Guide to biometrics:
Saved in:
| Format: | Book |
|---|---|
| Language: | English |
| Published: |
New York
Springer
2004
|
| Series: | Springer professional computing
|
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XIX, 364 Seiten Illustrationen |
| ISBN: | 0387400893 |
Staff View
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| 245 | 1 | 0 | |a Guide to biometrics |c Ruud M. Bolle |
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Record in the Search Index
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| adam_text |
RUUD M. BOLLE JONATHAN H. CONNELL SHARATH PANKANTI NALINI K. RATHA
ANDREW W. SENIOR WBIOMETRICS WITH 131 ILLUSTRATIONS SPRINGER CONTENTS
LIST OF FIGURES XIII LIST OF TABLES XXI FOREWORD XXV PREFACE XXVII I
BASICS OF BIOMETRICS 1 1 INTRODUCTION 3 1.1 PERSON AUTHENTICATION, IN
GENERAL 4 1.2 A QUICK OVERVIEW OF BIOMETRICS 6 1.2.1 BIOMETRIC
IDENTIFIERS 6 1.2.2 BIOMETRIC SUBSYSTEMS 7 1.2.3 SYSTEM PERFORMANCE AND
DESIGN ISSUES 8 1.2.4 COMPETING SYSTEM DESIGN ISSUES 10 1.3 BIOMETRIC
IDENTIFICATION 11 1.4 BIOMETRIC VERIFICATION 12 1.5 BIOMETRIC ENROLLMENT
13 1.6 BIOMETRIC SYSTEM SECURITY 14 2 AUTHENTICATION AND BIOMETRICS 17
2.1 SECURE AUTHENTICATION PROTOCOLS 17 2.2 ACCESS CONTROL SECURITY
SERVICES 18 2.3 AUTHENTICATION METHODS 20 2.4 AUTHENTICATION PROTOCOLS
22 2.5 MATCHING BIOMETRIC SAMPLES 24 2.5.1 IDENTIFICATION 25 2.5.2
SCREENING 26 2.5.3 VERIFICATION 26 2.5.4 CONTINUITY OF IDENTITY 26 2.6
VERIFICATION BY HUMANS 27 2.7 PASSWORDS VERSUS BIOMETRICS 28 VI CONTENTS
2.8 HYBRID METHODS 29 3 THE COMMON BIOMETRICS 31 3.1 FINGERPRINT
RECOGNITION 31 3.1.1 ACQUISITION DEVICES 32 3.1.2 MATCHING APPROACHES 34
3.1.3 MINUTIAE 35 3.2 FACE RECOGNITION 36 3.2.1 IMAGING 36 3.2.2 LOCAL
AND GLOBAL MODELS 37 3.2.3 CHALLENGES 39 3.3 SPEAKER RECOGNITION 40
3.3.1 APPLICATION CATEGORIES 41 3.3.2 ACOUSTIC FEATURES 42 3.4 IRIS
RECOGNITION 43 3.5 HAND GEOMETRY 45 3.6 SIGNATURE VERIFICATION 47 4
ADDITIONAL BIOMETRICS 51 4.1 DNA 52 4.2 RETINA RECOGNITION 53 4.3
THERMOGRAMS 54 4.4 GAIT 55 4.5 KEYSTROKE 56 4.6 EAR RECOGNITION 56 4.7
SKIN REFLECTANCE 57 4.8 LIP MOTION 57 4.9 BODY ODOR 58 II PERFORMANCE
AND SELECTION 61 5 BASIC SYSTEM ERRORS 63 5.P MATCHING 63 5.1.1 TWO
KINDS OF ERRORS 65 5.1.2 SCORE DISTRIBUTIONS 66 5.1.3 ESTIMATING ERRORS
FROM DATA 68 5.1.4 ERROR RATES OF MATCH ENGINES 69 5.1.5 DEFINITIONS OF
FAR AND FRR, POSITIVE AUTHENTICATION 70 5.2 THE RECEIVER OPERATING
CHARACTERISTIC (ROC) 70 5.2.1 VARIATIONS ON ROCS 72 5.2.2 USING THE ROC
CURVE 73 5.2.3 EXPRESSING THE "QUALITY" OF A ROC CURVE 74 5.3 ERROR
CONDITIONS "SPECIFIC" TO BIOMETRICS 78 5.4 NEGATIVE AUTHENTICATION 79
