Design and Implementation of a Machine Learning Data Storage Model Using Blockchain Technology

Design and Implementation of a Machine Learning Data Storage Model Using Blockchain Technology

Project / Seminar Material
Reference ID: PS-25170-TM

DEDICATION

This research material titled “Design and Implementation of a Machine Learning Data Storage Model Using Blockchain Technology” is dedicated to God for his enabling grace, and to all computer enthusiasts who contributed to make life a pleasant experience during my research documentation.

ACKNOWLEDGEMENT

I extend my sincere gratitude to all those who contributed to the completion of this project. Special thanks to my Supervisor (Name of your Supervisor), the Head of Department (Name of your HOD), the Lecturers in the department of Computer Science (CS), Book Authors and Profound Scholars of existing or related project material on “Design and Implementation of a Machine Learning Data Storage Model Using Blockchain Technology” for their invaluable guidance, support, and expertise throughout the journey.

I am also grateful to your study area (mention any funding organizations, if applicable) for their financial assistance. This research would not have been possible without the encouragement and assistance of some stakeholders (mention any mentors, teachers, or colleagues). Additionally, I would like to acknowledge the understanding and patience of my family and friends during this endeavor. Your unwavering support has been a constant source of motivation. Thank you all for being part of this meaningful endeavor.

Design and Implementation of a Machine Learning Data Storage Model Using Blockchain Technology

TABLE OF CONTENTS

PRELIMINARY PAGES

CHAPTER ONE

INTRODUCTION

  • 1.1 Introduction
  • 1.2 Background of Study
  • 1.3 Statement of Problem
  • 1.4 Aim and Objectives of the Study
  • 1.5 Significance of Study
  • 1.6 Scope of Study
  • 1.7 Limitations of the Study
  • 1.8 Definition of Terms

CHAPTER TWO

LITERATURE REVIEW

  • 2.1 Introduction
  • 2.2 Conceptual Review
  • 2.3 Overview of Machine Learning
  • 2.4 Types of Machine Learning Algorithms
  • 2.5 Overview of Blockchain Technology
  • 2.5.1 Comparison between Block Chain and Central Databases
  • 2.6 Theoretical Framework of Machine Learning
  • 2.7 Integration of Machine Learning in Blockchain-Based Applications

CHAPTER THREE

SYSTEM ANALYSIS AND DESIGN

  • 3.1 Methodology Adopted
  • 3.1.1 Problem Identification Using SSADM
  • 3.2 Analysis of the Existing System
  • 3.2.1 Dataflow of the Existing System
  • 3.2.2 Disadvantages Of The Existing System
  • 3.2.3 Weakness of the existing System
  • 3.3 Feasibility Study
  • 3.3.1 Economic Feasibility
  • 3.3.2 Technical Feasibility
  • 3.3.3 Operational Feasibility
  • 3.4 Analysis of the Proposed System
  • 3.4.1 Data Flow Diagram of the Proposed System
  • 3.4.2 Advantages of the Proposed System
  • 3.4.3 Justification of the Proposed System
  • 3.5 Functional Requirements
  • 3.5.1 Use Case Diagram Of The Admin / User Privileges
  • 3.6 Data Requirements
  • 3.7 High Level Model of the Proposed System

CHAPTER FOUR

SYSTEM DESIGN AND IMPLEMENTATION

  • 4.1 Objectives of the Design
  • 4.2 Cohesion and Decomposition High level Model
  • 4.3 Control Center / Overall Dataflow Diagram
  • 4.3.1 Proposed System Operation Flowchart
  • 4.4 System Specification and Design
  • 4.4.1 Input and Output Specification
  • 4.4.2 Database Specification and Design
  • 4.4.3 Data Dictionary
  • 4.5 Choice and Justification of Programming Language
  • 4.6 Program Documentation
  • 4.7 Implementation Techniques
  • 4.8 Programming Module Specification
  • 4.8.1 Installation
  • 4.8.2 Security Design Specification
  • 4.8.3 System Architecture
  • 4.9 Computer Hardware Minimum Requirement
  • 4.10 Software Requirement
  • 4.11 Personnel / User Training

