Bachelor Thesis A Trust System for the openSUSE Build Service Saarland University Faculty of Natural Sciences and Technology I Department of Computer Science submitted by Marko Jung on 17th April 2009 Supervisor Professor Dr.-Ing. Thorsten Herfet Advisor Dr. Michael Schröder Reviewers Professor Dr.-Ing. Thorsten Herfet Professor Dr. Joachim Weickert Statement under Oath & Declaration of Consent I hereby confirm under oath that I have written this thesis on my own and that I have not used any other media or materials than the ones referred to in this thesis. I agree to make both versions of my thesis (with a passing grade) accessible to the public by having them added to the library of the Computer Science Department. Saarbrücken, 17th April 2009. Marko Jung Contents 1 Introduction 1 1.1 openSUSE Build Service . .1 1.2 Trust ......................................................3 1.2.1 Definitions of Trust . .4 1.2.2 Properties of Trust . .5 1.2.3 Trust Metrics . .6 1.3 Aim of the Study . .7 1.4 Outline of the Thesis . .7 2 Notation and Terminology9 2.1 Notation . .9 2.2 Terminology . .9 3 State of the Art 11 3.1 Classification of Trust Metrics . 12 3.1.1 Network Perspective . 12 3.1.2 Computation Locus . 13 3.1.3 Link Evaluation . 13 3.1.4 Selection Method . 14 3.2 Trust Metrics . 14 3.2.1 PageRank . 15 3.2.2 EigenTrust . 16 3.2.3 Advogato . 19 3.2.4 TidalTrust . 21 3.2.5 Appleseed . 23 4 Architecture 29 4.1 openSUSE Build Service Terminology . 29 4.2 Major Components of the openSUSE Build Service . 31 4.3 Trust for Software Packages . 34 4.4 User-specific Trust . 35 v 4.5 Design of the openSUSE Trust Server . 36 4.5.1 Management of Trust Relations . 37 4.5.2 Management and Storage of Trust Formulae . 39 4.5.3 Solving of Trust Formulae using Appleseed . 40 5 Validation 43 5.1 Artificial Networks . 43 5.1.1 Random Graphs . 43 5.1.2 Small-world Model . 48 5.1.3 Model of Barabási and Albert . 52 5.2 Advogato Real-world Network . 58 5.2.1 Data Sets . 59 5.2.2 Leave-one-out Cross-validation . 61 6 Discussion 65 6.1 Computation of Trust using the Appleseed Trust Metric . 65 6.2 Validation using artificially generated Networks . 67 6.3 Validation using the Advogato Data Set . 68 7 Outlook 71 A Mathematical Symbols and Functions 73 B Appleseed Example 75 C Trust Metric Algorithms 77 C.1 The PageRank Algorithm . 77 C.2 EigenTrust Algorithms . 78 C.2.1 Simple non-distributed EigenTrust . 78 C.2.2 Basic EigenTrust . 78 C.2.3 Distributed EigenTrust . 79 C.3 Advogato . 80 C.4 TidalTrust . 81 C.5 Appleseed . 83 D Further Simulations using the Small-world Model 85 D.1 Rewiring Probability p=0.30 ..................................... 86 D.2 Rewiring Probability p=0.45 ..................................... 88 D.3 Rewiring Probability p=0.60 ..................................... 90 D.4 Rewiring Probability p=0.75 ..................................... 92 D.5 Rewiring Probability p=0.90 ..................................... 94 Acknowledgements 97 Bibliography 99 List of Figures 1.1 openSUSE Build Service web-client . .2 3.1 Properties of Trust Metrics . 12 3.2 Scalar vs Group Trust Metrics . 13 3.3 PageRank: Simplified PageRank Calculation . 15 3.4 Advogato: Graph conversion . 20 3.5 Advogato: Calculation of the Network Flow . 22 3.6 TidalTrust: Determination of the Trust Threshold . 22 3.7 Appleseed: Node Chains . 24 3.8 Appleseed: Rank Sinks . 24 3.9 Appleseed: Normalisation Issue . 24 3.10 Appleseed: Backward Propagation . 24 3.11 Appleseed: Distribution of Trust and Distrust . 27 4.1 Example for an openSUSE Build Service Project . 30 4.2 Major Components of the openSUSE Build Service . 32 4.3 openSUSE Trust Service Web-Interface listing Trust Relations . 37 4.4 openSUSE Trust Service Web-Interface presenting a Trust Value . 41 5.1 Random Graphs: Example . 44 5.2 Random Graphs: General statistics . 46 5.3 Random Graphs: Maximal distributed Trust . 47 5.4 Random Graphs: Maximal distributed Trust vs discovered Nodes . 47 5.5 Small-world Model: Example . 48 5.6 Small-world Model: General Statistics . 50 5.7 Small-world Model: Maximal distributed Trust . 51 5.8 Small-world Model: Maximal distributed Trust vs discovered Nodes . 51 5.9 Model of Barabási and Albert: Example . 53 5.10 Model of Barabási and Albert using linear preferential Attachment: General Statistics . 54 5.11 Model of Barabási and Albert using quadratic preferential Attachment: General Statistics . 55 5.12 Model of Barabási and Albert using linear preferential Attachment: Maximal distributed Trust . 56 5.13 Model of Barabási and Albert using linear preferential Attachment: Maximal distributed Trust vs discovered Nodes . 56 5.14 Model of Barabási and Albert using quadratic preferential Attachment: Maximal distributed Trust . 57 5.15 Model of Barabási and Albert using quadratic preferential Attachment: Maximal distributed Trust vs discovered Nodes . 57 5.16 Advogato Data Set: Maximal distributed Trust vs discovered Nodes . 59 5.17 Advogato Data Set: General Statistics . 60 5.18 Advogato Data Set: Histograms for general Statistics . 60 5.19 Advogato Data Set: ROC Plots . 63 5.20 Advogato Data Set: Sensitivity vs Specificity Plot and Recall vs Precision Plot . 63 B.1 Appleseed: Test Network . 75 D.1 Small-world Model: General Statistics (p = 0.30) . 86 D.2 Small-world Model: Maximal distributed Trust (p = 0.30) . 87 D.3 Small-world Model: Maximal distributed Trust vs discovered Nodes (p = 0.30) 87 D.4 Small-world Model: General Statistics (p = 0.45) . ..