Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications (Communications in Computer and Information Science)

✍ Scribed by Tran Khanh Dang (editor), Josef Küng (editor), Tai M. Chung (editor), Makoto Takizawa (editor)

• Publisher: Springer
• Year: 2021
• Tongue: English
• Leaves: 502
• Category: Library

✦ Synopsis

This book constitutes the proceedings of the 8th International Conference on Future Data and Security Engineering, FDSE 2021, held in Ho Chi Minh City, Vietnam, in November 2021.

The 28 full papers and 8 short were carefully reviewed and selected from 168 submissions. The selected papers are organized into the following topical headings: big data analytics and distributed systems; security and privacy engineering; industry 4.0 and smart city: data analytics and security; blockchain and access control; data analytics and healthcare systems; and short papers: security and data engineering.

The conference was held virtually due to the COVID-19 pandemic.

✦ Table of Contents

Preface
Organization
Contents
Big Data Analytics and Distributed Systems
Document Representation with Representative Sets and Document Similarity at Sentence Level Using Maximum Matching in Bipartite Graph
1 Introduction
2 Related Work
3 Proposed Methods
3.1 Document Centroid Vector Method
3.2 Single Representative Set Method
3.3 Maximum-Matching with Minimum-Cost in Bipartite Graph
3.4 Multi Representative Sets
4 Experiments with Vietnamese Dataset and Online Utilities for Vietnamese Document Analysis
4.1 Dataset
4.2 Document Representation with Representative Sets: Experiments and Online Utility
4.3 Topic Relevance Experiment and Online Utility
4.4 Sentence Matching Experiment and Online Utility
5 Conclusion
References
A Hybrid Approach Using Decision Tree and Multiple Linear Regression for Predicting Students’ Performance
1 Introduction
2 Related Work
3 Methodology
3.1 Dataset
3.2 Feature Selection
3.3 Decision Tree
3.4 Model Evaluation
4 Results
4.1 Feature Selection
4.2 Decision Tree and Multiple Linear Regression Model
4.3 Decision Support System
5 Conclusions
References
Human Mobility Prediction Using k-Latest Check-ins
1 Introduction
2 Related Work
3 Proposed Method
3.1 Data Description
3.2 K-Latest Check-ins (kLC)
4 Results
4.1 Settings
4.2 Performance Metric
4.3 Experiment Results
5 Conclusion
References
Hospital Revenue Forecast Using Multivariate and Univariate Long Short-Term Memories
1 Introduction
2 Related Work
3 The Proposed Method for Hospital Revenue Forecast
3.1 Data Description
3.2 Features Importance
3.3 Neural Networks Setting
4 Experimental Results
4.1 Metrics for Evaluation
4.2 Hospital Revenue Forecasting
5 Conclusion
References
Using Some Machine Learning Methods for Time Series Forecasting Regarding Gold Prices
1 Introduction
2 Related Works
3 Some Research Models
3.1 The ARIMA Model
3.2 The SARIMA Model
3.3 Recurrent Fuzzy Neural Network
3.4 The ARIMA-LSTM Combined Model Based on MA Filter
4 Experimental Results and Assessment
4.1 The Results of Using the ARIMA Model
4.2 The Results of Using the SARIMA Model
4.3 The Results of Using the Recurrent Fuzzy Neural Network
4.4 The Results of Using the ARIMA - LSTM Combined Model
4.5 Evaluation of Experimental Results
5 Conclusion
References
Security and Privacy Engineering
Improving ModSecurity WAF Using a Structured-Language Classifier
1 Introduction
2 Background and Related Works
2.1 Background
2.2 Related Works
3 Proposed Approach
3.1 System Analysis
3.2 Architecture
4 System Implementation and Datasets
4.1 System Implementation
4.2 Datasets
5 Experiments and Evaluation
5.1 Request Categorizer
5.2 End-to-End Test
6 Discussion
7 Conclusion
References
