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系統識別號 U0026-0209201619264800
論文名稱(中文) 互信與互惠:食品安全物聯網
論文名稱(英文) Trust and Reciprocity: Internet of Things for Food Security and Safety
校院名稱 成功大學
系所名稱(中) 電腦與通信工程研究所
系所名稱(英) Institute of Computer & Communication
學年度 104
學期 2
出版年 105
研究生(中文) 沈育緯
研究生(英文) Yu-Wei Shen
學號 Q36024214
學位類別 碩士
語文別 英文
論文頁數 38頁
口試委員 口試委員-高嘉宏
口試委員-斯國峰
指導教授-焦惠津
中文關鍵字 可信度  信譽系統  協同合作  食品安全  物聯網 
英文關鍵字 Trustworthiness  Reputation System  Collaboration  Food Security and Safety  Internet of Things 
學科別分類
中文摘要 物聯網(Internet of Things)因為行動裝置的普及而受到重視,透過物件(Things)之間的互相連結並且交換可蒐集的資料,利用這些資料以更有效率的方式達成目標或是提供新型的服務,促使我們的生活更加便利。然而物聯網的概念是讓這些互連的物件協同合作,彼此貢獻資料產生更大的效益,而協同合作需建立在互信的基礎之上。但在物聯網的情境中,不同的物件能隨時能連結到物聯網路中,對於每一個物聯網中的物件來說,要在如此大量的物件中分辨哪些物件是可信的是極為困難的。在這篇論文中,以一個四個面向的模型定義物聯網,分別為互連、互動、互信與互惠。依循此模型建立一個以食品安全為目標的物聯網系統,並在互信的面向中提出一套信譽系統(Reputation System)的名聲演算法來協助系統中的使用者建立彼此的互信關係。利用系統中各個使用者過去的行為和互相評價,去計算每一個使用者的名聲值以及其貢獻的資料的可信度,禁止名聲值較低的使用者在系統中提供任何資訊,並給予名聲值較高之使用者獎勵,藉此留下值得信賴的使用者並吸引更多使用者加入,協助物聯網中的使用者建立互信關係。論文中提供兩個模擬實驗驗證演算法的有效性,在第一個實驗中追蹤物件的行為變化與對應的名聲值變化關係,第二個計算演算法的精準度(Precision)與召回率(Recall)。結果顯示演算法確實能夠有足夠的精準度與召回率,並依據行為區別出不同的使用者,協助物件建立互信關係。
英文摘要 The Internet of Things attracts attention recently because of popularity of mobile devices. The idea of Internet of Things is to connect all cyber things, physical things and people together. They can exchange data and achieve their own goals more effectively with these exchanged data. The fundamental of Internet of Things is collaboration. While Collaboration depends on trust, all things must trust each other. In the context of Internet of Things, large amount of things can connect at anytime. It is difficult to discriminate between trustworthy things and untrustworthy things. In this thesis, a four phase model of Internet of Things is provided. The four phases are interconnection phase, interaction phase, mutual trust phase and reciprocity phase in sequence. A system called Trustworthy Food Information System (TFIS) was built for maintaining food security and safety. It follows the four phase model of Internet of Things and apply a new reputation calculation algorithm proposed in this thesis to help users build mutual trust in the system. The algorithm calculates all users’ reputation scores and trustworthiness of provided data according to behavior history and ratings made by each other. TFIS restricts the low-reputation users to provide any data and gives high-reputation users rewards. It helps all users establish trust on each other. Two simulations are performed to evaluate the effectiveness of the algorithm. The result shows the algorithm can discriminate the users and helps users to build mutual trust.
論文目次 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1
2 Background and Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.1 Internet of Things . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4
2.2 Reputation System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
3 Four Phase Model of Internet of Things . . . . . . . . . . . . . . . . . . . . . . . . .8
4 Trustworthy Food Information System . . . . . . . . . . . . . . . . . . . . . . . . . .11
4.1 Identity Management System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
4.2 Community Management System and Community Platform . . . . . . . . . . . 13
4.2.1 Food Information Community . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
4.2.2 Food Knowledge System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .17
4.3 Reputation Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
4.3.1 Reputation Calculation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
4.3.2 Trustworthiness Calculation . . . . . . . . . . . . . . . . . . . . . . . . . . . .22
4.3.3 Initialization of Reputation Algorithm . . . . . . . . . . . . . . . . . . . . . . 23
5 Experiment Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
5.1 Simulation Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
5.2 Simulation Result . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
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