The International Conference on Deep Learning, Big Data and Blockchain (DBB 2022)

✍ Scribed by Irfan Awan; Muhammad Younas; Jamal Bentahar; Salima Benbernou

• Publisher: Springer Nature
• Year: 2022
• Tongue: English
• Leaves: 140
• Category: Library

✦ Synopsis

Deep and machine learning is the state-of-the-art at providing models, methods, tools and techniques for developing autonomous and intelligent systems which can revolutionise industrial and commercial applications in various fields such as online commerce, intelligent transportation, healthcare and medicine, etc. The ground-breaking technology of blockchain also enables decentralisation, immutability, and transparency of data and applications. This event aims to enable synergy between these areas and provide a leading forum for researchers, developers, practitioners, and professionals from public sectors and industries to meet and share the latest solutions and ideas in solving cutting-edge problems in the modern information society and the economy. The conference focuses on specific challenges in deep (and machine) learning, big data and blockchain. Some of the key topics of interest include (but are not limited to): Deep/Machine learning based models Statistical models and learning Data analysis, insights and hidden pattern Data visualisation Security threat detection Data classification and clustering Blockchain security and trust Blockchain data management

✦ Table of Contents

Preface
Organization
DBB 2022 Organizing Committee
General Chair
Program Co-chairs
Publication Chair
Journal Special Issue Coordinator
Workshop Coordinator
Publicity Chair
Program Committee
Contents
Blockchain and Applications
Apply Trust Computing and Privacy Preserving Smart Contracts to Manage, Share, and Analyze Multi-site Clinical Trial Data
1 Introduction
2 Related Work
3 The Soteria System
3.1 Patient Consent and Clinical Trials Chaincode
3.2 API Gateway
3.3 Decentralized Governance with (t, n) Adaptive Threshold Signature
4 A Detailed IRB Use Case for Data Sharing
5 Implementations
6 Evaluations and Discussion
6.1 Evaluations
6.2 Security Discussion
7 Conclusions
References
Design Principles for Interoperability of Private Blockchains
1 Introduction
2 Background
3 Related Work
4 The Proposed Approach
5 Conclusions
6 Future Research Potential
References
Blockchain for Proposal Management
1 Introduction
2 Proposal Management Process
2.1 Go/No-Go Decision
2.2 Proposal Planning
2.3 Kickoff Meeting
2.4 Proposal Development
2.5 Sending Out
2.6 Closing Out
3 Value of Blockchain for Proposal Management
4 Design and Implementation of Decentralized Applications for Proposal Management
4.1 A Decentralized Autonomous Organization for Proposal Management
4.2 A Decentralized Application for Document Registration
5 Conclusion
References
Machine and Deep Learning
One-Shot Federated Learning-based Model-Free Reinforcement Learning
1 Introduction
1.1 Contributions
1.2 Organization
2 Related Work
2.1 One-Shot Federated Learning
2.2 FL Scheduling Models
3 Problem Formulation
3.1 Deep Q-Network
3.2 One-Shot Federated Learning
4 Implementation and Experiments
4.1 Experimental Setup
4.2 Experimental Results
5 Conclusion
References
A New Approach for Selecting Features in Cancer Classification Using Grey Wolf Optimizer
1 Introduction
2 Background
2.1 Grey Wolf Optimizer (GWO)
2.2 Inspiration
2.3 Social Behavior of Gray Wolves
2.4 Mathematical Modeling
3 Proposed Algorithm
4 Experimental Results and Discussions
4.1 Microarray Data Set
4.2 Parameter Settings
4.3 Results and Analysis
4.4 Comparative Evaluations
5 Conclusion
References
A Smart Video Surveillance System for Helping Law Enforcement Agencies in Detecting Knife Related Crimes
1 Introduction
2 Related Work
3 Smart Video Surveillance System
3.1 Data Collection Phase
3.2 Data Storage and Processing Phase
3.3 Data Analytics Phase
4 Experiments and Results
4.1 Knives Dataset and Data Preprocessing
4.2 Experimental Setup
4.3 Performance Analysis Study
5 Conclusion
References
Biologically Inspired Variational Auto-Encoders for Adversarial Robustness
1 Introduction
2 Related Work
3 Proposed Model
3.1 Varitional Auto-Encoder (VAE)
3.2 Spiking Varitional Auto-Encoder (SVAE)
3.3 VAE–Sleep
3.4 Mirrored STDP (mSTDP)
3.5 Defense–VAE–Sleep
4 Experiments
4.1 Network Architectures and Training Parameters
4.2 Results of White-box Attacks
4.3 Results of Black-box Attacks
4.4 How Come is Defense–VAE–Sleep Mighty and Efficient?
5 Conclusion and Future Research Directions
References
Blockchain Technology and Protocols
Detecting Illicit Ethereum Accounts Based on Their Transaction History and Properties and Using Machine Learning
1 Introduction
2 Related Work
3 Dataset Construction
3.1 Labelled Data Collection
3.2 Feature Extraction
4 A Robust and Performant Model
4.1 Baseline Model
4.2 Feature Selection
5 Results and Discussion
5.1 Feature Cartography and Frauder Profiling
5.2 Misclassified Samples
6 Conclusion and Future Work
References
Identifying Incentives for Extortion in Proof of Stake Consensus Protocols
1 Introduction
2 Background
3 Economic Analysis of the Staking Pool Market
3.1 Malicious Activity Against Staking Pools
3.2 Competition on Price Versus Security
4 Conclusions
References
Three-Valued Model Checking Smart Contract Systems with Trust Under Uncertainty
1 Introduction
2 Background
2.1 Blockchain Technology
2.2 Smart Contract in Block-chain Technology
2.3 Trust Computational Temporal Logic (TCTL)
3 Modeling Uncertainty in a Amart Contract System with Trust
3.1 3-Valued Propositional Logic
3.2 3-Valued TCTL
4 Model Checking 3v-TCTL
4.1 Reduction-based Model Checking 3v-TCTL
4.2 Case Study: A Smart Contract-based System for Drug Traceability in Healthcare Supply Chain
4.3 System Properties
4.4 Verification Results
5 Conclusion and Future Work
References
Author Index