Security Issues in Android Application Development and Plug-in for Android Studio to Support Secure Programming
1 Introduction
2 Related Work
2.1 Security Issues in Android Applications
2.2 Android Secure Coding Methodologies and Tools
3 Security Issues in Android Applications
3.1 Security in Cryptography Implementation
3.2 Security in Client-Side and Click-Jacking Prevention
3.3 Security in Communication Between Application and Server
3.4 Security in Android Components
3.5 Protect Data Stored on Mobile Phones
3.6 Secure Coding with Logs and Debug Information
4 Secure Coding Plugin for Android Studio
4.1 Android Lint
4.2 Proposed Architecture for Extending Android Lint's Detection and Reporting System
4.3 9Fix: Android Studio Secure Coding Plug-in
4.4 Example of Use
4.5 Rules Customization for a Specific Project
4.6 Security Checklist
5 Experiment Results
5.1 Performance
5.2 User Experience
6 Conclusion
References
On Using Cryptographic Technologies in Privacy Protection of Online Conferencing Systems
1 Introduction
2 Related Work
3 Material and Methodologies
3.1 Time-Based One-Time Password (TOTP)
3.2 InsertableStream
4 System Design and Integration
4.1 Online Conference Application
4.2 Authentication Application
4.3 System Integration
5 Experiment and Results
5.1 Experimental Specifications
5.2 Experimental Results
5.3 Quality of Service Evaluation
5.4 Discussion
6 Conclusion and Future Work
References
A Survey of Machine Learning Techniques for IoT Security
1 Introduction
2 IoT Security Risks
3 Current IoT Security Research Trends
3.1 Existing IoT Security Solutions Based on Machine Learning
3.2 ML-Based IoT Security Classification
3.3 Limitations in Applied Machine Learning in IoT System
4 Evaluation on ML-Based Techniques for IoT Security
5 Conclusions
References
Industry 4.0 and Smart City: Data Analytics and Security
A Prediction-Based Cache Replacement Policy for Flash Storage
1 Introduction
2 Related Work
3 Proposed Method
3.1 Cache Structure and Policies
3.2 Future Reference Prediction
4 Performance Evaluation
4.1 Experiment Setting
4.2 Experiment Result
5 Conclusion
References
A Deep Learning-Based Method for Image Tampering Detection
1 Introduction
2 Related Works
3 Problem Statement
4 Proposed Method
4.1 YOLO Algorithm [1]
4.2 A Model of Tampering Detection
5 Simulation Results
6 Conclusions
References
Building a Vietnamese Dataset for Natural Language Inference Models
1 Introduction
2 The Constructing Method
2.1 NLI Sample Generation
2.2 Entailment Pair Collection
3 Building Vietnamese NLI Dataset
3.1 Contradiction Creation Guidelines
3.2 Building Steps
3.3 Building Results
4 Experiments
4.1 Experiment Settings
4.2 Experiment Results
5 Conclusion and Future Works
References
One-Class Classification with Noise-Based Data Augmentation for Industrial Anomaly Detection
1 Introduction
2 Related Works
3 Method
4 Experiments
5 Concluding Remarks
References
Features Selection in Microscopic Printing Analysis for Source Printer Identification with Machine Learning
1 Introduction
2 Related Work
3 Proposed Method
4 Experiments
5 Conclusion
References
Forecasting and Analyzing the Risk of Dropping Out of High School Students in Ca Mau Province
1 Introduction
2 Related Work
3 Proposed Method
3.1 Data Collection
3.2 Data Pre-processing
3.3 Using Machine Learning Models
3.4 Extraction of Essential Features
4 Experimental Result
4.1 Machine Learning Model Evaluation
4.2 Experimental Result
4.3 Features Extraction for Analyzing Factors Affecting Students' Dropout
5 Conclusion and Future Work
References
Personalized Student Performance Prediction Using Multivariate Long Short-Term Memory
1 Introduction
2 Related Work
3 Method
3.1 Datasets for the Experiments
