دانلود کتاب Ubiquitous Security. Second International Conference, UbiSec 2022 Zhangjiajie, China, December 28–31, 2022 Revised Selected Papers

فهرست مطالب :

Preface
Organization
Contents
Cyberspace Security
Support Tool Selection in Digital Forensics Training
1 Introduction
2 Background
3 Related Work
4 Support Tool Selection in Digital Forensics Training
4.1 Layers of Abstraction
4.2 Typology
4.3 Decision-Making with AHP
5 Applying the Concept to a Use-Case
5.1 Use Case Description
5.2 Input for Abstraction Layer Concept
5.3 AHP Calculation
5.4 Results Interpretation of the AHP
5.5 Output of Abstraction Layer Concept
6 Discussion
7 Conclusion and Future Work
References
Listen to the Music: Evaluating the Use of Music in Audio Based Authentication
1 Introduction
2 Background and Literature Review
3 Source Audio Selection
4 Feature Extraction
5 Implementation
5.1 Source Audio Generation
5.2 Devices Under Test
5.3 Experiment Architecture
5.4 Environment
6 Classification and Evaluation
7 Evaluating the Effect of Noise
8 Results
8.1 Source Audio Comparison
8.2 Feature Comparison
8.3 Impact of Phones Registered
8.4 Impact of Training Samples
8.5 Impact of Noise
9 Conclusion
References
A Hybrid Secure Two-Party Protocol for Vertical Federated Learning
1 Introduction
2 Related Work
3 Preliminaries
3.1 Split Learning
3.2 Arithmetic Sharing
3.3 Garbled Circuit
4 Overview
4.1 System Model
4.2 Threat Model
4.3 Objective
5 The Proposed Scheme
5.1 Linear Protocol
5.2 Non-linear Protocol
6 Evaluation
7 Conclusion
References
Detecting Unknown Vulnerabilities in Smart Contracts with Multi-Label Classification Model Using CNN-BiLSTM
1 Introduction
2 Related Work
3 Implementation
4 Evaluation
5 Conclusion
References
CATS: A Serious Game in Industry Towards Stronger Cloud Security
1 Introduction
2 Related Work
3 Method
4 Design and Implementation
4.1 Overview of CATS
4.2 Design of CATS
4.3 Implementation of CATS
5 Design Evaluation
5.1 Game Dynamic Evaluation
5.2 Questionnaire and SSI Evaluation
5.3 Evaluation from Open Discussion and Open-Ended Questions in SSI
6 Discussion
7 Conclusion
References
Automated Vulnerability Detection in Source Code Using Quantum Natural Language Processing
1 Introduction
2 Literature Review
3 Methodology
3.1 Dataset Specification
3.2 Input Representation
3.3 Classification Models
3.4 Evaluation Metrics
4 Result and Discussion
5 Conclusion
References
System Call Processing Using Lightweight NLP for IoT Behavioral Malware Detection
1 Introduction
2 Previous Work
2.1 Behavioral Malware Detection
2.2 IoT Background
3 Malware
3.1 Advanced Persistent Threat
3.2 Denial of Service
4 Data Collection and Processing
4.1 Initial Data Processing
4.2 Data Transformation Using NLP
5 Experimental Results
5.1 Logistic Regression
5.2 Shallow Neural Network
6 Conclusions
6.1 Future Work
References
Vulnerability Detection with Representation Learning
1 Introduction
2 Related Works
2.1 Vulnerability Detection Based on Software Metrics
2.2 Machine Learning-Based Vulnerability Detection
2.3 Deep Learning-Based Vulnerability Detection
3 Methodology
3.1 Overview
3.2 Representation Learning
3.3 Ensemble Learning with Neural Representations
4 Empirical Evaluation
4.1 Data Introduction
4.2 Evaluation Metrics
4.3 Experiment Settings and Environment
5 Conclusion
References
Assessing Vulnerability from Its Description
1 Introduction
2 Background
2.1 Common Vulnerability Scoring System (CVSS)
2.2 Term Frequency Inverse Document Frequency and Support Vector Machine
2.3 Universal Sentence Encoder
2.4 Generative Pre-trained Transformer 3
3 Related Works
3.1 Machine Learning for CVSS Prediction
3.2 Conversion from CVSS V2.0 to CVSS V3.1
4 Methodology
4.1 Data
4.2 Tasks
4.3 Training
4.4 Evaluation