CHAPTER FIVE

SUMMARY, CONCLUSION AND RECOMMENDATION

  • 5.1 Introduction
  • 5.2 Summary
  • 5.3 Conclusion
  • 5.4 Recommendation

REFERENCES

APPENDIX A - “SOURCE CODE”

APPENDIX B - “OBJECT PROGRAM”

ABSTRACT

Machine learning (ML) is the study of computer algorithms that can improve automatically through experience and by the use of data. It is seen as a part of artificial intelligence. The aim of the study is to design and implement A Machine Learning Data Storage Model Using Blockchain Technology. In achieving this aim, the following specific objectives were laid out as follows to design a machine learning data storage model solution using Bitcoin Blockchain and implement the Bitcoin Blockchain machine learning data storage model design. The motivation that led to the implementation of the proposed system is as a result of the problem facing Machine Learning which is the lack of good data such as; noisy data, dirty data, and incomplete data are the quintessential enemies of ideal Machine Learning. The methodology adopted in this study is the structured system analysis and design methodology (SSADM) which is a technical approach for analyzing and designing an application or system by applying object throughout the software development process. The programming language used is HTML, CSS, JAVASCRIPT, PHP, SQL and JQUERY. The reason why web programming languages was used is because, it is platform independent and it is a web based application. Machine learning has improved the quality of lives of humans by providing a number of applications to facilitate human living. Among the numerous applications of machine learning in the field of health, science, industries etc. is the timely detection of diseases. It is in this regard that Machine Learning has remained significant over the years. The expected result is A Machine Learning Data Storage Model Using Blockchain Technology system that will provide an effective storage model for web search and it will also provide language translation mechanism that will help worldwide communications and limiting the great language barrier among countries.

Design and Implementation of a Machine Learning Data Storage Model Using Blockchain Technology

CHAPTER ONE

1.1 Introduction

Machine learning (ML) is the study of computer algorithms that can improve automatically through experience and by the use of data. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning is at work all around us today, when we interact with banks, shop online, or use social media, machine learning algorithms come into play to make our experience efficient, smooth, and secure. Machine learning and the technology around it are developing rapidly, and we're just beginning to scratch the surface of its capabilities. A blockchain is a distributed database that uses cryptographically signed transactions and is shared among the nodes of a computer network. It works in a block-by-block fashion, with each block having its own cryptographic system.

As a prelude to other parts of this study, this chapter will discuss the background upon which this study was initiated, the statement of problems that led to this study, the Aim and Objectives of the study. Others are Significance of the study, Scope of work, Limitations of the Study and Definition of technical terms.

1.2 Background of Study

Machine learning models can make predictions or conduct data analysis using the data stored in the Bitcoin blockchain network. Consider any smart BT-based application in which data is collected from various sources such as sensors, smart devices, and IoT devices, and the Bitcoin blockchain in this application functions as an integral part of the application, where a machine learning model can be applied to the data for real-time data analytics or predictions. Storing data on the Bitcoin blockchain reduces ML model errors because the data in the network does not contain missing values, duplicates, or noise, which is a key prerequisite for a machine learning model to achieve higher accuracy. The learning capabilities of ML can be applied to blockchains based applications to make them smarter. By using ML security of the distributed ledger may be improved. ML may also be used to enhance the time taken to reach consensus by building better data sharing routes. Further, it creates an opportunity to build better models by taking advantage of the decentralized architecture of BT.