3.2 Data Pre-processing
3.3 Learning Models for Student Performance
4 Evaluation of Results
4.1 Evaluation Method
4.2 Experimental Results
5 Conclusion
References
Estimating the Traffic Density from Traffic Cameras
1 Introduction
2 Related Work
3 Proposed Method
3.1 Faster RCNN Structure
3.2 API Send SMS – Nexmo
3.3 Emailing API - SendGrid
3.4 Evaluation Methods
4 Experiment Results and Discussion
4.1 The datasets
4.2 Experiment Results
5 Conclusion and Future Work
References
Air Pollution Forecasting Using Regression Models and LSTM Deep Learning Models for Vietnam
1 Introduction
2 Related Works
3 Study Area and Methodology
3.1 Dataset Description
3.2 Dataset Preprocessing
3.3 Time Series Modeling
4 Model Description
4.1 LSTM and BLSTM
4.2 Performance Criteria
4.3 Parameter Optimization
5 Result
6 Conclusion
References
Proposing Recommendation System Using Bag of Word and Multi-label Support Vector Machine Classification
1 Introduction
2 Related Work
3 System Design
3.1 Overview of Proposal System
3.2 Building Model
3.3 Training Process
4 Simulation and Result
4.1 Setup
4.2 Result
4.3 Deploying on Website
5 Conclusion
References
Blockchain and Access Control
IU-SmartCert: A Blockchain-Based System for Academic Credentials with Selective Disclosure
1 Introduction
2 Related Work
3 Proposed Solution
3.1 Defining a Credential Schema
3.2 Issuing Credentials
3.3 Generating Receipts
3.4 Exchanging Credentials
3.5 Revoking Credentials
3.6 Verifying a Credential
4 Security Analysis
4.1 Authenticity and Protection Against Spoofing Identity
4.2 Integrity of Users's Credentials (Protection Against Tampering)
4.3 Originality and Repudiation
4.4 Protection Against Information Disclosure
4.5 Denial of Service
4.6 Elevation of Privilege
5 Proof of Concept and Experimental Results
5.1 Implementation
5.2 Cost of Transactions
6 Discussion
7 Conclusion
References
An Approach for Project Management System Based on Blockchain
1 Introduction
2 Related Work
3 Background
3.1 Blockchain
3.2 Smart Contract
3.3 Binance Smart Chain
4 The Proposed Architecture for Project Management System Based on Blockchain
4.1 Overall Architecture
4.2 Major Modules for Project Management System
5 Deployment
6 Conclusion
References
Privacy-Preserving Attribute-Based Access Control in Education Information Systems
1 Introduction
2 Related Works
3 Proposed Solution
3.1 Phase 1
3.2 Phase 2
4 Conclusion
References
A Consortium Blockchain-Based Platform for Academic Certificate Verification
1 Introduction and Motivation
2 Technical Background
2.1 Blockchain Technology
2.2 The Consensus Protocols
2.3 Smart Contracts
3 Consortium Blockchain-Based Degree Certificate Verification System
3.1 The Functional Design
3.2 The System Architecture Design
3.3 Blockchain Framework and Configuration
3.4 Data Structures and Smart Contracts
3.5 The System Prototyping
3.6 The System Evaluation
4 Conclusion
References
Data Analytics and Healthcare Systems
Innovative Way of Detecting Atrial Fibrillation Based on HRV Features Using AI-Techniques
1 Introduction
2 Related Work
3 Dataset
3.1 General
3.2 Preprocessing
4 Methodology
4.1 Preliminary Analysis
4.2 Feature Selection
4.3 Clustering
5 Evaluation
6 Conclusion
References
Entropy-Based Discretization Approach on Metagenomic Data for Disease Prediction
1 Introduction
2 Related Work
3 Method
3.1 Binning Approach
3.2 Machine Learning Algorithms
4 Evaluation
4.1 Configuration
4.2 Benchmark Dataset
4.3 Evaluation Metrics
5 Experimental Results
6 Conclusion
References
Forecasting Covid-19 Infections in Ho Chi Minh City Using Recurrent Neural Networks
1 Introduction
2 Recurrent Neural Networks
3 Dataset and Experimental Results
3.1 Dataset
3.2 Experimental Results and Discussions