5 Empirical Evaluation Results
5.1 Predicting Common Vulnerability Scoring System 2.0
5.2 Predicting Common Vulnerability Scoring System 3.1
6 Discussion
7 Conclusion
References
Malware Traffic Classification Based on GAN and BP Neural Networks
1 Introduction
2 Related Work
2.1 Network Traffic Detection Technology
2.2 Generative Adversarial Network
3 Model
3.1 Combined Model
3.2 Design of the Generative Adversarial Network
4 Experiments
4.1 Datasets
4.2 Data Preprocessing
4.3 Settings
4.4 Results and Analysis
5 Summary
References
Source Code Vulnerability Detection Using Deep Learning Algorithms for Industrial Applications
1 Introduction
2 State-of-the-Art
2.1 Open Source Software Vulnerability Detection for C#
2.2 Deep Learning Software Vulnerability Detection Method
3 Proposed Solution
3.1 Vulnerability Detection Data Set
3.2 Deep Learning Vulnerability Detection
4 Experimental Results and Discussions
5 Conclusions and Future Work
References
Detecting Unknown Vulnerabilities in Smart Contracts with Binary Classification Model Using Machine Learning
1 Introduction
2 Related Work
3 System Model for Unknown Vulnerability Detection
3.1 Data Collection
3.2 Data Pre-processing
3.3 Model Training
3.4 Vulnerability Detection
4 Detailed Design
4.1 Scheme Process
4.2 N-gram Model
4.3 Vector Weight Penalty Mechanism
5 Experiment
5.1 Experimental Dataset
5.2 Evaluation Metrics
5.3 Experimental Results and Analysis
6 Conclusions
References
Prototyping the IDS Security Components in the Context of Industry 4.0 - A Textile and Clothing Industry Case Study
1 Introduction
2 Related Work
3 IDS Security Architecture and Components
4 Prototype Implementation
4.1 Requirements and Proposed Architecture
4.2 Components Configuration
4.3 Communication Testing
5 Discussion
6 Conclusions
References
An Aspect-Based Semi-supervised Generative Model for Online Review Spam Detection
1 Introduction
2 Related Work
3 Proposed Method
3.1 Problem Statement
3.2 The Solution
3.3 Aspect Level Review and Product Information Embedding
3.4 ACVAE: Spam Detection Based on CVAE at the Aspect Level
4 Experiment
4.1 Datasets and the Evaluation Metrics
4.2 Baselines
5 Result and Analysis
6 Case Study
7 Conclusion
References
Hierarchical Policies of Subgoals for Safe Deep Reinforcement Learning
1 Introduction
2 Related Work
3 Method
3.1 Reinforcement Learning
3.2 Subgoal Embedding
4 Experiments
4.1 Environment Set Up
4.2 Subgoal Embedding in Reinforcement Learning Algorithm
5 Discussion
6 Conclusion
References
Improved DeepLabV3+ based Railway Track Extraction to Enhance Railway Transportation Safety
1 Introduction
2 Methods in This Paper
2.1 Algorithm Flow
2.2 Mobilenetv3 Network
2.3 Channel Attention Mechanism
2.4 Network Structure and Algorithm of This Paper
3 Experimental Data and Evaluation Indicators
3.1 Experimental Data Set
3.2 Experimental Environment and Parameter Setting
3.3 Evaluating Indicator
4 Experimental Data and Evaluation Indicators
4.1 Analysis of Ablation Experiment
4.2 Visual Analysis of Loss Function
4.3 Analysis of Model Comparison Experiment
5 Conclusion
References
Analysis of Techniques for Detection and Removal of Zero-Day Attacks (ZDA)
1 Introduction
1.1 Zero-Day Attacks Process
1.2 Conventional Security
2 Literature Review
3 Research Methodology
4 Results and Discussion
4.1 Analysis
4.2 Discussion
5 Conclusion
6 Proposed Model
References
Android Malware Detection: A Literature Review
1 Introduction
2 Android Malware Detection
3 Android Malware Analysis Approaches
3.1 Static Approach
3.2 Dynamic Approach
3.3 Hybrid Approach
3.4 Other Approaches
4 Malware Detection: Challenges and Research Directions
5 Conclusion
References
Threat Modeling in Cloud Computing - A Literature Review
