Machine Learning for Cyber Security: 4th International Conference, ML4CS 2022, Guangzhou, China, December 2–4, 2022, Proceedings, Part I

Preface
Organization
Contents – Part I
Contents – Part II
Contents – Part III
Traditional Chinese Medicine Health Status Identification with Graph Attention Network
	1 Introduction
	2 Related Work
	3 Methods
		3.1 TCM Graph Constrcuction Module
		3.2 Attention Layer Construction Module
		3.3 State Element Prediction Module
	4 Experiments
		4.1 Experimental Setup
		4.2 Experimental Results and Analysis
	5 Conclusion
	References
Flexible Task Splitting Strategy in Aircraft Maintenance Technician Scheduling Based on Swarm Intelligence
	1 Introduction
	2 Problem Definition and Flexible Task Splitting Strategy
		2.1 Problem Description
		2.2 Flexible Task Splitting Strategy
		2.3 Technician Assignment Methods
	3 Model Design and Formulations
		3.1 Objective Formulation
		3.2 Constraints Formulation
	4 Swarm Intelligence Algorithms and Solution Encoding
		4.1 Swarm Intelligence Algorithms
		4.2 Encoding Scheme
	5 Experiments and Comparisons
		5.1 Experimental Settings
		5.2 Experiments and Results
	6 Conclusions
	References
Privacy Preserving CSI Fingerprint Device-Free Localization
	1 Introduction
	2 Theories and System
		2.1 Channel State Information
		2.2 Artificial Neural Network
		2.3 Federated Learning
	3 Performance Evaluation
		3.1 Experimental Configurations
		3.2 Experimental Results and Discussion
	4 Conclusion
	References
A Novel Blockchain-MEC-Based Near-Domain Medical Resource Sharing Model
	1 Introduction
	2 Related Works
	3 Structure
		3.1 Device Layer
		3.2 MEC Layer
		3.3 Blockchain Layer
		3.4 Application Layer
	4 Module
		4.1 D2D Communication
		4.2 MEC
		4.3 Blockchain
	5 Experiment and Analysis
		5.1 Experimental Environment
		5.2 Experimental Content
		5.3 Result
		5.4 Analysis
	6 Conclusion
	References
Pairwise Decomposition of Directed Graphic Models for Performing Amortized Approximate Inference
	1 Introduction and Motivation
	2 BNs and Inference Methods
		2.1 BNs and Exact Inference
		2.2 Generalized Belief Propagation and Region Graph
	3 Amortized BN Inference
		3.1 Pairwise Decomposition of CPDs
		3.2 LSRG Algorithm with Node Ordering
		3.3 Amortizing
	4 Evaluations
		4.1 Validation of the PWC Algorithm
		4.2 Validation of the PWC-LSRG Region Graph
		4.3 Validation of the Amortized PWC-LSRG Algorithm
	5 Conclusion and Future Works
	References
VDDL: A Deep Learning-Based Vulnerability Detection Model for Smart Contracts
	1 Introduction
	2 Related Work
	3 Model
		3.1 Overview
		3.2 Extraction
		3.3 Training
		3.4 Prediction
	4 Experiment and Evaluation
		4.1 Dataset
		4.2 Experimental Setup
		4.3 Evaluation Metrics
		4.4 Parameter Influence
		4.5 Comparison with ML-Based Methods
	5 Conclusion and Future Work
	References
Robust Remote Sensing Scene Classification with Multi-view Voting and Entropy Ranking
	1 Introduction
	2 Related Work
	3 Our Approach
		3.1 Multi-view Training and Voting
		3.2 Entropy Ranking
		3.3 Iterative Refinement
	4 Experiments and Discussions
		4.1 Datasets
		4.2 Implementation Details
		4.3 Results
	5 Conclusion
	References
Visualized Analysis of the Emerging Trends of Automated Audio Description Technology
	1 Introduction
	2 Data Collection
	3 Data Analysis
		3.1 Brief Description of the General Trends
		3.2 Most Active Topic Analysis
		3.3 Research Trend Analysis
		3.4 Knowledge Base Analysis
	4 Discussion
	5 Conclusion
	References
Anomaly Detection for Multi-time Series with Normalizing Flow
	1 Introduction
	2 Related Work and Theory
		2.1 Anomaly Detection
		2.2 Bayesian Network
		2.3 Normalizing Flow
	3 Method
		3.1 Overall Framework
		3.2 Dependency Encoder
		3.3 Anomaly Detection
	4 Experiment
		4.1 Dataset
		4.2 Experimental Detail
		4.3 Experimental Metrics
		4.4 Baselines
		4.5 Experimental Result
	5 Conclusion
	References