5.5 TRADE-OFFS 81 CONTENTS VII 5.5.1 CONVENIENCE VERSUS SECURITY 81
5.5.2 COST VERSUS SECURITY OF POSITIVE AUTHENTICATION 82 5.5.3 COST OF
NEGATIVE AUTHENTICATION 83 6 IDENTIFICATION SYSTEM ERRORS 87 6.1 PROBLEM
OVERVIEW 88 6.1.1 WINNOWING 89 6.1.2 APPROACHES AND IMPLEMENTATIONS 89
6.1.3 OPEN AND CLOSED WORLDS 90 6.1.4 RANKING VERSUS SCORING 91 6.1.5
IDENTITIES VERSUS TEMPLATES 94 6.2 GENERIC EVALUATION CRITERIA 94 6.2.1
RELIABILITY AND SELECTIVITY 94 6.2.2 THE RECALL PRECISION CURVE 96 6.3
THRESHOLD-BASED IDENTIFICATION 97 6.3.1 SIMPLE FAR(M) ANDFRR(M) 98 6.3.2
UNAMBIGUOUS ANSWERS 99 6.4 RANK-BASED IDENTIFICATION 101 6.4.1
RANK-ORDER STATISTICS 101 6.4.2 RANK PROBABILITY MASS (RPM) FUNCTION 102
6.4.3 CHOOSING THE LIST LENGTH 103 7 PERFORMANCE TESTING 105 7.1
MEASURING PERFORMANCE 105 7.1.1 TECHNOLOGY EVALUATIONS 106 7.1.2
SCENARIO EVALUATIONS 108 7.1.3 COMPARISON OF THE METHODS 108 7.1.4
LIMITS TO EVALUATION 110 7.2 IMPLICATIONS OF ERROR RATES ILL 7.3 FACE,
FINGER, AND VOICE 113 7.4 IRIS AND HAND 114 7.5 SIGNATURE 117 7.6
SUMMARY OF VERIFICATION ACCURACIES 120 7.7 IDENTIFICATION SYSTEM TESTING
121 7.7.1 BIOMETRIC DATA AND ROC, CMC 121 7.7.2 BIOMETRIC SEARCH ENGINES
122 7.7.3 1: M SEARCH ENGINE TESTING 123 7.7.4 FACE RECOGNITION AND
VERIFICATION TEST 2000 125 7.7.5 FRVT 2002 126 7.8 CAVEATS 127 8
SELECTING A BIOMETRIC 129 8.1 BIOMETRIC ATTRIBUTES 130 8.1.1 SENSOR
PROPERTIES 131 8.1.2 TEMPLATE SIZES 131 8.1.3 SCALABILITY 132 VIII
CONTENTS 8.2 APPLICATION PROPERTIES . T 133 8.2.1 WAYMAN'S APPLICATION
TAXONOMY 133 8.2.2 WEIGHTING THE FACTORS 135 8.3 EVALUATING OPTIONS 138
8.3.1 MISMATCH CALCULATION 138 8.3.2 ZEPHYR* CHARTS 141 8.3.3 OPEN
COMPETITIONS FOR COMPARING BIOMETRICS 142 8.4 AFFORDABILITY AND COST 144
8.5 POSITIVES AND NEGATIVES OF THE BIOMETRICS 145 8.5.1 FINGERPRINT 146
8.5.2 FACE 146 8.5.3 VOICE 147 8.5.4 IRIS 148 8.5.5 HAND 148 8.5.6
SIGNATURE 149 8.6 BIOMETRIC MYTHS AND MISREPRESENTATIONS 150 III SYSTEM
ISSUES 155 9 CREATING AND MAINTAINING DATABASES 157 9.1 ENROLLMENT
POLICIES 158 9.1.1 ENROLLMENT FOR POSITIVE AUTHENTICATION 159 9.1.2
ENROLLMENT FOR SCREENING 160 9.1.3 SOCIAL ISSUES 161 9.2 THE ZOO 162 9.3
BIOMETRIC SAMPLE QUALITY CONTROL 164 9.4 TRAINING 166 9.4.1 TRAINING AND
MODELING 167 9.4.2 THERE ARE TWO ASPECTS TO TRAINING 167 9.5 ENROLLMENT
IS SYSTEM TRAINING 169 9.5.1 DATABASE INTEGRITY 170 9.5.2 PROBABILISTIC
ENROLLMENT . 172 9.5.3 MODELING THE WORLD 172 9.5.4 MODELING THE REST OF
THE WORLD*COHORTS 173 9.5.5 UPDATING THE PROBABILITIES 175 9.5.6 USE OF
THE PROBABILITIES 176 10 LARGE-SCALE APPLICATIONS 177 10.1 EXAMPLE
SYSTEMS 177 10.2 REQUIRED ACCURACIES 179 10.2.1 ENROLLMENT FALSE