1 Introduction
2 Background
2.1 Cloud Computing
2.2 Threat Modeling
3 Threat Modeling: Approaches and Methods
3.1 Threat Modeling Language-Based Approaches
3.2 Other Threat Modeling Approaches
4 Discussion and Future Directions
5 Conclusion
References
A New Signal Packing Algorithm for CAN-FD with Security Consideration
1 Introduction
2 System Model and Security Model
2.1 System Model
2.2 Security Model
3 MILP-Based Packing Algorithm
3.1 MILP Formulation
3.2 Execution Steps of CSLLP
4 Simulated-Annealing-Based Algorithm
5 Experimental Results
6 Conclusion
References
An Adversarial Sample Defense Method Based on Saliency Information
1 Introduction
2 Related Work
2.1 Existing Attack Methods
2.2 Existing Defense Methods
2.3 Salient Feature Extraction Methods
3 Our Approach
3.1 Pipeline
3.2 Notation
3.3 Learning Objective
4 Experimental Results and Analysis
4.1 Details
4.2 Algorithm Structure
4.3 Qualitative Experiments
4.4 Comparative Experiments
4.5 Ablation Study
5 Conclusion
References
BlockLearning: A Modular Framework for Blockchain-Based Vertical Federated Learning
1 Introduction
2 Related Work
3 BlockLearning Framework\'s Design
3.1 Structure and Modules
4 BlockLearning Framework\'s Implementation
5 Experimental Setup and Evaluation
6 Results and Discussion
7 Conclusions and Future Directions
References
Cyberspace Privacy
An Interactive Query Differential Privacy Protection Model Based on Big Data Analysis
1 Introduction
2 Related Work
3 Redundant Track Data Deletion Algorithm
4 Matrix Decomposition Method Based on Combinatorial Properties
5 Adaptive Noise Tracking Data Protection
6 Simulation Experiments
6.1 Time Complexity
6.2 Information Theft Rate
6.3 Information Loss Rate
7 Conclusion
References
Decentralized Collaborative Filtering Algorithm with Privacy Preserving for Recommendation in Mobile Edge Computing
1 Introduction
2 Related Work
3 Three Observations on Decentralized Recommendation in MEC
3.1 From Low Latency to Ultra-Low Latency
3.2 From Resource Wasting to High Utilization
3.3 From High Risk to Privacy Preserving
4 Decentralized Collaborative Filtering Algorithm
5 Conclusion
References
Encryption Proxies in a Confidential Computing Environment
1 Introduction
2 Background and Project Overview
2.1 Intel SGX
2.2 SCONE
2.3 Eperi Gateway
3 Implementation
3.1 Eperi with SGX
4 Experimental Setup
5 Results
5.1 Latency
5.2 Throughput
5.3 Security Requirements
6 Discussion
7 Conclusion
8 Future Work
References
FedTA: Locally-Differential Federated Learning with Top-k Mechanism and Adam Optimization
1 Introduction
2 Preliminary
2.1 Local Differential Privacy
2.2 Perturbation Mechanism
2.3 Different Optimizers
3 Top-k + Adam
3.1 Top-k Mechanism
3.2 Adam Mechanism
3.3 Top-k + Adam
4 Experiment
5 Conclusion
References
Differentially Private Clustering Algorithm for Mixed Data
1 Introduction
2 Related Work
3 Differentially Private Mixed Data Clustering Algorithm
3.1 Overview of the DPMC Algorithm
3.2 Differential Privacy Protection
3.3 Adaptive Privacy Budget Allocation
3.4 Optimization Based on Consistency Inference
4 Experiments
4.1 Data Set and Parameter Setting
4.2 Performance Evaluation
5 Conclusion
References
Impact of Reenactment Programs on Young Generation
1 Introduction
1.1 Objective of Study
2 Related Work
2.1 Research Gap
3 Research Design and Methodology
3.1 Problem Identification
3.2 Data Collection and Sampling
3.3 Measurement Instruments
3.4 Evaluation
4 Experimentation
4.1 Violence
4.2 Language
4.3 Seduction
4.4 Instigation
4.5 Fear
5 Results and Discussion
5.1 Discussion
6 Conclusion
References
Sensor Cloud Data Privacy Protection Model Based on Collaborative Deep Learning
1 Introduction
2 Algorithm
3 Experiment
4 Conclusion and Discussion
References
