Data structures and algorithms for disjoint set union problems
ACM Computing Surveys (CSUR)
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Generalizing data to provide anonymity when disclosing information (abstract)
PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Optimal aggregation algorithms for middleware
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Algorithms and Theory of Computation Handbook
Algorithms and Theory of Computation Handbook
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Achieving k-anonymity privacy protection using generalization and suppression
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Optimal aggregation algorithms for middleware
Journal of Computer and System Sciences - Special issu on PODS 2001
Using GPS to learn significant locations and predict movement across multiple users
Personal and Ubiquitous Computing
Robust and fast similarity search for moving object trajectories
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Location Privacy in Mobile Systems: A Personalized Anonymization Model
ICDCS '05 Proceedings of the 25th IEEE International Conference on Distributed Computing Systems
Towards Privacy-Aware Location-Based Database Servers
ICDEW '06 Proceedings of the 22nd International Conference on Data Engineering Workshops
Protection of Location Privacy using Dummies for Location-based Services
ICDEW '05 Proceedings of the 21st International Conference on Data Engineering Workshops
The new Casper: query processing for location services without compromising privacy
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Time-focused clustering of trajectories of moving objects
Journal of Intelligent Information Systems
Anonymous Usage of Location-Based Services Through Spatial and Temporal Cloaking
Proceedings of the 1st international conference on Mobile systems, applications and services
Trajectory clustering: a partition-and-group framework
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Preserving privacy in gps traces via uncertainty-aware path cloaking
Proceedings of the 14th ACM conference on Computer and communications security
Best position algorithms for top-k queries
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Mining Infrequent Itemsets Based on Multiple Level Minimum Supports
ICICIC '07 Proceedings of the Second International Conference on Innovative Computing, Informatio and Control
A conceptual view on trajectories
Data & Knowledge Engineering
Private queries in location based services: anonymizers are not necessary
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Privacy Preservation in the Publication of Trajectories
MDM '08 Proceedings of the The Ninth International Conference on Mobile Data Management
Privacy-Preserving Publication of User Locations in the Proximity of Sensitive Sites
SSDBM '08 Proceedings of the 20th international conference on Scientific and Statistical Database Management
Protecting Privacy in Continuous Location-Tracking Applications
IEEE Security and Privacy
Towards trajectory anonymization: a generalization-based approach
SPRINGL '08 Proceedings of the SIGSPATIAL ACM GIS 2008 International Workshop on Security and Privacy in GIS and LBS
Anonymizing moving objects: how to hide a MOB in a crowd?
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Mining interesting locations and travel sequences from GPS trajectories
Proceedings of the 18th international conference on World wide web
A Hybrid Prediction Model for Moving Objects
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Trajectory Outlier Detection: A Partition-and-Detect Framework
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Never Walk Alone: Uncertainty for Anonymity in Moving Objects Databases
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Private Queries and Trajectory Anonymization: a Dual Perspective on Location Privacy
Transactions on Data Privacy
Privacy Preserving Publication of Moving Object Data
Privacy in Location-Based Applications
Walking in the crowd: anonymizing trajectory data for pattern analysis
Proceedings of the 18th ACM conference on Information and knowledge management
Preventing velocity-based linkage attacks in location-aware applications
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
A reciprocal framework for spatial K-anonymity
Information Systems
Inference attacks on location tracks
PERVASIVE'07 Proceedings of the 5th international conference on Pervasive computing
Efficient k-anonymization using clustering techniques
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
Anonymization of moving objects databases by clustering and perturbation
Information Systems
An online framework for publishing privacy-sensitive location traces
Proceedings of the Ninth ACM International Workshop on Data Engineering for Wireless and Mobile Access
Preserving privacy in semantic-rich trajectories of human mobility
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Security and Privacy in GIS and LBS
Providing K-Anonymity in location based services
ACM SIGKDD Explorations Newsletter
Hiding Sequential and Spatiotemporal Patterns
IEEE Transactions on Knowledge and Data Engineering
Nearest neighbor search with strong location privacy
Proceedings of the VLDB Endowment
Protecting privacy against location-based personal identification
SDM'05 Proceedings of the Second VDLB international conference on Secure Data Management
On the anonymity of periodic location samples
SPC'05 Proceedings of the Second international conference on Security in Pervasive Computing
A formal model of obfuscation and negotiation for location privacy
PERVASIVE'05 Proceedings of the Third international conference on Pervasive Computing
Differentially private sequential data publication via variable-length n-grams
Proceedings of the 2012 ACM conference on Computer and communications security
Privacy-preserving distributed monitoring of visit quantities
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
A two-phase algorithm for mining sequential patterns with differential privacy
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Efficient Time-Stamped Event Sequence Anonymization
ACM Transactions on the Web (TWEB)
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Recent years have witnessed pervasive use of location-aware devices such as GSM mobile phones, GPS-enabled PDAs, location sensors, and active RFID tags. The use of these devices generates a huge collection of spatio-temporal data, variously called moving object data, trajectory data, or moblity data. These data can be used for various data analysis purposes such as city traffic control, mobility management, urban planning, and location-based service advertisements. Clearly, the spatio-temporal data so collected may help an attacker to discover personal and sensitive information like user habits, social customs, religious and sexual preferences of individuals. Consequently, it raises serious concerns about privacy. Simply replacing users' real identifiers (name, SSN, etc.) with pseudonyms is insufficient to guarantee anonymity. The problem is that due to the existence of quasi-identifiers, i.e., spatio-temporal data points that can be linked to external information to re-identify individuals, the attacker may be able to trace the anonymous spatio-temporal data back to individuals. In this survey, we discuss recent advancement on anonymity preserving data publishing of moving object databases in an off-line fashion. We first introduce several anonymity models, then we describe in detail some of the proposed techniques to enforce trajectory anonymity, discussing their merits and limitations. We conclude by identifying challenging open problems that need attention.