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Agent-Based Architecture for Privacy Payoff in Ecommerce

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Agent-Based Architecture for Privacy Payoff in Ecommerce AAPPeC: Agent-based Architecture for Privacy Payoff in eCommerce by Abdulsalam Yassine A thesis submitted to the Faculty of Graduate and Postdoctoral Studies In partial fulfillment of the requirements for the degree of Doctor of Philosophy in Electrical and Computer Engineering Ottawa-Carleton Institute for Electrical and Computer Engineering School of Information Technology and Engineering Faculty of Engineering University of Ottawa Abdulsalam Yassine, Ottawa, Canada, 2010 Acknowledgements Writing this thesis marks the happy conclusion of the journey that I started a few years ago. Throughout the journey, I greatly and sincerely benefited from the support and companionship of many people. First and foremost, I had the great fortune of being supervised by a very supportive and helpful supervisor. His integrity, dedication, insightful advice, and encouragement have greatly contributed in fulfilling this degree, and so I give my heartfelt gratitude to Dr. Shervin Shirmohammadi. Throughout my thesis-study period, he was always there for me with prompt guidance and feedback and lots of good ideas. I would have been lost without his support. I will never find the words to thank him for believing in me and giving me the chance to pursue this degree, and I much regret the fact that I will have had little chance to pay him back for his kindness. I have enormous gratitude for Dr. Thomas T. Tran, my co-supervisor, for his help, rich discussions, and sound advice. His valuable comments on my work and experienced guidance were significant in shaping the quality of this research. For that reason, it is difficult to put into words the debt that I owe to Dr. Thomas T. Tran. During the last two years, I have had the pleasure of working with Dr. Ali Nazari, for whom I am greatly thankful. His technical expertise combined with his friendship has been very helpful to me during the critical stages of this work. I would especially thank him for his excellent work on helping me build the experimental tests. I also wish to dedicate my thanks to my parents from the bottom of my heart. Although they are physically far away from me, I feel they are with me all the time. It is their unconditional support and love that have made all my accomplishments possible. ii Last, but certainly not least, I would like to express my sincere gratitude to my family, especially my beloved wife Reem and my two beautiful kids Mostafa and Yasmine for all the sacrifices and patience, and, most importantly, for their understanding that sometimes “I am extremely busy.” iii Abstract With the rapid development of applications in open distributed environments such as eCommerce, privacy of information is becoming a critical issue. Today, many online companies are gathering information and have assembled sophisticated databases that know a great deal about many people, generally without the knowledge of those people. Such information changes hands or ownership as a normal part of eCommerce transactions, or through strategic decisions that often includes the sale of users’ information to other firms. The key commercial value of users’ personal information derives from the ability of firms to identify consumers and charge them personalized prices for goods and services they have previously used or may wish to use in the future. A look at present-day practices reveals that consumers’ profile data is now considered as one of the most valuable assets owned by online businesses. In this thesis, we argue the following: if consumers’ private data is such a valuable asset, should they not be entitled to commercially benefit from their asset as well? The scope of this thesis is on developing architecture for privacy payoff as a means of rewarding consumers for sharing their personal information with online businesses. The architecture is a multi-agent system in which several agents employ various requirements for personal information valuation and interaction capabilities that most users cannot do on their own. The agents in the system bear the responsibility of working on behalf of consumers to categorize their personal data objects, report to consumers on online businesses’ trustworthiness and reputation, determine the value of their compensation using risk-based financial models, and, finally, negotiate for a payoff value in return for the dissemination of users’ information. iv Table of Contents Acknowledgements ii Abstract iv List of Figures viii List of Tables x List of Definitions xi List of Acronyms xii List of Symbols xiii Chapter 1. Introduction 1 1.1 Research Motivation ........................................................................................ 2 1.1.1 Motivating Example .............................................................................. 4 1.2 Research Problem ............................................................................................ 6 1.3 Research Goal and Objectives ......................................................................... 8 1.4 Main Contributions ........................................................................................ 11 1.4.1 Peer-reviewed Publications .................................................................. 12 1.5 Road Map ...................................................................................................... 14 Chapter 2. Privacy – Background and Issues 15 2.1 Introduction ................................................................................................... 15 2.2 Property, Privacy, and the Right to Private Data ........................................... 16 2.3 Reflections on Property Rights over Private Data ......................................... 17 2.4 Summary........................................................................................................ 18 Chapter 3. Related Work 20 3.1 Introduction ................................................................................................... 20 3.2 Agent-based eCommerce Systems ................................................................ 20 3.3 Privacy Systems in eCommerce .................................................................... 24 3.3.1 Access Control Privacy Systems ......................................................... 24 3.3.2 Privacy Negotiation Systems ............................................................... 29 3.3.3 Privacy Enhancement through Trust and Reputation Systems ............ 30 3.4 Classification of Related Work...................................................................... 33 3.5 Summary........................................................................................................ 37 Chapter 4. AAPPeC Architecture 39 4.1 Introduction ................................................................................................... 39 4.2 High-level View ............................................................................................ 39 4.3 Database Agent .............................................................................................. 46 v 4.3.1 Attribute Ontology ................................................................................ 47 4.3.2 Data Classification ................................................................................ 48 4.3.3 Risk Quantification ............................................................................... 50 4.4 Trust and Reputation Agent ........................................................................... 54 4.4.1 Fuzzy Engine ........................................................................................ 58 4.4.2 Fuzzy Rules .......................................................................................... 60 4.4.3 Privacy Credential Report .................................................................... 61 4.5 Payoff Agent .................................................................................................. 62 4.5.1 Payoff Calculation ............................................................................... 63 4.6 Negotiation Agent ......................................................................................... 67 4.6.1 Negotiation Strategy ............................................................................ 68 4.6.2 Offer Construction ............................................................................... 71 4.6.3 Negotiation Protocol ............................................................................ 73 4.7 Facilitator Agent ............................................................................................ 74 4.7.1 Communication Module ...................................................................... 75 4.7.2 Task Manager ...................................................................................... 76 4.7.3 Decision Manager ................................................................................ 77 4.8 Summary........................................................................................................ 77 Chapter 5. AAPPeC design specification 79 5.1 Introduction ................................................................................................... 79 5.2 Overview of the Gaia Methodology .............................................................. 80 5.3 JADE Overview ............................................................................................. 82 5.4 Using Gaia and JADE for AAPPeC Design .................................................. 84 5.4.1 Requirements ......................................................................................
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