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研究生： 曾亭媗
Ting-Hsuan Tseng
論文名稱： 行動使用者環境下的位置導向身分鑑別協定
Location-based Authentication Protocols for Mobile User Environments
指導教授： 羅乃維
Nai-Wei Lo
口試委員: 賴源正
Yuan-Cheng Lai
楊傳凱
Chuan-Kai Yang
學位類別： 碩士
Master
系所名稱： 管理學院 - 資訊管理系
Department of Information Management
論文出版年： 2016
畢業學年度： 104
語文別： 英文
論文頁數： 76
中文關鍵詞： 網路協定電視 、個人化服務 、身分鑑別 、行動裝置 、臉部識別
外文關鍵詞： IPTV, Personalized Services, Authentication, Mobile Device, Face Recognition  
相關次數： 點閱：347  下載：4 
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    • 隨著行動裝置的普及，加上行動裝置的優點是無論何時何地皆能透過無線網路即可使用服務，帶給現代人們便利性。而無線網路與現存的有線網路相較之下，帶來更多的安全威脅。因此，本篇論文考慮行動裝置的移動性與無線網路下的安全威脅，例如：非法存取、傳輸中的資料被竄改等，我們提出適用在各種環境下授予合法使用者透過行動裝置享受服務的身分鑑別機制。我們的環境分為家庭環境與特定地點環境，而家庭環境結合了網路協定電視（Internet Protocol TV，IPTV）提供使用者移動式網路協定電視( Mobile IPTV ) 個人化服務。
    在本研究中，我們結合臉部識別技術與行動裝置提出基於家庭與特定地點環境下的三套安全的身分鑑別協定，可用於新穎的商業模式。分別為一套適用於家庭環境下的協定為Household-based Authentication Protocol，以及兩套適用於特定地點環境下分別為Location-based Authentication Protocol與Location-based ECC Authentication Protocol。通過身分鑑別的使用者，在家庭下可以使用IPTV供應商所提供的個人化服務，在特定地點環境下，透過不同地區搭配不同的機制可讓使用者享受個人化服務，進而提高利潤。經實驗與分析表明，本機制可滿足安全性需求並提供良好的系統易用性、可部署性及服務擴展性。

    With the increasing popularity of mobile devices, services can be accessed via wireless networks anytime and anywhere. However, the wireless environment has more security threats than wired networks. Therefore, this thesis is concerned with the mobility of mobile devices and security threats in wireless networks, such as unauthorized access, data integrity, etc. We proposed an authentication and authorization mechanism for mobile devices in various environments. The application environments can be divided into household and public location environments with the household environment combined with IPTV to provide mobile IPTV personalized services for authorized users.
    In this thesis, we proposed three authentication protocols by using face recognition and mobile devices in household-based and public location environments, which can be used for new business models. The first is the household-based authentication protocol used for the domestic environment. The second and third are the location-based authentication protocol and location-based ECC (Elliptic curve cryptography) authentication protocol for the public location environment. The authenticated user can be permitted to use the personalized services by the IPTV providers offered in the household environment. In the public location environment, service providers can use different regions with different mechanisms which allows users to enjoy personalized services, thereby increasing profits. The experiments and analysis show that the proposed mechanisms can meet the security requirements and provide great system usability, deploy ability and service scalability for personalized services.

    中文摘要 I Abstract II 誌謝 III Contents IV List of Figures VI List of Tables VII Chapter 1　Introduction 1 Chapter 2　Related Work 8 2.1　Face Recognition and Automatic Age Estimation 8 2.1.1 Face Recognition in Practice 10 2.2.2 Automatic Age Estimation 12 2.2　 Authentication Mechanism in Mobile IPTV 14 2.3　Threat Model 16 Chapter 3　Proposed Authentication Protocols 18 3.1　Overview 18 3.2　Notations 22 3.3　Household-based Authentication Protocol 23 3.3.1　Registration Phase 23 3.3.2　Authentication Phase 27 3.3.3　Password Update Phase 30 3.4　Location-based Authentication Protocols 36 3.4.1　Location-based Authentication Protocol 36 3.4.2　 Location-based ECC Authentication Protocol 41 Chapter 4　 Security Analysis 46 4.1　Household-based Authentication Protocol 46 4.1.1　Mutual Authentication 46 4.1.2　 Resistance to an Impersonation Attack 47 4.1.3　 Resistance to a Replay Attack 48 4.1.4　 Resistance to a Man-in-the-Middle Attack 49 4.1.5　 Resistance to a Server Spoofing Attack 50 4.2　Location-based Authentication Protocol 50 4.2.1　 Mutual Authentication 50 4.2.2　 Resistance to an Impersonation Attack 51 4.2.3　 Resistance to a Replay Attack 51 4.2.4　 Resistance to a Man-in-the-Middle Attack 52 4.2.5　 Resistance to Server Spoofing Attack 52 4.3　 Location-based ECC Authentication Protocol 52 4.3.1　Mutual Authentication 53 4.3.2　 Resistance to an Impersonation Attack 53 4.3.3　 Resistance to a Replay Attack 54 4.3.4　 Resistance to a Man-in-the-Middle Attack 54 4.3.5　 Resistance to a Server Spoofing Attack 54 Chapter 5　Performance Analysis 56 5.1　 Prototype Implementation 56 5.2　 Experiment Evaluation 59 Chapter 6　Discussion 63 6.1　Three-Factor Authentication 63 6.2　How to Do XOR Calculation for Values in Set of Vector and Hash Value 66 Chapter 7　Conclusion 68 Appendix 1 69 References 71

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