Future Data and Security Engineering

Name: Future Data and Security Engineering | 8th International Conference, FDSE 2021, Virtual Event, November 24-26, 2021, Proceedings
Brand: Springer
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8th International Conference, FDSE 2021, Virtual Event, November 24-26, 2021, Proceedings

Tran Khanh Dang Josef Küng Tai M. Chung Makoto Takizawa(Herausgeber*in)

Springer (Verlag)

Erschienen am 18. November 2021

XIII, 426 Seiten

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978-3-030-91387-8 (ISBN)

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Inhalt

Intro
Preface
Organization
Contents
Invited Keynotes
Federated Learning: Issues in Medical Application
1 Introduction
2 Federated Learning in Medical Applications
2.1 Physical Disorder Predictions
2.2 Mental Disorder Predictions
2.3 Other Medical Applications
3 Research Issues
3.1 Heterogeneity Issues
3.2 Client Management Issues
3.3 Traceability and Accountability Issues
3.4 Privacy and Security Issues
4 Modular Framework Under Development
5 Conclusion and Future Works
References
Time in Data Models
1 Introduction
2 Representing Time
3 Snapshots vs. Historical Data Models
4 Temporal Databases
5 Temporal Multiversion Data Models
6 Temporal Integrity Constraints
7 Conclusions
References
Big Data Analytics and Distributed Systems
Distributed Scalable Association Rule Mining over Covid-19 Data
1 Introduction
2 Scrutiny of Related Work
3 Preliminaries
3.1 Apriori
3.2 FP-Growth
3.3 k-Nearest Neighbours
3.4 Apache Spark
4 Methodology
4.1 Hardware and Software Configuration
4.2 Dataset Description
4.3 Data Pre-processing
5 Results and Discussion
5.1 Core Utilization
5.2 Node Utilization
5.3 Number of Transactions
6 Conclusion
References
Threshold Benefit for Groups Influence in Online Social Networks
1 Introduction
2 Related Work
3 Information Diffusion Models
3.1 Independent Cascade Model
3.2 Problem Definition
4 Proposed Algorithm
4.1 Estimation of i
4.2 Main Algorithm
5 Experiments
5.1 Experimental Settings
5.2 Experiment Results
6 Conclusion
References
Application Based Cigarette Detection on Social Media Platforms Using Machine Learning Algorithms
1 Introduction
2 Related Work
3 Methodology
3.1 Dataset
3.2 MMDetection
3.3 Mask R-CNN
3.4 Cascade Mask R-CNN
3.5 HTC
4 Performance Evaluation
4.1 Mask R-CNN
4.2 Cascade Mask R-CNN
4.3 HTC
5 Conclusions
References
Efficient Brain Hemorrhage Detection on 3D CT Scans with Deep Neural Network
1 Introduction
2 Related Works
3 Background
3.1 Architecture of U-Net Deep Neural Network
3.2 Overfitting and Underfitting
3.3 Loss Function
3.4 Xavier Initialization
3.5 Measure of the Average Precision
4 Proposed Method
4.1 The Training Phase
4.2 The Testing Phase
5 Experimental Results
5.1 Description of Dataset and Environment
5.2 Scenario Descriptions
5.3 Scenario Evaluation
6 Conclusion
References
Advances in Machine Learning for Big Data Analytics
Multi-class Bagged Proximal Support Vector Machines for the ImageNet Challenging Problem
1 Introduction
2 Support Vector Machines
3 Proximal Support Vector Machines
4 Multi-class Bagged Proximal Support Vector Machines
4.1 Multi-class Proximal Support Vector Machines
4.2 Parallel Bagged Proximal Support Vector Machines for Large-Scale Multi-class
5 Experimental Results
5.1 Software Programs
5.2 ILSVRC 2010 Dataset
5.3 Tuning Parameter
5.4 Classification Results
6 Conclusion and Future Works
References
Selective Combination and Management of Distributed Machine Learning Models
1 Introduction
2 Related Research and Approaches
2.1 Related Research
2.2 Approach
3 Combining Feature Models
3.1 Distributed Feature Models
3.2 Sequential Combining Method
3.3 Adaptive Selection Method
3.4 Similarity Model Retrieved Method