Encrypted Transmission Method of Network Speech Recognition Information Based on Big Data Analysis
	1 Introduction
	2 Network Voice Preprocessing
	3 Encrypted Transmission of Speech Recognition Information
	4 Experiment and Result Analysis
		4.1 Experiment Preparation Stage
		4.2 Analysis of Experimental Results
	5 Conclusion
	References
A Lightweight NFT Auction Protocol for Cross-chain Environment
	1 Introduction
	2 Related Works
		2.1 Cross-Chain Schemes
		2.2 Blockchain-Based Electronic Auction
		2.3 Cross-Chain NFT
	3 Cross-Chain Auction Protocol
		3.1 Protocol Illustration
		3.2 NFT Locking Process
		3.3 NFT Auction Process
		3.4 Asset Exchange
	4 Experiment and Analysis
		4.1 Experiment Setup
		4.2 Results
	5 Conclusion
	References
A Multi-scale Framework for Out-of-Distribution Detection in Dermoscopic Images
	1 Introduction
	2 Related Work
		2.1 Out-of-Distribution Detection
		2.2 Out-of-Distribution Detection in Skin Images
	3 Method
		3.1 Rectified One-Class Support Vector Machine
		3.2 Adapted Gram Matrix
		3.3 Multi-scale Detection Framework
	4 Experiments
		4.1 Setup
		4.2 Results
	5 Conclusion
	References
Swarm Intelligence for Multi-objective Portfolio Optimization
	1 Introduction
	2 Swarm Intelligence for Multi-objective Optimization
		2.1 Multi-objective Optimization Model
		2.2 Swarm Intelligence
	3 Swarm Intelligence for Portfolio Selection Problems
		3.1 Portfolio Selection Model
		3.2 Encoding
	4 Experiments and Discussions
		4.1 Definition of Experiments
		4.2 Experimental Results
	5 Conclusion
	References
Research on Secure Cloud Storage of Regional Economic Data Network Based on Blockchain Technology
	1 Introduction
	2 Design of Secure Cloud Storage Method for Regional Economic Data Network
		2.1 Building a Regional Economic Data Network Model
		2.2 Collect and Process Regional Economic Data
		2.3 Use Blockchain Technology to Determine the Storage Structure of Economic Data
		2.4 Regional Economic Data Encryption
	3 Experiment Analysis of Cloud Storage Effect Test
		3.1 Configure the Experimental Environment
		3.2 Prepare Regional Economic Data Samples
		3.3 Generate Data Security Storage Tasks
		3.4 Introducing Malicious Nodes
		3.5 Set Cloud Storage Effect Test Indicators
		3.6 Experimental Process and Result Analysis
	4 Conclusion
	References
Data Leakage with Label Reconstruction in Distributed Learning Environments
	1 Introduction
	2 Motivation
	3 Method
		3.1 Overview
		3.2 Label Reconstruction
		3.3 Label Smoothing
	4 Experiment
		4.1 Over Special Datasets
		4.2 On Pretrained Model
	5 Defense Methods
	6 Related Work
	7 Conclusion and Future Work
	References
Analysis Method of Abnormal Traffic of Teaching Network in Higher Vocational Massive Open Online Course Based on Deep Convolutional Neural Network
	1 Introduction
	2 Analysis Method Design of Abnormal Traffic in Teaching Network of Higher Vocational Education in Massive Open Online Course
		2.1 Constructing Massive Open Online Course Teaching Network Model in Higher Vocational Education
		2.2 Collecting Traffic Data of Teaching Network in Higher Vocational Massive Open Online Course
		2.3 Pre-processing of Teaching Network Traffic Data in Massive Open Online Course Higher Vocational Education
		2.4 Extracting Traffic Characteristics Using Deep Convolution Neural Network
		2.5 Detect Abnormal Phenomenon of Network Traffic Data
		2.6 Realize Network Abnormal Traffic Analysis
	3 Comparative Experimental Analysis
		3.1 Configure the Research Object of Massive Open Online Course Teaching Network in Higher Vocational Education
		3.2 Prepare a Sample of Teaching Network Traffic Data in Massive Open Online Course of Higher Vocational Education
		3.3 Input that Running Parameter of the Deep Convolution Neural Network Algorithm
		3.4 Describe the Test Process of Comparative Experiment
		3.5 Set Performance Test Index of Network Abnormal Traffic Analysis
		3.6 Comparison of Experimental Results and Analysis
