3825-3851页

作者： Haizhen Wang Na Jia Yang He Pan Tan College of Computer and Control Engineering Qiqihar UniversityQiqihar161006China Heilongjiang Key Laboratory of Big Data Network Security Detection and Analysis Qiqihar UniversityQiqihar161006China

As the popularity and dependence on the Internet increase,DDoS(distributed denial of service)attacks seriously threaten network *** accurately distinguishing between different types of DDoS attacks,targeted defense strategies can be formulated,significantly improving network protection *** attacks usually manifest as an abnormal increase in network traffic,and their diverse types of attacks,along with a severe data imbalance,make it difficult for traditional classification methods to effectively identify a small number of attack *** solve this problem,this paper proposes a DDoS recognition method CVWGG(Conditional Variational Autoencoder-Wasserstein Generative Adversarial Network-gradient penalty-Gated Recurrent Unit)for unbalanced data,which generates less noisy data and high data quality compared with existing *** mainly includes unbalanced data processing for CVWG,feature extraction,and *** uses the CVAE(Conditional Variational Autoencoder)to improve the WGAN(Wasserstein Generative Adversarial Network)and introduces a GP(gradient penalty)term to design the loss function to generate balanced data,which enhances the learning ability and stability of the ***,the GRU(Gated Recurrent Units)are used to capture the temporal features and patterns of the ***,the logsoftmax function is used to differentiate DDoS attack *** PyCharm and Python 3.10 for programming and evaluating performance with metrics such as accuracy and precision,the results show that the method achieved accuracy rates of 96.0%and 97.3%on two datasets,***,comparison and ablation experiment results demonstrate that CVWGG effectively mitigates the imbalance between DDoS attack categories,significantly improves the classification accuracy of different types of attacks and provides a valuable reference for network security defense.

关键词： Conditional variational autoencoder generating adversarial networks DDoS attack

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Multi-Objective Optimization of Asymmetric PM-Assisted Synchronous Reluctance Motor Based on NSGA-III 7

Multi-Objective Optimization of Asymmetric PM-Assisted Synch...

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7th IEEE International Electrical and Energy Conference, CIEEC 2024

作者： Wang, Weinan Wang, Shuo Zhao, Xiaokun Zhu, Liangkuan Liu, Yiqi Wei, Jian College of Computer and Control Engineering Northeast Forestry University Harbin China College of Mechanical and Electrical Engineering Northeast Forestry University Harbin China

ISBN: (纸本)9798350359558

Reluctance motor has the advantages of simple structure, low amount of permanent magnet and high stability. But reluctance motor's limited torque density hinders its widespread application. However, the problem of high torque ripple caused by the asymmetric topology of the permanent magnet still needs further optimization. Firstly, the structure of APMA-SynRM and the parameters to be optimized are introduced. The APMA-SynRM optimization steps are then designed. Then, the range of optimization variables is determined by parametric scanning of APMA-SynRM parameters, and the response surface of APMA-SynRM is established. The final optimal design was obtained by non-dominating genetic algorithm (NSGA-III), In conclusion, the comparison and analysis of the key performance indicators before and after APMA-SynRM optimization are presented. © 2024 IEEE.

关键词： Reluctance motors

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Low Conduction-Loss DC Circuit Breaker with Bidirectional Break Capability 7

Low Conduction-Loss DC Circuit Breaker with Bidirectional Br...

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7th IEEE International Electrical and Energy Conference, CIEEC 2024

作者： Wu, Yucheng Yin, Laicheng Gu, Fangning Liu, Jiayi Yu, Xiaohan Liu, Yiqi College of Mechanical and Electrical Engineering Northeast Forestry University Harbin China College of Computer and Control Engineering Northeast Forestry University Harbin China

ISBN: (纸本)9798350359558

The Modular Multilevel Converter-based High Voltage Direct Current (MMC-HVDC) transmission system has become the most commonly used transmission technology in DC transmission projects. In order to save transmission and distribution costs, it often employs a half-bridge submodule combined with a DC circuit breaker for isolating DC-side short-circuit faults. The DC circuit breaker is crucial equipment for DC fault isolation. During a short-circuit fault on the DC side, the current can quickly exceed several times its rated value within milliseconds. Hybrid DC circuit breakers efficiently and safely interrupt DC power. However, traditional hybrid DC circuit breakers, which use IGBTs as forced commutation switches, incur high costs and suffer from kilowatt-level power losses. Therefore, this paper proposes a low conduction loss DC circuit breaker topology with bidirectional interruption capability. It utilizes thyristors and diode bridges as forced commutation switches and designs thyristor turn-off circuits and capacitor pre-charging strategies. The proposed topology offers advantages of high interruption efficiency, low conduction losses, and low cost. Simulation verification using the PSCAD/EMTDC platform confirms the effectiveness of the proposed topology. © 2024 IEEE.

关键词： Electric circuit breakers

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Orthogonal Dual-channel based Wireless Charging System with Free Rotation and Simultaneous Data Transmission 2

Orthogonal Dual-channel based Wireless Charging System with ...

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2nd China Power Supply Society Electromagnetic Compatibility Conference, CPEMC 2024

作者： Liu, Hao Chang, Junhao Li, Zhenjie Chen, Henglin College of Electrical Engineering Zhejiang University Hangzhou310027 China College of Computer and Control Engineering Northeast Forestry University Harbin150040 China

ISBN: (纸本)9798331509552

An orthogonal dual-channel-based wireless charging system is designed to desensitize the wireless charging system to free rotation and transmit energy and data simultaneously. The radial magnetic flux and rectangular coil make the power transmission channel insensitive to rotation and have a certain degree of anti-misalignment ability and the spiral tube-shaped magnetic coupling structure also has anti offset ability when decoupled from the power channel. In addition, the channel is rotationally symmetric. A simple decoding circuit is designed to achieve data extraction. Simulation results based on finite element and PLECS software verified the decoupling and anti-misalignment performance, verifying the proposed WCS's feasibility. ©2024 IEEE.

关键词： Wireless charging

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