Cyberspace Anonymity
An Improved Cuckoo Search Algorithm and Its Application in Function Optimization
1 Introduction
2 Introduction of the CS Algorithm
2.1 Algorithm Principle
2.2 Levy Flight
2.3 Random Migration
2.4 Advantages and Disadvantages of the Algorithm
3 Algorithm Optimization Strategies
3.1 Opposition-Based Learning Strategy
3.2 Dynamic Adjustment Strategy of Inertia Weight
3.3 Local Exploitation Strategy
4 Description and Analysis of ECSOW Algorithm
4.1 Algorithm Description
4.2 Time Complexity Analysis
5 Experiments
5.1 Experimental Environment and Test Functions
5.2 Experimental Results and Analysis
6 Conclusion
References
Empirical Likelihood for PLSIM with Missing Response Variables and Error-Prone Covariates
1 Introduction
2 Methodology and Result
2.1 Empirical Likelihood
2.2 Asymptotic Result
3 Numerical Examples
3.1 Simulation
3.2 A Real Data Example
4 Proofs
5 Discussion
References
High-Speed Anonymous Device Authentication Without Asymmetric Cryptography in the Internet-of-Things
1 Introduction
1.1 Our Contribution and Outline of the Paper
2 Related Work
3 Notation and Preliminaries
3.1 Notation
3.2 Cryptographic Primitives
4 High-Speed Authentication Protocols
4.1 One-Message Authentication with Anonymity
4.2 Authentication with Data Transmission
5 Implementation and Evaluation
5.1 Experiment Configuration
5.2 Result Summary
6 Conclusion and Future Work
References
A-VMD: Adaptive Variational Mode Decomposition Scheme for Noise Reduction in Sensor-Cloud
1 Introduction
2 System Model
2.1 Principle of VMD Algorithm
2.2 Sample Entropy
3 A-VMD Algorithm
3.1 Number of Decomposition Modes
3.2 Quadratic Penalty Factor
3.3 Component Selection and Processing of Reconstructed Signals
3.4 A-VMD Algorithm Flow
4 Noise Reduction Comparison
4.1 Simulation Data Analysis
4.2 Measured Data Analysis
5 Conclusion
References
A Thermal-Aware Scheduling Algorithm for Reducing Thermal Risks in DAG-Based Applications in Cyber-Physical Systems
1 Introduction
2 Related Work
3 System Model
3.1 Application Model
3.2 Power Model
3.3 Thermal Model
3.4 Threat Model
4 Proposed Algorithm
5 Experimental Setup
6 Result and Discussion
7 Conclusion
References
Short Papers
Garbage Recognition Algorithm Based on Self-attention Mechanism and Deep Sorting
1 Introduction
2 Related Work
2.1 YOLOv5s
2.2 CA Self-attention Mechanism
2.3 DeepSort Algorithm
3 Improvement of YOLOv5s Network Structure
3.1 DeepSort and CA Algorithm Combined with YOLOv5s
4 Experimental Setup and Results Analysis
4.1 Dataset Settings
4.2 YOLOv5s Network Training
4.3 YOLOv5s Ablation and Comparative Test
4.4 Algorithm Test Results Analysis
5 Conclusion
References
Approaches for Zero Trust Adoption Based upon Organization Security Level
1 Introduction
2 Related Work
3 Background
4 Zero Trust Adoption and Deployment
4.1 Organizational Categories
4.2 Zero Trust Approaches
4.3 Mapping Zero Trust to Organization Categories
5 Zero Trust and the Cloud
6 Conclusion
References
Multi-Mobile Agent Security by Design Itinerary Planning Approach in Wireless Sensor Network
1 Introduction
2 Multi-mobile Agent Itinerary Planning in WSN
2.1 Dynamic Itinerary Planning
2.2 Data Security
2.3 Limitations of Prior Work
3 A Dynamic Multi-mobile Agent Itinerary Planning Approach in WSNs
3.1 Lightweight AES Implementation
3.2 Proposed Grouping Mechanism
3.3 A Secure Dynamic Itinerary Planning Approach
4 Conclusion and Future Work
References
On the Variability in the Application and Measurement of Supervised Machine Learning in Cyber Security
1 Introduction
2 Method
3 Literature Review
3.1 Supervised Machine Learning and Measurements
3.2 ML Applications in the Field of Cyber Security
4 Discussion
5 Conclusion
Appendix
References
Author Index