	4 Concluding Remarks
	References
Spatio-Temporal Context Modeling for Road Obstacle Detection
	1 Introduction
	2 Related Work
	3 Method
		3.1 Scene Layout Construction
		3.2 Obstacle Tracking with Optical Flow
		3.3 Spatio-temporal Aware Detection
	4 Experiments
		4.1 Datasets
		4.2 Implementation Details
		4.3 Experimental Results
	5 Conclusion
	References
A Survey of Android Malware Detection Based on Deep Learning
	1 Introduction
	2 Android Malware Detection Based on Deep Learning
		2.1 Android Application Structure
		2.2 Deep Learning Model Algorithms
		2.3 Android Malware Detection Process Based on Deep Learning
	3 Research Progress
		3.1 Android Malware Detection Based on Different Characteristics
		3.2 Android Malware Detection Based on Different Networks
	4 Datasets Analysis
	5 Evaluation Indicators
	6 Conclusion
	References
Information Encryption Transmission Method of Automobile Communication Network Based on Neural Network
	1 Introduction
	2 Research on Encrypted Transmission of Vehicle Communication Network Information
		2.1 Information Encryption of Automotive Communication Network Based on Neural Network
		2.2 Information Transmission of Vehicle Communication Network
	3 Method Testing and Analysis
		3.1 Experiment Preparation
		3.2 Neural Network Parameter Settings
		3.3 Neural Network Training
		3.4 Method Performance Evaluation Indicators
		3.5 Method Performance Test Results
	4 Conclusion
	References
Explanation-Guided Minimum Adversarial Attack
	1 Introduction
	2 Related Work
		2.1 Adversarial Example Attack
		2.2 Privacy Risk of Model Explanations
	3 Method
		3.1 Model Independent Explanations
		3.2 Adversarial Example Attack
		3.3 Explanation-Guided Minimum Adversarial Attack Algorithm
	4 Experimental Design and Implementation
		4.1 The Experimental Setting
		4.2 Experimental Results and Analysis
	5 Conclusion
	References
CIFD: A Distance for Complex Intuitionistic Fuzzy Set
	1 Introduction
	2 Complex Intuitionistic Fuzzy Set
	3 New Distance for Complex Intuitionistic Fuzzy Sets
		3.1 Similarity Measure Between CIFSs
		3.2 The Novel Distance Between CIFSs
	4 Numerical Example
	5 Conclusion
	References
Security Evaluation Method of Distance Education Network Nodes Based on Machine Learning
	1 Introduction
	2 Security Evaluation of Distance Education Network Nodes
		2.1 Attack Feature Attribute Extraction
		2.2 Build a Network Wide Attack Model
		2.3 Construction of Network Node Security Evaluation Model for Distance Education
	3 Case Evaluation Test
	4 Conclusion
	References
MUEBA: A Multi-model System for Insider Threat Detection
	1 Introduction
	2 Related Work
	3 Methodology
		3.1 Individual Historical Analysis
		3.2 Group Analysis
		3.3 Comprehensive Assessment
	4 Experiment and Analysis
		4.1 Dataset
		4.2 Experimental Settings
		4.3 Results Analysis
	5 Conclusion
	References
Bayesian Based Security Detection Method for Vehicle CAN Bus Network
	1 Introduction
	2 Data Preprocessing
	3 Classification of Network Attacks
	4 CAN Bus Information Entropy Calculation
	5 Implementation of Bus Network Security Detection Based on Bayesian
		5.1 Bayesian Network Learning
		5.2 Inference of Bayesian Networks
		5.3 Detection Implementation
	6 Experimental Comparison
		6.1 Experiment Preparation
		6.2 Analysis of Experimental Results
	7 Conclusion
	References
Discrete Wavelet Transform-Based CNN for Breast Cancer Classification from Histopathology Images
	1 Introduction
	2 Related Work
	3 Dataset and Methods
		3.1 Dataset
		3.2 Overview
		3.3 Image Processing
		3.4 Discrete Wavelet Transform (DWT)
		3.5 Transfer Learning
	4 Experiments and Results
		4.1 Training Methodology
		4.2 Evaluation Metrics
		4.3 Results and Analyses
	5 Conclusion
	References
Machine Learning Based Security Situation Awareness Method for Network Data Transmission Process
	1 Introduction
	2 Design of Security Situational Awareness Method in Network Data Transmission Process