3.5 Comparison of Performance by Combining
3.6 Combining Policy
4 Feature Model Management
4.1 Management Policy
4.2 Similarity Retrieval of Feature Models
4.3 R-Trees in a Distributed Environment
4.4 Evaluation
5 Issues and Summary
References
Improving ADABoost Algorithm with Weighted SVM for Imbalanced Data Classification
1 Introduction
2 Preliminaries
3 Proposed Method
3.1 Initialize Adaptive ADABoost Weights
3.2 Positive Label Sensitive Confidence Weights of the Membership Classifier
3.3 Im.ADABoost.W-SVM Algorithm
4 Experiments
5 Conclusion
References
Feature Learning and Data Generative Models for Facial Expression Recognition
1 Introduction
2 Related Works
2.1 Expression Recognition on Face Images
2.2 Generative Adversarial Network Model
3 FER2013 Data Set Analysis
3.1 Overview of FER2013 Data Set
3.2 Statistics of Data Set FER2013
3.3 Challenges on the FER2013 Data Set
4 The Proposed Approach
4.1 Problem Statement
4.2 Develop the Data Generation Model
4.3 Design Identity Models
5 Experimental Results
5.1 Model Training Process
5.2 Accuracy Evaluation
6 Conclusion
References
Industry 4.0 and Smart City: Data Analytics and Security
Authorization Strategies and Classification of Access Control Models
1 Introduction
2 Authorization Strategies
2.1 Discretionary Strategy (DAC)
2.2 Mandatory Strategy (MAC)
2.3 Hybrid Strategy
3 Access Control Models
3.1 Access Control by Explicit Object-Subject Assignment (OSA)
3.2 Access Control by Model-Specific Rules (MsR)
3.3 Access Control by Roles
3.4 Access Control by Content
3.5 Access Control by Context
4 Comparative Studies
5 Analysis
6 Conclusion
References
Motorbike Counting in Heavily Crowded Scenes
1 Introduction
2 Related Work
3 Crowd Counting Methods
3.1 Bag-of-Visual-Words
3.2 Lempitsky-Zisserman's Method
3.3 Qing Wen et al.'s Method
3.4 Donatello Conte et al.'s Method
3.5 Deep Convolutional Neural Network for Object Counting
3.6 Context-Aware Crowd Counting (CAN) ch12liu2019context
4 Experiments and Discussion
4.1 The Dataset
4.2 Evaluation Method
4.3 Implementation Details
4.4 Experimental Results
5 Conclusion and Future Work
References
Pesticide Label Detection Using Bounding Prediction-Based Deep Convolutional Networks
1 Introduction and Motivation
2 Technical Background
2.1 Deep Learning and Convolutional Neural Networks (CNNs)
2.2 You Only Look Once (YOLO)
2.3 Single Shot Detection (SSD)
3 Experiments
3.1 Datasets
3.2 Models' Architecture Configuration
3.3 Evaluation Metrics
3.4 Experimental Results
4 Mobile-App Deployment
5 Conclusion
References
Intelligent Urban Transportation System to Control Road Traffic with Air Pollution Orientation
1 Introduction
2 Related Work
3 IUTAR Concepts and Solutions
3.1 System Context Overview
3.2 GAINS Vehicles Categories and Emission Factors
3.3 Modeling Optimal Traffic Light Cycle
4 Application Results
4.1 Training Dataset with Image Pre-processing
4.2 Test Run Results
4.3 IUTAR Dashboard
5 Conclusion and Future Works
References
A Data Union Method Using Hierarchical Clustering and Set Unionability
1 Introduction
2 Background and Related Works
2.1 Related Works
2.2 Dataset Similarity Measurement
3 Proposed Method
3.1 Schema Step
3.2 Clustering Step
3.3 Union Step
4 Experiment and Evaluation
5 Conclusion
References
Blockchain and IoT Applications
A Consensus-Based Load-Balancing Algorithm for Sharded Blockchains
1 Introduction
2 Problem Definition
2.1 Types of Blockchains
2.2 Sharding Strategies
2.3 The Load-Balancing Problem for Sharded Account-Based Blockchains
3 Algorithms
3.1 Diffusion Algorithm
3.2 Centralized Algorithms
4 Experimentation
4.1 Sharding Simulations
4.2 Numerical Results
4.3 Discussion
5 Conclusion
References
Neighboring Information Exploitation for Anomaly Detection in Intelligent IoT
1 Introduction
2 Propose Scheme
