THE FUNDAMENTALS Introduction Data Collection and Data Publishing What Is Privacy-Preserving Data Publishing? Related Research Areas Attack Models and Privacy Models Record Linkage Model Attribute Linkage Model Table Linkage Model Probabilistic Model Modeling Adversary''s Background Knowledge Anonymization Operations Generalization and Suppression Anatomization and Permutation Random Perturbation Information Metrics General Purpose Metrics Special Purpose Metrics Trade-Off Metrics Anonymization Algorithms Algorithms for the Record Linkage Model Algorithms for the Attribute Linkage Model Algorithms for the Table Linkage Model Algorithms for the Probabilistic Attack Attacks on Anonymous Data ANONYMIZATION FOR DATA MINING Anonymization for Classification Analysis Introduction Anonymization Problems for Red Cross BTS High-Dimensional Top-Down Specialization (HDTDS) Workload-Aware Mondrian Bottom-Up Generalization Genetic Algorithm Evaluation Methodology Summary and Lesson Learned Anonymization for Cluster Analysis Introduction Anonymization Framework for Cluster Analysis Dimensionality Reduction-Based Transformation Related Topics Summary EXTENDED DATA PUBLISHING SCENARIOS Multiple Views Publishing Introduction Checking Violations of k-Anonymity on Multiple Views Checking Violations with Marginals Multi-Relational k-Anonymity Multi-Level Perturbation Summary Anonymizing Sequential Releases with New Attributes Introduction Monotonicity of Privacy Anonymization Algorithm for Sequential Releases Extensions Summary Anonymizing Incrementally Updated Data Records Introduction Continuous Data Publishing Dynamic Data Republishing HD-Composition Summary Collaborative Anonymization for Vertically Partitioned Data Introduction Privacy-Preserving Data Mashup Cryptographic Approach Summary and Lesson Learned Collaborative Anonymization for Horizontally Partitioned Data Introduction Privacy Model Overview of the Solution Discussion ANONYMIZING COMPLEX DATA Anonymizing Transaction Data Introduction Cohesion Approach Band Matrix Method km-Anonymization Transactional k-Anonymity Anonymizing Query Logs Summary Anonymizing Trajectory Data Introduction LKC-Privacy (k, δ)-Anonymity MOB k-Anonymity Other Spatio-Temporal Anonymization Methods Summary Anonymizing Social Networks Introduction General Privacy-Preserving Strategies Anonymization Methods for Social Networks Data Sets Summary Sanitizing Textual Data Introduction ERASE Health Information DE-identification (HIDE) Summary Other Privacy-Preserving Techniques and Future Trends Interactive Query Model Privacy Threats Caused by Data Mining Results Privacy-Preserving Distributed Data Mining Future Directions References the Record Linkage Model Algorithms for the Attribute Linkage Model Algorithms for the Table Linkage Model Algorithms for the Probabilistic Attack Attacks on Anonymous Data ANONYMIZATION FOR DATA MINING Anonymization for Classification Analysis Introduction Anonymization Problems for Red Cross BTS High-Dimensional Top-Down Specialization (HDTDS) Workload-Aware Mondrian Bottom-Up Generalization Genetic Algorithm Evaluation Methodology Summary and Lesson Learned Anonymization for Cluster Analysis Introduction Anonymization Framework for Cluster Analysis Dimensionality Reduction-Based Transformation Related Topics Summary EXTENDED DATA PUBLISHING SCENARIOS Multiple Views Publishing Introduction Checking Violations of k-Anonymity on Multiple Views Checking Violations with Marginals Multi-Relational k-Anonymity Multi-Level Perturbation Summary Anonymizing Sequential Releases with New Attributes Introduction Monotonicity of Privacy Anonymization Algorithm for Sequential Releases Extensions Summary Anonymizing Incrementally Updated Data Records Introduction Continuous Data Publishing Dynamic Data Republishing HD-Composition Summary Collaborative Anonymization for Vertically Partitioned Data Introduction Privacy-Preserving