POSITIVES 179 10.2.2 ENROLLMENT FALSE NEGATIVES 181 10.2.3
AUTHENTICATION ACCURACY 181 10.3 MATCHER SIZING 182 10.3.1 MATCH
THROUGHPUT 182 CONTENTS IX 10.3.2 TOTAL NUMBER OF MATCHES 183 10.4
EXCEPTION HANDLING 184 10.5 VOTER REGISTRATION 186 10.6 NATIONAL ID
SYSTEMS 188 10.7 HOW FEASIBLE IS LARGE SCALE? 191 11 INTEGRATING
INFORMATION 193 11.1 INTEGRATION METHODS 193 11.2 DECISION LEVEL
INTEGRATION 196 11.2.1 BOOLEAN COMBINATION 196 11.2.2 BINNING AND
FILTERING 198 11.2.3 DYNAMIC AUTHENTICATION PROTOCOLS 201 11.3 SCORE
LEVEL INTEGRATION 203 11.3.1 NORMAL DISTRIBUTIONS 205 11.3.2 DEGENERATE
CASES 207 11.3.3 FROM THRESHOLDS TO BOUNDARIES 208 11.4 ALTERNATIVES 210
12 THWARTING ATTACKS 211 12.1 PATTERN RECOGNITION MODEL 211 12.2
ATTACKING BIOMETRIC IDENTIFIERS 213 12.3 FRONT-END ATTACKS 215 12.4
CIRCUMVENTION 216 12.5 BACK-END ATTACKS 217 12.6 OTHER ATTACKS 219 12.7
COMBINING SMARTCARDS AND BIOMETRICS 220 12.8 CHALLENGE AND RESPONSE 221
12.9 CANCELLABLE BIOMETRICS 222 12.9.1 PRIVACY 222 12.9.2 INTENTIONAL,
REPEATABLE TRANSFORMS 224 12.9.3 SIGNAL DOMAIN DISTORTIONS 224 12.9.4
FEATURE DOMAIN DISTORTIONS 226 12.9.5 RELATION TO COMPRESSION AND
ENCRYPTION 226 13 APIS, STANDARDS, AND DATABASES 229 13.1 INTERFACE
STANDARDS 229 13.1.1 APPLICATION PROGRAMMING INTERFACES 230 .13.1.2 DATA
STRUCTURE AND SECURITY STANDARDS 231 13.2 DATABASES 233 13.2.1
FINGERPRINT DATABASES 233 13.2.2 FACE DATABASES 235 13.2.3 SPEAKER
RECOGNITION DATABASES 237 13.2.4 OTHER DATABASES 238 13.3 CERTIFICATIONS
239 13.4 LEGISLATION 241 X CONTENTS IV MATHEMATICAL ANALYSES 243 14 A
BIOMETRIC'S INDIVIDUALITY 245 14.1 APPROACHES TO INDIVIDUALITY 245 14.2
EMPIRICAL INDIVIDUALITY STUDIES 247 14.3 A PARTIAL IRIS MODEL 248 14.3.1
FAR MODELING 249 14.3.2 FRR CALCULATION 251 14.3.3 NUMERIC EVALUATION
251 14.4 FINGERPRINT INDIVIDUALITY 253 14.4.1 A SIMPLE MODEL 254 14.4.2
PROBABILISTIC SCORING 256 14.4.3 A MORE COMPLEX MODEL 257 14.4.4 MODEL
COMPARISON 260 14.4.5 IMPOSING STRUCTURE 261 14.4.6 MINUTIAE
DISTRIBUTIONS 262 14.5 STANDARDS FOR LEGAL EVIDENCE 263 14.6 EXPERT
FINGERPRINT TESTIMONY 264 14.7 REMARKS 267 15 SYSTEM ERRORS REVISITED
269 15.1 ESTIMATING THE MATCH SCORE MEAN 270 15.1.1 CONFIDENCE INTERVALS
271 15.1.2 PARAMETRIC METHOD 271 15.1.3 NONPARAMETRIC METHODS 272 15.1.4
ESTIMATING THE QUANTILES 274 15.1.5 THE BOOTSTRAP 275 15.2 THE DATA ARE
NOT INDEPENDENT 277 15.2.1 HOW ARE THE DATA OBTAINED? 277 15.2.2 THE
SUBSETS BOOTSTRAP 278 15.2.3 ESTIMATING THE MATCH SCORE MEAN (CONTINUED)
279 15.3 CONFIDENCE INTERVALS ON THE FRR AND FAR 280 15.3.1
DISTRIBUTIONS F AND A G SPECIFY THE ENGINE 280 15.3.2 ERROR IN THE FRR
ESTIMATE 282 15.3.3 ERROR IN THE FAR ESTIMATE 283 15.4 HOW GOOD ARE THE
