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Cyberspace Simulation and Evaluation: Third International Conference, CSE 2024, Shenzhen, China, November 2628, 2024, Proceedings, Part I [Mīkstie vāki]

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  • Formāts: Paperback / softback, 498 pages, height x width: 235x155 mm, 169 Illustrations, color; 37 Illustrations, black and white; XXII, 498 p. 206 illus., 169 illus. in color., 1 Paperback / softback
  • Sērija : Communications in Computer and Information Science 2420
  • Izdošanas datums: 06-May-2025
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 9819645026
  • ISBN-13: 9789819645022
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Cyberspace Simulation and Evaluation: Third International Conference, CSE 2024, Shenzhen, China, November 2628, 2024, Proceedings, Part IPalielināt
  • Formāts: Paperback / softback, 498 pages, height x width: 235x155 mm, 169 Illustrations, color; 37 Illustrations, black and white; XXII, 498 p. 206 illus., 169 illus. in color., 1 Paperback / softback
  • Sērija : Communications in Computer and Information Science 2420
  • Izdošanas datums: 06-May-2025
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 9819645026
  • ISBN-13: 9789819645022
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9789819645022.html
Keywords:
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 2628, 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.
.- 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.