臺灣博碩士論文加值系統

本論文利用區塊鏈技術並結合多個密碼學的演算法來設計一套區塊鏈作業評分系統，其目的在於建立一個公平且透明的師生互動平台以確保每位學生在被評分時都能被平等對待、同時藉由可追蹤的活動紀錄來避免任何作弊和造假的行為。本論文中所設計的架構也將基於以太坊的開源碼實作出一套概念性的雛型平台：包括提出三個智能合約的設計來進一步增加評分的公平性以及分攤老師的評分工作。藉由這些設計，本論文期望能在師生互動方面提供更透明公平的機制且能鼓舞並督促每個成員扮演好自己的角色、用最正確的態度各盡各其責。

In this thesis, with the aid of multiple cryptography algorithms, a design of blockchain-based homework grading system is presented to establish a transparent and fair platform for teacher-student interactions. Our goal is to ensure the fairness and transparency of the mutual interaction between students and teachers so as to guarantee that all students being treated equally and the post-grade cheating events being prevented totally, by recording grading and grading activities on chain. To proof its applicability, the purposed work is realized on the basis of Ethereum source codes. Additionally, three autonomous smart contracts are also presented to enhance the design for providing more fairness to students and sharing more works from teachers. Combining all the above features, our work helps manage interaction between teachers and students and encourage every member to play their roles with accurate attitude.

CONTENTS

口試委員會審定書 i
誌謝 ii
中文摘要 iii
ABSTRACT iv
CONTENTS v
LIST OF FIGURES vii
LIST OF TABLES ix
Chapter 1 Introduction 1
Chapter 2 Background and Related Work 4
2.1 Blockchain 4
2.1.1 Decentralization [20] 4
2.1.2 Transparency: Trackability of Action 5
2.1.3 Proof-carrying of Data 5
2.1.4 Immutability 6
2.1.5 Anonymous 7
2.2 Blockchain in Education 8
2.3 Ethereum 10
Chapter 3 Basic Architecture and Definition of the Proposed System 11
3.1 Computational power 11
3.2 Regulations and Accounts 11
Chapter 4 Methodology 13
4.1 Member Interaction Models 13
4.1.1 Interaction Between Teacher(s) and Students 14
4.1.2 The Role of Teaching Assistant 17
4.1.3 Collective Grading 19
4.2 Smart Contract 22
4.2.1 Grading by Mutual Exchanging 24
4.2.2 Autonomous Correction and Grading 26
4.2.3 Contract for Supporting Collective Correction 27
4.3 Authentication 30
4.4 Consensus 34
Chapter 5 Experiments 36
5.1 Implementation 36
5.1.1 Application Tools 36
5.1.2 An Example of Teacher-Student Interaction 37
5.2 Smart Contract Pseudocodes 43
5.2.1 Grading by Mutual Exchange 43
5.2.2 Auto Correction 44
5.2.3 Collective Correction 46
5.3 Randomness of the Chaos-based Random Number Generator 48
5.4 Comparison with Related Work 50
Chapter 6 Discussion and Future Work 52
Chapter 7 Conclusion 55
REFERENCES 56
APPENDIX 59

LIST OF FIGURES

Fig. 2.1 Members uses their node to interact with blockchain. 4
Fig. 2.2 The Merkle Tree used in the Bitcoin. 6
Fig. 2.3 Relationships Between Different Layers of Features in Education. 8
Fig. 3.1 Basic Architecture and Definition of the Proposed System. 12
Fig. 4.1 Teacher-student interactions and grading procedures with the design models through the blockchain. 14
Fig. 4.2 Processes of Signing a Digital Signature to a Transaction. 15
Fig. 4.3 Interactions Between Teachers and Students. 17
Fig. 4.4 Interactions Among Teachers, TAs, and Students. 18
Fig. 4.5 Interactions Among the Responsible Teacher, Invited Judges, and Students in Collective Grading. 21
Fig. 4.6 Schematic Diagram of Smart Contract Based Grading by using Mutual Exchanging Mechanism. 26
Fig. 4.7 Schematic Diagram of Smart Contract Based Automous Grading System. 27
Fig. 4.8 Schematic Diagram of the Proposed Smart Contract Based Automous Collective Grading System 29
Fig. 4.9 Student generates secret pieces 32
Fig. 4.10 Teacher recovers a student’s secret code by retrieving secret pieces sent together with the hand-in homework. 32
Fig. 4.11 Teacher identify a student with the password (R_1) and the associated secret code. 33
Fig. 5.1 The application user interface for Teachers (left) and students (right). 37
Fig. 5.2 Procedures of the example of Teacher-Student Interaction. 37
Fig. 5.3 A student obtains the secret pieces. 38
Fig. 5.4 The teacher generates a key pair. 38
Fig. 5.5 The teacher assigns a homework to students. 39
Fig. 5.6 The student uses blockchain module to search messages. 39
Fig. 5.7 The student finds the assigned homework. 40
Fig. 5.8 The student encrypts his/her answers and a secret piece. 40
Fig. 5.9 The student submits his/her answers in ciphertext form to teacher. 41
Fig. 5.10 The teacher collects students’ submissions. 41
Fig. 5.11 The teacher decrypts students’ submissions. 41
Fig. 5.12 The teacher recovers the student’s secret code. 42
Fig. 5.13 Pseudocodes of the “Grading by Exchanging” smart contract. 44
Fig. 5.14 Pseudocodes of the “Auto Correction” smart contract. 45
Fig. 5.15 The mechanism of “SetGrade” to store scores. 46
Fig. 5.16 Pseudocodes of the “Collective Correction” smart contract. 47
Fig. 5.17 The noisy image generated with the seed value 12345678. 48
Fig. 5.18 The noisy image generated with the seed value 12345677. 49
Fig. 5.19 The difference image between the two noisy images given in Fig. 5.17 and Fig. 5.18. 49
Fig. 5.20 A traditional online course platform, CEIBA, developed by NTU. 50

LIST OF TABLES

Table 4.1 Statuses of all functions when function (2) is called. 24
Table 4.2 Influences to all functions by calling Function (2). 28
Table 5.1 Comparison of the purposed work and the traditional online course platform, CEIBA. 51

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