Behavior Dynamics in Media-Sharing Social Networks

Half-title......Page 3
Title......Page 5
Copyright......Page 6
Dedication......Page 7
Contents......Page 9
Preface......Page 13
Part I: Introduction......Page 15
1 Introduction to media-sharing social networks......Page 17
1.1 Quantitative analysis of social networks......Page 19
1.1.1.2 Notations......Page 20
1.1.2 Centrality and prestige......Page 21
1.1.4 Structural equivalence......Page 23
1.2 Understanding media semantics in media-sharing networks......Page 24
1.2.1 Social media annotation......Page 25
1.2.3 Emergent semantics......Page 26
2 Overview of multimedia fingerprinting......Page 28
2.1 Traitor-tracing multimedia fingerprinting......Page 29
2.2 Scalable video coding system......Page 31
2.3 Scalable video fingerprinting......Page 32
2.3.2 Multiuser collusion attacks......Page 33
2.3.3 Fingerprint detection and colluder identification......Page 36
2.3.4 Performance criteria......Page 37
3 Overview of mesh-pull peer-to-peer video streaming......Page 38
3.1.1 Mesh formation......Page 39
3.1.2 Video streaming services......Page 42
3.1.3.2 Quality metrics......Page 44
3.1.3.3 Security threats......Page 46
3.2 User dynamics in peer-to-peer video streaming......Page 47
3.2.1 Peer selection......Page 48
3.2.2 Incentives......Page 50
3.2.2.2 Chunk answering based on differential service......Page 51
3.2.2.3 Incentives for super nodes......Page 52
3.2.2.4 Incentives based on video quality......Page 53
4 Game theory for social networks......Page 55
4.1 Noncooperative and cooperative games......Page 56
4.2.1 Pure-strategy Nash equilibriums......Page 57
4.2.2 Mixed-strategy equilibriums......Page 58
4.2.3.2 Subgame perfection......Page 60
4.2.3.3 Stable equilibrium......Page 62
4.2.4 Equilibrium improvement......Page 63
4.3.1 Axiomatic bargaining model......Page 64
4.3.2 Strategic bargaining model......Page 65
Part II: Behavior forensics in media-sharing social networks......Page 69
5.1 Equal-risk collusion......Page 71
5.1.1 Analysis of the detection statistics......Page 72
5.1.2 Selection of the collusion parameters......Page 73
5.1.2.1 Highest-quality colluded copy......Page 74
5.1.2.2 Medium-quality colluded copy......Page 75
5.1.3 Summary of parameter selection to achieve fairness during collusion......Page 76
5.2.1 Statistical analysis on traitor-tracing capacity......Page 77
5.2.2 Simulation results with ideal gaussian models......Page 79
5.2.3 Simulation results on video sequences......Page 83
5.3.1.1 Upper and lower bounds of Kmax......Page 89
5.3.1.2 Calculation of…......Page 92
5.3.2 Catch-more......Page 93
5.3.3 Catch-all......Page 94
5.4 Chapter summary and bibliographical notes......Page 96
6.1 Probing and using side information......Page 99
6.1.1.1 Collective fingerprint detector......Page 100
6.1.1.2 Fingerprint detection at each layer......Page 101
6.1.2 Performance comparison of detection types......Page 102
6.1.3 Colluder identification with side information......Page 103
6.1.4 Performance analysis and simulation results......Page 104
6.1.5 Impact of side information on fairness of multiuser collusion......Page 106
6.2 Game-theoretic analysis of colluder detector dynamics......Page 107
6.3.1 Min–max formulation......Page 108
6.3.2 Analysis of the maximum mean......Page 109
6.3.2.1 For colluder…......Page 110
6.3.2.2 For colluder…......Page 111
6.3.3.1 Scenario 1......Page 112
6.3.3.2 Scenario 2......Page 113
6.3.3.4 Scenario 4......Page 114
6.3.3.6 Scenario 6......Page 115
6.3.4 Min–max solution......Page 116
6.4 Simulation results......Page 117
6.5 Chapter summary and bibliographical notes......Page 123
7 Risk–distortion analysis of multiuser collusion......Page 125