		2.1 Building a Security Situational Awareness Model
		2.2 Extracting Data Features Related to Security Situation
		2.3 Network Data Security Situation Assessment
		2.4 Prediction of Network Data Security Situation
	3 Experiment and Result Analysis
		3.1 Experiment Preparation Stage
		3.2 Analysis of Experimental Results
	4 Conclusion
	References
Multi-objective Hydrologic Cycle Optimization for Integrated Container Terminal Scheduling Problem
	1 Introduction
	2 HCO
		2.1 The Basic Hydrologic Cycle Optimization Algorithm
		2.2 Modified Hydrologic Cycle Optimization Algorithm
	3 HCO for Integrated Container Terminal Scheduling
		3.1 Integrated Container Terminal Scheduling Model
		3.2 Encoding
	4 Experiments and Discussions
		4.1 Parameter Settings
		4.2 Benchmark Test Function Experimental Results
		4.3 ICTS Problem Experimental Results
		4.4 Discussions
	5 Conclusion
	References
High Voltage Power Communication Network Security Early Warning and Monitoring System Based on HMAC Algorithm
	1 Introduction
	2 Hardware Design of High-Voltage Power Communication Network Security Early Warning Monitoring System Based on HMAC Algorithm
		2.1 HMAC-Based Logic Controller
		2.2 HMAC-Based Fault Sensor
		2.3 HMAC-Based Signal Receiving Port
		2.4 Design of Fault Early Warning Equipment Based on HMAC
		2.5 Data Sensing Module
		2.6 Monitoring Module
		2.7 Early Warning Module
	3 Software Design of High-Voltage Power Communication Network Security Early Warning Monitoring System Based on HMAC Algorithm
	4 Experimental Studies
	5 Conclusion
	References
Large Scale Network Intrusion Detection Model Based on FS Feature Selection
	1 Introduction
	2 Network Intrusion Detection Model Design
		2.1 Intrusion Detection Dataset
		2.2 Intrusion Detection Data Preprocessing
		2.3 FS Feature Selection
		2.4 Intrusion Detection Implementation
	3 Model Application Test
		3.1 Model Application Test Tool
		3.2 Training Set and Test Set Samples
		3.3 Feature Selection Results
		3.4 Evaluation Indicators
		3.5 Model Application Performance
	4 Conclusion
	References
Research on Intelligent Detection Method of Automotive Network Data Security Based on FlexRay/CAN Gateway
	1 Introduction
	2 Data Forwarding Based on FlexRay/CAN Gateway
		2.1 FlexRay/CAN Gateway Settings
		2.2 EDF Scheduling Algorithm
		2.3 Queue Forwarding Efficiency
	3 Design of Intelligent Detection Method for Vehicle Network Data Security
		3.1 Definition of In-Vehicle Network
		3.2 Data Domain Analysis
		3.3 Flow Detection Coefficient
	4 Case Analysis
	5 Conclusion
	References
Adversarial Attack and Defense on Natural Language Processing in Deep Learning: A Survey and Perspective
	1 Introduction
	2 Preliminary
		2.1 Definition of Adversarial Example
		2.2 Common Tasks and Datasets
		2.3 Adversarial Example Quality Assessment
		2.4 Textual Adversarial Example Classification
	3 Textual Adversarial Attack
		3.1 Character Level
		3.2 Word Level
		3.3 Sentence Level
		3.4 Multi-level Combinations
	4 Textual Adversarial Defense
		4.1 Robust Encoding
		4.2 Randomization
		4.3 Adversarial Training
		4.4 Adversarial Detection
		4.5 Certified Defense
	5 Adversarial Examples on Chinese Texts
		5.1 Adversarial Attack on Chinese Text
		5.2 Adversarial Defense on Chinese Text
	6 Discussion
		6.1 Reason of Adversarial Vulnerability
		6.2 Generality of Methods
		6.3 Adversarial Examples in Real-World Scenarios
	7 Conclusion
	References
A Novel Security Scheme for Mobile Healthcare in Digital Twin
	1 Introduction
	2 Related Works
		2.1 Application of Traditional AI Technologies in the Medical Field
		2.2 Federated Learning in the Medical Field
		2.3 Digital Twin and Related Technologies in Healthcare and Other Fields
	3 Structure
	4 Module
		4.1 Multi-factor Authentication Module
		4.2 Cryptographic Module
		4.3 Blockchain Module
		4.4 Interaction Module
	5 Experiments
		5.1 Experiment Environment
		5.2 Results
	6 Conclusion