2.1 The Overall Process
2.2 Data Processing Model
3 Performance Evaluation
3.1 Experimental Dataset and Evaluation Method
3.2 Experimental Results
4 Conclusion
References
Feature Representation of AutoEncoders for Unsupervised IoT Malware Detection
1 Introduction
2 Related Works
3 Background
3.1 AutoEncoder
3.2 Principle Component Analysis
3.3 Self-Organizing Maps
4 Hybrid AEs and SOMs for IoT Malware Detection
4.1 Latent Representation of AEs
4.2 SOM-Based Clustering Algorithm
5 Experiments
5.1 Datasets
5.2 Parameters Settings
5.3 Evaluation Metrics
6 Results and Discussion
6.1 IoT Data Analysis
6.2 Unknown/New IoT Attack Detection
6.3 Transfer Learning
7 Conclusions and Future Work
References
Machine Learning and Artificial Intelligence for Security and Privacy
Potential Threat of Face Swapping to eKYC with Face Registration and Augmented Solution with Deepfake Detection
1 Introduction
2 Related Work
2.1 Know Your Customer
2.2 Deepfake Generation and Detection
3 Deepfake Attack on eKYC Systems
3.1 Regular Registration Process for eKYC
3.2 Attack Registration Process with Deepfake
4 Deepfake Detection to Protect eKYC Systems
4.1 Deepfake Detection
4.2 Enhanced eKYC with Deepfake Detection
5 Experiments
6 Conclusion
References
Spliced Image Forgery Detection Based on the Combination of Image Pre-processing and Inception V3
1 Introduction
2 Literature Review
3 Problem Statement
4 Proposed Method
4.1 The Architecture of Inception V3
4.2 Spliced Image Forgery Detection
5 Simulation Results
6 Conclusion
References
Comprehensive Analysis of Privacy in Black-Box and White-Box Inference Attacks Against Generative Adversarial Network
1 Introduction
2 Background
3 Related Work
3.1 Condition Generative Adversarial Networks
3.2 Control Generative Adversarial Networks
3.3 Wasserstein Generative Adversarial Networks
4 The Experimentation
4.1 Threat Models
4.2 White-Box Attack
4.3 Black-Box Attack Without Auxiliary Knowledge
4.4 Black-Box Attack with Auxiliary Knowledge
4.5 Experimental Results
5 Conclusions
References
Face Recognition in the Wild for Secure Authentication with Open Set Approach
1 Introduction
2 Related Work
2.1 Face Recognition
2.2 Open-Set Recognition
3 Face Recognition for Authentication with Open-Set Approach
3.1 Overview
3.2 Facenet with OpenMax
3.3 Learning Placeholder with Facenet
3.4 Pipeline
4 Experiments
5 Conclusion
References
Intrusion Detection in Software-Defined Networks
1 Introduction
2 Related Works
2.1 Methods
2.2 Datasets
3 The InSDN Dataset
4 Methods and Experimental Results
4.1 Methods
4.2 Experimental Results
5 Conclusions
References
Emerging Data Management Systems and Applications
Clustering Analyses of Two-Dimensional Space-Filling Curves
1 Preliminaries
2 Our Analytical and Combinatorial Approach
3 Clustering Statistics of 2-Dimensional Hilbert Curves
3.1 (Hk2,G) over Subgrids G Overlapping with Two Quadrants
3.2 Query Subgrids Overlapping with All Quadrants
3.3 The Big Picture: Computing Eq(Hk2)
4 Clustering Statistics of 2-Dimensional z-Order Curves
5 Concluding Remarks
References
Attendance Monitoring Using Adjustable Power UHF RFID and Web-Based Real-Time Automated Information System
1 Introduction
2 Literature Review
3 Proposed System
3.1 System Structure
3.2 Hardware Placement
3.3 Power Adjustment
3.4 Software Analysis
3.5 Advantages and Disadvantages
4 Simulation Results
5 Conclusions
References
Integrating Deep Learning Architecture into Matrix Factorization for Student Performance Prediction
1 Introduction
2 Related Works
3 Proposed Method
3.1 Problem Definition
3.2 Baseline Methods
3.3 Deep Learning Matrix Factorization Method
4 Result
4.1 Dataset
4.2 Evaluation
4.3 Experimental Result
5 Conclusion
References
Author Index

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