CONFIDENCE INTERVALS? 286 15.4.1 THE SET OF SAMPLES X 287 15.4.2 MORE
INDEPENDENT SAMPLES X L5 X 2 , 288 15.4.3 THE MATCH SCORE SET X 289
15.4.4 CONFIDENCE INTERVAL VALIDATION 290 15.4.5 SAMPLE MEANS VERSUS THE
TRUE MEAN 291 CONTENTS XI 16 ADVANCED TOPICS 293 16.1 WHAT IS NEEDED TO
COMPARE MATCHERS? 294 16.2 THE DATA NEEDED TO COMPARE MATCHERS 295 16.3
COST FUNCTIONS IN DETAIL 296 16.3.1 STATISTICAL TESTS USING COSTS 299
16.3.2 ESTIMATING OPERATING THRESHOLDS 300 16.4 STATISTICAL TESTS AT
FIXED FRR OR FAR 302 16.4.1 THE FAR IS KNOWN 303 16.4.2 ESTIMATING THE
FAR FIRST 304 16.5 BIOMETRIC SEARCHING AND SORTING*THE CMC 305 16.5.1
ESTIMATING THE CMC 306 16.5.2 CLOSED UNIVERSE 308 16.5.3 THE CMC,
FAR/FRR RELATION 309 16.5.4 OPENING UP THE CLOSED WORLD 314 16.6
BIOMETRIC SEARCHING AND RANKING 315 16.6.1 MATCHING VERSUS SEARCHING 315
16.6.2 BIOMETRIC SEARCH ENGINE 316 16.6.3 RANK ENGINE 317 16.6.4 SEARCH
ERRORS 319 16.6.5 PROBABILITY OF CORRECT IDENTIFICATION 320 16.7 ROC
VERSUS CMC 322 17 WHAT'S NEXT? 325 17.1 RECOMMENDATIONS 326 17.2 CURRENT
ISSUES 328 17.3 THE FUTURE 330 17.4 A FINAL WORD 333 REFERENCES 335
INDEX 353 |
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| spelling | Guide to biometrics Ruud M. Bolle New York Springer 2004 XIX, 364 Seiten Illustrationen txt rdacontent n rdamedia nc rdacarrier Springer professional computing Biometric identification Identification Automation Pattern recognition systems Biometrie (DE-588)4124925-2 gnd rswk-swf Biometrie (DE-588)4124925-2 s DE-604 Bolle, Ruud M. Sonstige oth HEBIS Datenaustausch Darmstadt application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=012951216&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Guide to biometrics Biometric identification Identification Automation Pattern recognition systems Biometrie (DE-588)4124925-2 gnd |
| subject_GND | (DE-588)4124925-2 |
| title | Guide to biometrics |
| title_auth | Guide to biometrics |
| title_exact_search | Guide to biometrics |
| title_full | Guide to biometrics Ruud M. Bolle |
| title_fullStr | Guide to biometrics Ruud M. Bolle |
| title_full_unstemmed | Guide to biometrics Ruud M. Bolle |
| title_short | Guide to biometrics |
| title_sort | guide to biometrics |
| topic | Biometric identification Identification Automation Pattern recognition systems Biometrie (DE-588)4124925-2 gnd |
| topic_facet | Biometric identification Identification Automation Pattern recognition systems Biometrie |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=012951216&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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