Cyberspace Simulation and Evaluation : Third International Conference, CSE 2024, Shenzhen, China, November 26-28, 2024, Proceedings, Part I (Communications in Computer and Information Science)

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Cyberspace Simulation and Evaluation : Third International Conference, CSE 2024, Shenzhen, China, November 26-28, 2024, Proceedings, Part I (Communications in Computer and Information Science)

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  • 製本 Paperback:紙装版/ペーパーバック版／ページ数 493 p.
  • 言語 ENG
  • 商品コード 9789819645022

Full Description

This three volume set, CCIS 2420 - 2422 , constitutes the proceedings of the Third International Conference on Cyberspace Simulation and Evaluation, CSE 2024, held in Shenzhen, China, during November 26-28, 2024.

The 90 full papers included in this book were carefully reviewed and selected from 164 submissions. These papers are organized under topical sections as follows: - 

Part I : Simulation Theory and Methodology; Simulation for CI scenario; Defense Methodology in the Evaluation; and Simulation for IoT scenario.

Part II : Attack Methodology in the Evaluation; Other Simulation and Evaluation methods; Evaluation Theory and Methodology; and Defense Methodology in the Evaluation.

Part III: Defense Methodology in the Evaluation; Design and Cybersecurity for AIoT Systems; Metaverse and Simulation; Secure loT and Blockchain -Enabled Solutions; Software and Protocols Security Analysis; and Test and Evaluation for Cybersecurity.

Contents

.- Simulation Theory and Methodology.

.- State of Health Estimation for Lithium-ion Batteries withan Attention-Integrated BiLSTM-MLP Hybrid Model.

.- A mapping method from experimental scenario to experimental system scheme.

.- A Toolbox for Simulation and Analysis ofStructured Light 3D Reconstruction Systems.

.- A deep reinforcement learning algorithm to bring about stabilization of Hindmarsh-Rose neural model.

.- Synchronization between two Hindmarsh-Rose neural models via deep reinforcement learning methodl.

.- EmuGuard: An Active Defense System For ICS Emulation.

.- Distributed Deep Reinforcement Learning Based Deterministic Task Offloading in End-Edge-Cloud Collaborative Computing Networks.

.- Survey of Ubiquitous Cyberspace Visualization Based on Ontology Engineering.

.- Simulation for CI scenario.

.- Towards Secure Multilayer Networks: Modeling and Robustness Analysis of 3IOTs.

.- Efficient Cross-domain Energy Sharing with lattice-based Aggregated Signature for Blockchain-enabled Smart Grid.

.- Comprehensive Analysis of Scenario Matching Techniques in Cyberspace Security.

.- A Lightweight DTLS Mechanism for New Power Systems Based on Edge Computing.

.- Adaptive Frequency and Delay Compensation in MultiAgent Systems: Enhancing Communication Efficiency and  Robustness.

.- An efficient switching mechanism of satellite and  terrestrial links for satellite internet and  simulation evaluation.

.- MSCVP: Multiscale Network Emulation Based on the  Integration of Modeling, Simulation, Container,  Virtualization, and Physical Networks.

.- Defense Methodology in the Evaluation.

.- Distributed Fiber Acoustic Sensing Home Anomaly Detection Technology Based on Lightweight YOLO.

.- MTMixAD: Metric-Trace Mixed Anomaly Detection Framework for Microservice Systems with Limited and Mislabeled Data.

.- HTTP DDoS Attack Detection Technology Based on PF-RING and Gaussian Naive Bayes in Containerized Environment.

.- A Novel Approach for Advanced Persistent Threats Detection via Graph Transformer.

.- Optimization Framework for Malware Detection Based on Adversarial Networks and Gradient Reversal.

.- LIDS: Enhancing Industrial IoT Network Security  through Lightweight Machine Learning-Powered Intrusion Detection System.

.- Efficient Intrusion Detection in Edge Computing with eBPF and Lightweight Networks.

.- Zypkro: A Node-Level Anomaly Detector for Provenance  Graphs Based on Nonlinear Interaction and Adaptive  Domain Techniques.

.- A Double-Shell Structured Ransomware Defense Method  Tailored for the RaaS Model.

.- Simulation for IoT scenario.

.- I-GATEPi: An adaptive and interpretable monitoring framework for complex industrial processes.

.- DSA-Former: Dual-Stage Attention for Soft Sensing in  Blast Furnace Ironmaking Process.

.- Power Prediction Model Based on CNN-LSTM with Dual- Stream Attention.

.- Modeling and prediction of gas consumption for  slab heating in steel rolling reheating furnace  based on gradient boosting decision tree with Bayesian optimization.

.- Adaptive Particle Swarm Optimization-Simulated Annealing for Complex Workshop Task Scheduling.

.- Self-Tuning Ensemble Empirical Mode Decomposition for  Industrial Oscillation Extraction.

.- Recovery of Control-loop Oscillations in Industrial Time Series with Missing Values.