Preface
Organization
Deep-BDB 2021 Organizing Committee
General Chair
Programme Co-chairs
Local Organizing Co-chairs
Publication Chair
Journal Special Issue Coordinator
Workshop Coordinator
Publicity Chair
Programme Committee
Contents
Machine Learning and Time Series
Tiered Clustering for Time Series Data
1 Introduction
2 Background
2.1 Distance Measure
2.2 Time Series Similarity
2.3 Normalization Methods
3 Tiered Clustering
3.1 Distance Density Clustering
3.2 Hierarchical Agglomerative Clustering
4 SWAN-SF Dataset
5 Experimental Results
6 Conclusion
References
A Three-Step Machine Learning Pipeline for Detecting and Explaining Anomalies in the Time Series of Industrial Process Plants
1 Introduction
2 Related Work
3 Solution Approach
4 Evaluation Data
5 Evaluation and Discussion
6 Conclusion
References
Detecting Phishing Websites Using Neural Network and Bayes Classifier
1 Introduction
2 Related Works
2.1 Classification Models for Classifying the Phishing Attacks
2.2 Detecting Phishing Websites Using Machine Learning Algorithms
2.3 Detecting Phishing Websites with Chrome Support Using Machine Learning Algorithms
2.4 Detecting Phishing URL Using Random Forest Algorithm
3 Information About Dataset
4 Related Works
4.1 URL and Hyperlink Based Features
5 Detecting Phishing Using Neural Network Algorithm
6 Detecting Phishing Website with Bayes Classifier
7 Evaluation Metrics
8 Conclusion
References
Blockchain Technology and Applications
A Blockchain Framework for On-Demand Intermodal Interlining: Blocklining
1 Introduction
2 Related Work
2.1 Air and Rail Interlining
2.2 Virtual Interlining Models
2.3 Airport Facilitated Interlining
2.4 Through Baggage Interlining
3 Blocklining
4 Data Exchange
5 Methodology
6 Conclusion
References
Intersection of AI and Blockchain Technology: Concerns and Prospects
1 Introduction
2 Literature Review
3 Technologies Based on Centralized AI
3.1 Digital Twin
3.2 SenseTime
3.3 AIONE
3.4 Deep Learning for Java (Deeplearning4j)
3.5 TensorFlow
3.6 PyTorch
3.7 Keras
4 Technologies Based on Decentralized AI
5 AI for Blockchain
5.1 Automatic Governance
5.2 Real-Time Flagging of Fraudulent Transactions
5.3 Enhances Security
5.4 Efficient Creation of Digital Investment Assets
5.5 Scalability
6 Blockchain for AI
6.1 Transparency in AI
6.2 Improved Trust on Robotic Decisions
6.3 Decentralized Intelligence
6.4 Keeping Data Private
6.5 Data Distribution and Security
7 Intersection Between Blockchain and AI
8 Issues and Problems at the Intersection of AI and Blockchain
8.1 Governance
8.2 Tedious Consolidation of Outputs
8.3 Magnitude of Efforts
8.4 Higher Computational Needs
8.5 Security
9 Conclusion
References
SAIaaS: A Blockchain-Based Solution for Secure Artificial Intelligence as-a-Service
1 Introduction
2 A Secure Marketplace for IA
2.1 Actors and High-Level Workflow
2.2 Semantic Matchmaking Phase
2.3 Auction Phase
2.4 Secure Learning Phase
2.5 Restitution Phase
3 Proof of Concept
3.1 Implementation
3.2 Cost Estimation
3.3 Discussion
4 Related Work
5 Conclusion and Future Works
References
Blockchain and Security
Trade-Off Between Security and Scalability in Blockchain Design: A Dynamic Sharding Approach
1 Introduction
2 Overview of SecuSca Approach and Motivation
2.1 Motivating Example
2.2 The SecuSca Approach in a Nutshell
3 Related Work
4 Background
4.1 Blockchain Systems
4.2 States Management
5 The Proposed Dynamic Sharding Approach
5.1 Architecture of SecuSca
5.2 The Process of SecuSca Approach
6 Block Insertion in the Dynamic Sharding
7 Implementation and Discussion
7.1 Experimental Setup
7.2 Experiments Studies
8 Conclusion
References
BC-HRM: A Blockchain-Based Human Resource Management System Utilizing Smart Contracts
1 Introduction
2 Smart Contracts
2.1 Conventional Contracts Versus Smart Contracts
2.2 Smart Contracts and Ethereum
3 Related Work: Blockchain Technology Role in Human Resources Management
4 BC-HRM Analysis, Design and Implementation
4.1 Smart Contract Execution
4.2 BC-HRM Application
4.3 BC-HRM Database
5 BC-HRM Evaluation
6 Limitations
7 Conclusion and Future Work
References
Applicability of the Software Security Code Metrics for Ethereum Smart Contract
1 Introduction
2 Background
2.1 Ethereum Smart Contract and Solidity
2.2 Smart Contract Security
2.3 Metrics for Measuring Software Security
2.4 Metric in Smart Contract Domain
3 Applicability of Software Security Metrics for Ethereum Smart Contracts
3.1 Method and Process
3.2 Result
4 Discussion
5 Conclusion
References
Machine Learning, Blockchain and IoT
A Recommendation Model Based on Visitor Preferences on Commercial Websites Using the TKD-NM Algorithm
1 Introduction
2 Literature Review
3 Methodology
4 Experimental Results
5 Conclusion and Suggestions
References
Reinforcement Learning: A Friendly Introduction
1 Introduction
2 Background
2.1 RL Achievements
2.2 Real-Life Applications
2.3 Current Challenges and/or Opportunities
3 RL Taxonomy
3.1 Value-Based Methods
3.2 Policy-Based Methods
3.3 Model-Based Methods
4 RL: An Overview
4.1 Components of RL Agent
4.2 Markov Decision Process
4.3 Bellman Optimality Equation
5 Example of RL
6 Recent Developments
6.1 Graph Convolutional RL
6.2 Measuring the Reliability of RL Algorithms
6.3 Behavior Suite for RL
6.4 The Ingredients of Real World Robotics RL
6.5 Network Randomisation
7 RL: Pros and Cons
7.1 Advantages
7.2 Disadvantages
8 Conclusion
References
Universal Multi-platform Interaction Approach for Distributed Internet of Things
1 Introduction
2 Distributed IoT Computing System and IoT Objects and Interaction
3 IoT Interaction System Design
3.1 Socket API
3.2 RMI
3.3 CORBA
4 Technology Comparison for Distributed IoT Computing System Communication Implementation
5 Conclusion
References
A Practical and Economical Bayesian Approach to Gas Price Prediction
1 Introduction
2 Background
2.1 Ethereum and Gas
2.2 Gaussian Process
3 Methodology
3.1 Pre-processing
3.2 The Model
3.3 Model Evaluation
4 Empirical Analysis
4.1 Observations
4.2 More Observations
5 Discussion
References
Author Index