	References
Construction of Security Risk Prediction Model for Wireless Transmission of Multi Axis NC Machining Data
	1 Introduction
	2 Security Risk Prediction Model for Wireless Transmission of Multi Axis NC Machining Data
		2.1 Wireless Data Transmission Security Risk Data Mining
		2.2 Build a Data Wireless Transmission Security Risk Prediction Model
		2.3 Determination of Evaluation Index Weight
	3 Model Test
		3.1 Experimental Data
		3.2 Analysis of Test Results
	4 Conclusion
	References
Spiking Neural Networks Subject to Adversarial Attacks in Spiking Domain
	1 Introduction
	2 Preliminary and Related Work
		2.1 Spiking Neural Networks
		2.2 Adversarial Attack for SNNs
	3 Spike Perturbation Superimposed Attack Method
		3.1 Problem Description and Solutions
		3.2 Problem Formulation
		3.3 Spike Perturbation Superimposed Attack on Static and Neuromorphic Datasets
	4 Experiments
		4.1 Experimental Setup
		4.2 Experimental Results
		4.3 Further Analysis
	5 Conclusion
	References
Diverse Web APIs Recommendation with Privacy-preservation for Mashup Development
	1 Introduction
	2 Related Work
	3 Our Approach: Min-Div
		3.1 Step 1: Construct Web APIs Correlation Graph
		3.2 Step 2: Search for the Candidate API Sets
		3.3 Step 3: Select Optimal API Sets with Best Diversity
	4 Experiment
		4.1 Evaluation Metrics and Compared Methods
		4.2 Experiment Comparison
	5 Conclusion
	References
Network Security Evaluation Method of College Freshmen Career Counseling Service Based on Machine Learning
	1 Introduction
	2 Research on Network Security Evaluation Based on Machine Learning
		2.1 Construction of Network Security Evaluation Index System
		2.2 Data Collection and Pretreatment of Evaluation Index
		2.3 Implementation of Network Security Assessment Based on Machine Learning
	3 Method Application Test
		3.1 Attack Environment
		3.2 Test Data
		3.3 Index Weight
		3.4 Evaluation Model Training
		3.5 Network Security Posture
		3.6 Method Accuracy Analysis
	4 Conclusions
	References
FedTD: Efficiently Share Telemedicine Data with Federated Distillation Learning
	1 Introduction
	2 Related Works
		2.1 Secure Sharing of Medical Data
		2.2 Knowledge Distillation in Federated Learning
	3 Methods
		3.1 Problem Definition
		3.2 Knowledge Distillation Problem Definition
		3.3 Global Server Aggregation
	4 Experiments and Analysis
		4.1 Experimental Environment
		4.2 Performance Evaluation
		4.3 Performance Comparison
	5 Conclusion
	References
Increase Channel Attention Based on Unet++ Architecture for Medical Images
	1 Introduction
	2 Proposed Approach
		2.1 Network Architecture
		2.2 Channel Attention Module
	3 Experiments
	4 Conclusion
	References
Distributed Power Load Missing Value Forecasting with Privacy Protection
	1 Introduction
	2 Related Work
		2.1 Privacy Protection in Load Forecasting
		2.2 Missing Power Data Prediction
	3 Motivation and Formulation
		3.1 Motivation
		3.2 Formulation
	4 A Novel Load Forecasting Approach: LFdLSH
		4.1 LSH: Locality-Sensitive Hashing
		4.2 LFdLSH: A Distributed LSH-Based Approach for Load Forecasting
	5 Case Study
	6 Conclusions and Future Work
	References
Differentially Private Generative Model with Ratio-Based Gradient Clipping
	1 Introduction
		1.1 An Overview of Differential Privacy
		1.2 An Overview of DPSGD and Gradient Clipping
		1.3 An Overview of Differentially Private GANs
		1.4 Our Contributions
	2 Preliminaries
		2.1 Differential Privacy
		2.2 Differentially Private Stochastic Gradient Descent
	3 Gradient Clipping and Perturbation Mechanism
		3.1 Per-unit Gradient Clipping and Perturbation
		3.2 Per-unit Ratio Gradient Clipping and Perturbation
		3.3 Per-layer Ratio Gradient Clipping and Perturbation
		3.4 Privacy Accounting Analysis
	4 Differentially Private Projection cGAN
	5 Experimental Results
		5.1 Experimental Settings
		5.2 Comparison and Analysis
		5.3 Summary
	6 Conclusion
	References
