Privacy-preserving data mining
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Introduction to cryptography: principles and applications
Introduction to cryptography: principles and applications
Executing SQL over encrypted data in the database-service-provider model
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Privacy preserving mining of association rules
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Order preserving encryption for numeric data
SIGMOD '04 Proceedings of the 2004 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
Incorporating a Secure Coprocessor in the Database-as-a-Service Model
IWIA '05 Proceedings of the Innovative Architecture on Future Generation High-Performance Processors and Systems
\ell -Diversity: Privacy Beyond \kappa -Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Answering top-k queries with multi-dimensional selections: the ranking cube approach
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
The new Casper: query processing for location services without compromising privacy
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Progressive and selective merge: computing top-k with ad-hoc ranking functions
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Private queries in location based services: anonymizers are not necessary
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Dominant Graph: An Efficient Indexing Structure to Answer Top-K Queries
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Blind evaluation of nearest neighbor queries using space transformation to preserve location privacy
SSTD'07 Proceedings of the 10th international conference on Advances in spatial and temporal databases
An attacker's view of distance preserving maps for privacy preserving data mining
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
A cryptography based privacy preserving solution to mine cloud data
Proceedings of the Third Annual ACM Bangalore Conference
Enabling search services on outsourced private spatial data
The VLDB Journal — The International Journal on Very Large Data Bases
Privacy-preserving outsourcing support vector machines with random transformation
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Privacy-preserving similarity measurement for access control policies
Proceedings of the 6th ACM workshop on Digital identity management
Towards location-based social networking services
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Location Based Social Networks
Privacy-preserving matching of spatial datasets with protection against background knowledge
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part I
Nearest neighbor search with strong location privacy
Proceedings of the VLDB Endowment
RASP: efficient multidimensional range query on attack-resilient encrypted databases
Proceedings of the first ACM conference on Data and application security and privacy
Shortest path computation with no information leakage
Proceedings of the VLDB Endowment
Authenticating location-based services without compromising location privacy
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Cooperative private searching in clouds
Journal of Parallel and Distributed Computing
Secure multidimensional range queries over outsourced data
The VLDB Journal — The International Journal on Very Large Data Bases
Thrifty privacy: efficient support for privacy-preserving publish/subscribe
Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems
Breaching Euclidean distance-preserving data perturbation using few known inputs
Data & Knowledge Engineering
Location privacy attacks based on distance and density information
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
Anonymous spatial query on non-uniform data
Proceedings of the 14th International Conference on Information Integration and Web-based Applications & Services
Efficient tree pattern queries on encrypted XML documents
Proceedings of the Joint EDBT/ICDT 2013 Workshops
Future Generation Computer Systems
Privacy-preserving multi-keyword text search in the cloud supporting similarity-based ranking
Proceedings of the 8th ACM SIGSAC symposium on Information, computer and communications security
Secure k-NN computation on encrypted cloud data without sharing key with query users
Proceedings of the 2013 international workshop on Security in cloud computing
Private proximity detection and monitoring with vicinity regions
Proceedings of the 12th International ACM Workshop on Data Engineering for Wireless and Mobile Acess
eSkyline: processing skyline queries over encrypted data
Proceedings of the VLDB Endowment
Secure k-NN query on encrypted cloud database without key-sharing
International Journal of Electronic Security and Digital Forensics
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Service providers like Google and Amazon are moving into the SaaS (Software as a Service) business. They turn their huge infrastructure into a cloud-computing environment and aggressively recruit businesses to run applications on their platforms. To enforce security and privacy on such a service model, we need to protect the data running on the platform. Unfortunately, traditional encryption methods that aim at providing "unbreakable" protection are often not adequate because they do not support the execution of applications such as database queries on the encrypted data. In this paper we discuss the general problem of secure computation on an encrypted database and propose a SCONEDB Secure Computation ON an Encrypted DataBase) model, which captures the execution and security requirements. As a case study, we focus on the problem of k-nearest neighbor (kNN) computation on an encrypted database. We develop a new asymmetric scalar-product-preserving encryption (ASPE) that preserves a special type of scalar product. We use APSE to construct two secure schemes that support kNN computation on encrypted data; each of these schemes is shown to resist practical attacks of a different background knowledge level, at a different overhead cost. Extensive performance studies are carried out to evaluate the overhead and the efficiency of the schemes.