4 Conclusions
References
White Blood Cell Segmentation and Classification Using Deep Learning Coupled with Image Processing Technique
1 Introduction
2 Proposed Method
3 Experimental Results
4 Conclusion
References
Modeling Transmission Rate of COVID-19 in Regional Countries to Forecast Newly Infected Cases in a Nation by the Deep Learning Method
1 Introduction
2 About the Models
2.1 Recurrent Neural Network (RNN)
2.2 Long-Short Term Memory (LSTM)
2.3 Gated Recurrent Unit (GRU)
2.4 Hybrid Models
3 Data Preparation
4 Experiments
4.1 Model Parameters
4.2 Training and Evaluation
4.3 Forecasting to Build Scenarios of COVID-19 in Vietnam
5 Conclusion
References
Short Papers: Security and Data Engineering
Using Artificial Intelligence and IoT for Constructing a Smart Trash Bin
1 Introduction
2 System Components
3 Data Collection
4 Trash Bin System Architecture
5 Classifier Training and Data Augmentation
5.1 MobileNet V2 Model
5.2 Augment Data with OpenCV
5.3 Augment Data with Keras Preprocessing Layer
6 Implement Classifier on Raspberry Pi
7 Mobile Application for Managing Trash Bin
8 Conclusion
References
Pixel-Wise Information in Fake Image Detection
1 Introduction
2 Related Work
3 Method
3.1 U-Net-Based Classifier
3.2 Loss Function
4 Experiments and Results
4.1 Dataset
4.2 Network Structure and Implementation Details
4.3 Results
5 Conclusion
References
Speaker Diarization in Vietnamese Voice
1 Introduction
2 The Proposed Method
2.1 Speaker Embedding Extraction
2.2 Clustering Approaches
3 Experimental Results
3.1 Dataset
3.2 Evaluation Results
4 Conclusion
References
The System for Detecting Vietnamese Mispronunciation
1 Introduction
2 Methodology
2.1 The Acoustic Model
2.2 The GoP Algorithm
2.3 Neural Network Classifier
3 Data Preparation
3.1 Training Data for Acoustic Model
3.2 Training Data for Neural Network Classifier
3.3 Testing Data
4 Experiments
4.1 The Acoustic Model
4.2 The Mispronunciation Detection System
5 Conclusion and Perspectives
References
Relation Classification Based on Vietnamese Covid-19 Information Using BERT Model with Typed Entity Markers
1 Introduction
2 Data Preparation
3 Methodology
4 Experiment and Evaluation
4.1 Environment Setup
4.2 Evaluation Method
4.3 Result Analysis
5 Conclusion and Perspectives
References
Preliminary Research for Anomaly Detection in Fog-Based E-Assessment Systems
1 Introduction
2 Related Work
2.1 E-Assessment Systems
2.2 Fog Computing and Existing Anomaly Detection Methods
3 Preliminary
3.1 Architectures of Our Proposed E-Assessment System
3.2 Scopes of Data Analysis
3.3 Factor: The Number of Tests
4 Proposed System
4.1 Proposed Factor: The Number of Exams
5 Conclusion
References
Using Machine Learning Algorithms Combined with Deep Learning in Speech Recognition
1 Introduction
2 Machine Learning Algorithms Combined with Deep Learning
2.1 Application of CNN Network in Feature Extraction and Noise Filtering
2.2 Application of LSTM Network in Speech Recognition
3 Speech Recognition to Advising Education Enrollment Robot
3.1 Speech Recognition Machine Learning Structure Model
3.2 Data Preprocessing
3.3 Speech Recognition Using Machine Learning
3.4 Database Query and Response
4 Experiment and Assessment
5 Conclusion
References
Evading Security Products for Credential Dumping Through Exploiting Vulnerable Driver in Windows Operating Systems
1 Introduction
2 Related Works
3 Background
3.1 Windows Application Programming Interface
3.2 Windows OS Credential Dumping
3.3 Legitimate Vulnerable Drivers
4 Methodology
4.1 Setup a Device Driver in Windows OS
4.2 Exploit the Vulnerable Driver
4.3 Develop Shellcode for Reading OS Credential
5 Experiments
6 Conclusion
References
Author Index