7.1.2 Fingerprint detection......Page 126
7.2.1 Risk of the colluders......Page 127
7.2.2 Distortion of the colluded frame......Page 128
7.2.3 The risk-distortion relationship......Page 129
7.2.4 Initialization for CCCP......Page 130
7.3.1 Optimal strategy for the detector......Page 131
7.3.2 Optimal strategy for attackers with side information......Page 132
7.3.3 Min–max strategy for the attacker: worst-case scenario......Page 133
7.3.4 Without additive noise......Page 134
7.3.5 Risk reduction using additive white gaussian noise......Page 135
7.5 Simulation results......Page 136
7.6 Chapter summary and bibliographical notes......Page 141
Part III: Fairness and cooperation stimulation......Page 143
8 Game-theoretic modeling of colluder social networks......Page 145
8.1 Multiuser collusion game......Page 146
8.1.2 Utility function definition......Page 147
8.1.2.1 Probability of being detected…......Page 148
8.1.2.2 Reward R(i)......Page 150
8.2.1 Feasible set......Page 151
8.2.2 Pareto optimality......Page 152
8.3 When to collude......Page 153
8.3.1.1 Colluders’ utility functions......Page 154
8.3.1.2 Analysis of the minimal number of colluders......Page 156
8.3.2.1 Colluders’ payoff functions......Page 157
8.3.2.2 Lower and upper bounds of the collusion parameter beta......Page 158
8.3.2.3 Analysis of the number of colluders......Page 159
8.4 How to collude: the bargaining model......Page 164
8.4.1 Fair collusion with non–time-restricted bargaining......Page 167
8.4.2 Time-restricted bargaining......Page 168
8.5.1 Scenario 1: Reward is independent of risk......Page 169
8.5.1.1 Bargaining solutions......Page 170
8.5.1.2 Simulation setting and results......Page 171
8.5.2 Scenario 2: Reward is proportional to risk......Page 172
8.5.3 Scenario 3: Time-restricted bargaining......Page 173
8.6.1 Single-resolution collusion......Page 174
8.6.2 Multiresolution collusion......Page 177
8.6.3 Simulation results......Page 179
8.7 Chapter summary and bibliographical notes......Page 181
9 Cooperation stimulation in peer-to-peer video streaming......Page 183
9.1.1 Mesh-pull P2P live streaming......Page 184
9.1.2 Two-player game model......Page 185
9.1.3 Nash equilibrium refinement......Page 187
9.1.3.2 Proportional fairness......Page 188
9.1.4.1 Cheating on private information......Page 189
9.1.4.2 Cheating on buffer map information......Page 190
9.1.5 Performance of the cheat-proof cooperation strategy......Page 191
9.2.1 Wireless video streaming model......Page 192
9.2.2 Two-player game model......Page 193
9.3 Optimal cooperation strategies for wireless video streaming......Page 195
9.3.1 Nash equilibrium refinement......Page 196
9.3.2.1 Cheating on private information......Page 199
9.3.2.2 Cheating on buffer map information......Page 200
9.3.2.3 Cheating on transmission power......Page 201
9.3.3 Simulation results for two-user case......Page 202
9.4 Optimal chunk request algorithm for P2P video streaming with scalable coding......Page 203
9.4.2 Video quality measure......Page 204
9.4.3 Optimal chunk-request algorithms......Page 205
9.5 Chapter summary and bibliographical notes......Page 207
10.1 Introduction......Page 209
10.2 System model......Page 210
10.3 Optimal strategies for single secondary buyer......Page 212
10.3.1 Video stream redistribution game definition......Page 213
10.3.2.1 Secondary buyer’s optimal strategy......Page 214
10.3.3 Existence of the equilibrium......Page 216
10.3.4 Simulation results......Page 218
10.4.1 Game model......Page 220
10.4.2 Mixed-strategy equilibrium......Page 221
10.5 Optimal pricing for the content owner......Page 222
10.5.1 Pricing game model and evolution dynamics......Page 224