Data Mashup Cryptographic Approach Summary and Lesson Learned Collaborative Anonymization for Horizontally Partitioned Data Introduction Privacy Model Overview of the Solution Discussion ANONYMIZING COMPLEX DATA Anonymizing Transaction Data Introduction Cohesion Approach Band Matrix Method km-Anonymization Transactional k-Anonymity Anonymizing Query Logs Summary Anonymizing Trajectory Data Introduction LKC-Privacy (k, δ)-Anonymity MOB k-Anonymity Other Spatio-Temporal Anonymization Methods Summary Anonymizing Social Networks Introduction General Privacy-Preserving Strategies Anonymization Methods for Social Networks Data Sets Summary Sanitizing Textual Data Introduction ERASE Health Information DE-identification (HIDE) Summary Other Privacy-Preserving Techniques and Future Trends Interactive Query Model Privacy Threats Caused by Data Mining Results Privacy-Preserving Distributed Data Mining Future Directions References DED DATA PUBLISHING SCENARIOS Multiple Views Publishing Introduction Checking Violations of k-Anonymity on Multiple Views Checking Violations with Marginals Multi-Relational k-Anonymity Multi-Level Perturbation Summary Anonymizing Sequential Releases with New Attributes Introduction Monotonicity of Privacy Anonymization Algorithm for Sequential Releases Extensions Summary Anonymizing Incrementally Updated Data Records Introduction Continuous Data Publishing Dynamic Data Republishing HD-Composition Summary Collaborative Anonymization for Vertically Partitioned Data Introduction Privacy-Preserving Data Mashup Cryptographic Approach Summary and Lesson Learned Collaborative Anonymization for Horizontally Partitioned Data Introduction Privacy Model Overview of the Solution Discussion ANONYMIZING COMPLEX DATA Anonymizing Transaction Data Introduction Cohesion Approach Band Matrix Method km-Anonymization Transactional k-Anonymity Anonymizing Query Logs Summary Anonymizing Trajectory Data Introduction LKC-Privacy (k, δ)-Anonymity MOB k-Anonymity Other Spatio-Temporal Anonymization Methods Summary Anonymizing Social Networks Introduction General Privacy-Preserving Strategies Anonymization Methods for Social Networks Data Sets Summary Sanitizing Textual Data Introduction ERASE Health Information DE-identification (HIDE) Summary Other Privacy-Preserving Techniques and Future Trends Interactive Query Model Privacy Threats Caused by Data Mining Results Privacy-Preserving Distributed Data Mining Future Directions References STRONG> Introduction Privacy-Preserving Data Mashup Cryptographic Approach Summary and Lesson Learned Collaborative Anonymization for Horizontally Partitioned Data Introduction Privacy Model Overview of the Solution Discussion ANONYMIZING COMPLEX DATA Anonymizing Transaction Data Introduction Cohesion Approach Band Matrix Method km-Anonymization Transactional k-Anonymity Anonymizing Query Logs Summary Anonymizing Trajectory Data Introduction LKC-Privacy (k, δ)-Anonymity MOB k-Anonymity Other Spatio-Temporal Anonymization Methods Summary Anonymizing Social Networks Introduction General Privacy-Preserving Strategies Anonymization Methods for Social Networks Data Sets Summary Sanitizing Textual Data Introduction ERASE Health Information DE-identification (HIDE) Summary Other Privacy-Preserving Techniques and Future Trends Interactive Query Model Privacy Threats Caused by Data Mining Results Privacy-Preserving Distributed Data Mining Future Directions References ;lt;BR>Other Spatio-Temporal Anonymization Methods Summary Anonymizing Social Networks Introduction General Privacy-Preserving Strategies Anonymization Methods for Social Networks Data Sets Summary Sanitizing Textual Data Introduction ERASE Health Information DE-identification (HIDE) Summary Other Privacy-Preserving Techniques and Future Trends Interactive Query Model Privacy Threats Caused by Data Mining Results Privacy-Preserving Distributed Data Mining Future Directions References.