Differential Privacy Protection Algorithm for Data Clustering Center
	1 Introduction
	2 Differential Privacy
		2.1 Basic Definition
		2.2 The Laplace Mechanism
	3 Differential Privacy K-Means Clustering Algorithm
	4 Improved Differential Privacy K-Means Algorithm
		4.1 Centroid Improvement Design
		4.2 Improved Design of Privacy Protection
		4.3 Privacy Protection Analysis
	5 Experimental Results and Analysis
		5.1 Experimental Data Set
		5.2 Evaluation Index of Clustering Results
		5.3 Experimental Results and Analysis
	6 Summary and Expectation
	References
Improved Kmeans Algorithm Based on Privacy Protection
	1 Introduction
	2 Relevant Theoretical Basis
		2.1 Differential Privacy
		2.2 Kmeans
	3 Improved Kmeans Algorithm Based on Privacy Protection
		3.1 Kmeans Algorithm Based on Dynamically Allocating Cluster Centers
		3.2 Improved Kmeans Algorithm Based on Privacy Protection
	4 Experimental Validation
		4.1 Experimental Design
		4.2 Experimental Results
	5 Conclusion
	References
Symmetry Structured Analysis Sparse Coding for Key Frame Extraction
	1 Introduction
		1.1 Notation
	2 Related Work
	3 Formulation
		3.1 Analysis Sparse Coding with MCP Sparse Regularization
	4 Algorithm
		4.1 Key Frame Extraction Algorithm
	5 Experiments
		5.1 Performance on Synthetic Data
		5.2 Key Frame Extraction Performance
		5.3 Computational Complexity
		5.4 Discussion
	6 Conclusion
	References
Data Reconstruction from Gradient Updates in Federated Learning
	1 Introduction
	2 Motivation
	3 Our Approach
		3.1 Label Selection for Reconstructed Data
		3.2 Acquisition of Single-Label Reconstructed Data
		3.3 Acquisition of Mixed-Label Reconstruction Data
	4 Experiment
		4.1 Single-label Data Reconstruction
		4.2 Single Label Reconstructed Data Attack Performance
		4.3 Single Label Raw Data Attack Performance
		4.4 Single Label Noise Attack Performance
		4.5 Mixed Labels Reconstruction Data
		4.6 Mixed Label Raw Data
		4.7 Mixed Label Noise Data
	5 Conclusion and Future Work
	References
Natural Backdoor Attacks on Speech Recognition Models
	1 Introduction
	2 Related Work
	3 Methodology
		3.1 Poisoning-based Backdoor Attacks on Speech Recognition
		3.2 Backdoor Attacks with Natural Trigger
	4 Experiments of Natural Backdoor Attacks
		4.1 Experimental Setup
		4.2 Evaluation of Natural Backdoor Attacks
		4.3 Effect of Different Factors on ASR
	5 Conclusion
	References
Boarding Pass Positioning with Jointly Multi-channel Segmentation and Perspective Transformation Correction
	1 Introduction
	2 The Proposed Method
		2.1 Boarding Pass Coarse Positioning
		2.2 Boarding Pass Precise Positioning
		2.3 Segmentation and Correction
	3 Experiment and Analysis
		3.1 Separate Experimental Analysis
		3.2 Comparative Experimental Analysis
	4 Conclusion
	References
AP-GCL: Adversarial Perturbation on Graph Contrastive Learning
	1 Introduction
	2 Related Work
	3 Our Method
		3.1 Graph Contrastive Learning
		3.2 Models and Frameworks
	4 Experiments
		4.1 Datasets
		4.2 Experiment Setup
		4.3 Results and Analysis
	5 Conclusion
	References
An Overview of Opponent Modeling for Multi-agent Competition
	1 Introduction
	2 Multi-agent Competition Environment
		2.1 Multi-agent System
		2.2 Multi-agent Game
	3 Multi-agent Deep Reinforcement Learning
		3.1 Deep Reinforcement Learning
		3.2 Multi-agent Reinforcement Learning
	4 Opponent Modeling for Multi-agent Competition
		4.1 Explicit Opponent Modeling
		4.2 Implicit Opponent Modeling
	5 Conclusion
	References
Research on Potential Threat Identification Algorithm for Electric UAV Network Communication
	1 Introduction
	2 Data Acquisition of Electric UAV Network Communication
	3 Establishment of Potential Threat Evaluation Index for Electric UAV Network Communication
	4 Data Decomposition
	5 Establishment of Attack Graph
	6 Potential Threat Identification Process of Electric UAV Network Communication
	7 Experimental Comparison
	8 Conclusion
	References
Author Index