10.5.2 Analysis of pricing game with homogeneous mobile users......Page 226
10.5.3 Analysis of pricing game with heterogeneous mobile users......Page 228
10.5.4 Simulation results......Page 230
10.6 Chapter summary and bibliographical notes......Page 231
Part IV: Misbehaving user identification......Page 233
11 Cheating behavior in colluder social networks......Page 235
11.1.1 Precollusion processing using temporal filtering......Page 236
11.1.2 Risk minimization and tradeoff analysis......Page 237
11.1.3 Simulation results......Page 239
11.2.1 Changing the resolution of the fingerprinted copies before collusion......Page 241
11.2.1.1 Increasing resolution before multiuser collusion......Page 242
11.2.1.2 Reducing resolution before multiuser collusion......Page 247
11.2.2 Performance comparison of different strategies......Page 249
11.2.2.2 For cheating colluders in subgroup SCb,e1......Page 251
11.2.2.3 For cheating colluders in SCall......Page 254
11.2.3 Simulation results on real video......Page 257
11.3 Chapter summary......Page 259
12 Attack resistance in peer-to-peer video streaming......Page 261
12.1.1 Misbehavior in P2P video streaming......Page 262
12.1.2 Game model......Page 263
12.1.3.1 Credit mechanism......Page 264
12.1.3.2 Incomplete chunk attack detection......Page 266
12.1.3.3 Multiuser cooperation stimulation strategies......Page 267
12.1.4 Strategy analysis without malicious attackers......Page 268
12.1.5 Strategy analysis with malicious attackers......Page 270
12.1.6 Simulation results......Page 272
12.2.1 Game model......Page 275
12.2.2.1 Hand-wash attack and trust model......Page 278
12.2.3 Strategy analysis......Page 280
12.2.4 Overrequest for broadcast nature......Page 281
12.2.5 Attack-resistant P2P wireless video-sharing cooperation strategy with overrequest......Page 282
12.2.6 Simulation settings......Page 283
12.2.7 Performance evaluation......Page 284
12.3 Chapter summary and bibliographical notes......Page 287
Part V: Media-sharing social network structures......Page 289
13 Misbehavior detection in colluder social networks with different structures......Page 291
13.1.1 Misbehavior detection and identification......Page 292
13.1.2 Performance criteria......Page 293
13.2 Centralized colluder social networks with trusted ringleaders......Page 294
13.2.1 Detection of temporal-interpolation–based precollusion processing......Page 295
13.2.2 Identification of cheating colluders......Page 298
13.2.3.2 Performance evaluation......Page 301
13.3.1.1 Calculation of Dj (k, l)......Page 303
13.3.1.2 Autonomous detection and identification of cheating colluders......Page 304
13.3.2.1 Group of cheating colluders......Page 305
13.3.2.2 Multiple assistants for each subgroup......Page 307
13.3.2.3 Performance analysis......Page 308
13.3.3 Resistance to framing attacks......Page 312
13.3.3.2 Nonoverlapping content to each assistant......Page 313
13.3.3.3 Performance analysis......Page 315
13.3.4 Autonomous cheating colluder detection and identification process......Page 319
13.4 Chapter summary and bibliographical notes......Page 320
14 Structuring cooperation for hybrid peer-to-peer streaming......Page 322
14.1.2 Utility functions......Page 323
14.2 Agent selection within a homogeneous group......Page 325
14.2.2 Distributed agent selection......Page 326
14.2.4 Analysis of the cooperative streaming game......Page 327
14.3 Agent selection within a heterogeneous group......Page 331
14.3.1 Two-player game......Page 332
14.3.2 Multiplayer game......Page 333
14.5 Simulation results......Page 334
14.6 Chapter summary and bibliographical notes......Page 339
References......Page 340
Index......Page 349