Blockchains are an immutable set of records that are cryptographically linked together for audit (Zheng et al., 2017). It is similar to an accounting ledger. The previous records in accounting ledger cannot be changed, and new records need to be verified by a trusted party. The only difference between these two is that new block (set of records) checked by a decentralized structure of nodes that have a copy of the ledger. There is no centralized party to verify the records. Bitcoin is a decentralized electronic currency that represents a significant shift in the global financial system. Its system is peer-to-peer and encrypted in nature, and it is not controlled by any government or bank. Satoshi Nakamoto proposed Bitcoin in 2008, and the Bitcoin ecosystem has grown fast since then. It's also the most successful of hundreds of attempts to utilize cryptography to produce virtual money. Hundreds of imitators have followed in Bitcoin's footsteps, yet it remains the most valuable cryptocurrency by market capitalization. Bitcoin was a game changer in the global financial sector since it was the first successful project to use Blockchain technology. As a result, this research shows how Machine Learning may be used to solve Bitcoin issues.

1.3 Statement of Problem

Investigation reveals that the number one problem facing Machine Learning is the lack of good data. While enhancing algorithms often consumes most of the time of developers in AI, data quality is essential for the algorithms to function as intended. Noisy data, dirty data, and incomplete data are the quintessential enemies of ideal Machine Learning. It's becoming increasingly difficult to separate fact from fiction in terms of Machine Learning today. Before you decide on which AI platform to use, you need to evaluate which problems you’re seeking to solve. The easiest processes to automate are the ones that are done manually every day with no variable output. Complicated processes require further inspection before automation. While Machine Learning can definitely help automate some processes, not all automation problems need Machine Learning (Provintl, 2021).

1.4 Aim and Objectives of the Study

The aim of the study is to design and implement a Machine Learning Data Storage Model using Blockchain Technology. In achieving this aim, the following specific objectives were laid out as follows:

  1. To design a machine learning data storage model solution using Bitcoin Blockchain; and
  2. To implement the Bitcoin Blockchain machine learning data storage model design.

1.5 Significance of Study

Machine learning has improved the quality of lives of humans by providing a number of applications to facilitate human living. Among the numerous applications of machine learning in the field of health, science, industries etc. is the timely detection of diseases such as cancer, glaucoma and other diseases which are claiming human lives at a jaw-breaking rate, the visualization of smart cars, effective web search which has made the internet searches more easy, language translations are immensely helping in worldwide communications and limiting the great language barrier among countries, realization of fraud detection and face recognition systems to mention but a few are greatly helping to improve the quality of life of humans. It is in this regard that Machine Learning has remained significant over the years.

This study will be of immense benefit to software engineers and other researchers who intend to know more on this study and can also be used by non-researchers to build more on their research work. This study contributes to knowledge and could serve as a guide for other study.

1.6 Scope of Study

The scope of the research is focused on the Design and Implementation of Machine Learning Data Storage Model using Blockchain Technology.

1.7 Limitations of the Study

During the course of this study, many things militated against its completion, some of which are:

  1. Time Constraint: The time frame given to accomplish this project was very short due to school academic calendar and it was carried out under pressure which made the researcher not to implement some necessary features.
  2. Research material: availability of research material is a major setback to the scope of the study.
  3. Frequent power failure: This made the researcher append more money on fuel to ensure sustainable power.
  4. Financial Constraint: Insufficient fund tends to impede the efficiency of the researcher in sourcing for the relevant materials, literature or information and in the process of data collection (internet).

1.8 Definition of Terms

Blockchain: A blockchain is a distributed database that uses cryptographically signed transactions and is shared among the nodes of a computer network.

Registration: This means to keep records received from the management for reference purposes.

Management: It is the co-ordination of all the resources of an Organization through the process of planning, Organization, directing and controlling

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CHAPTER TWO

2.0 Literature Review

2.1 Introduction

This chapter focuses on the review of related literature. A literature review includes the current knowledge as well as theoretical and methodological contributions to a particular topic. It documents the state of the art with respect to the topic you are writing. It surveys the literature in the topic selected. In this research work the literature review includes the …

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