Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Foundations of Databases: The Logical Level
Foundations of Databases: The Logical Level
Privacy Preserving Data Mining
CRYPTO '00 Proceedings of the 20th Annual International Cryptology Conference on Advances in Cryptology
Tools for privacy preserving distributed data mining
ACM SIGKDD Explorations Newsletter
Building decision tree classifier on private data
CRPIT '14 Proceedings of the IEEE international conference on Privacy, security and data mining - Volume 14
Privacy preserving frequent itemset mining
CRPIT '14 Proceedings of the IEEE international conference on Privacy, security and data mining - Volume 14
Privacy Preserving Association Rule Mining
RIDE '02 Proceedings of the 12th International Workshop on Research Issues in Data Engineering: Engineering E-Commerce/E-Business Systems (RIDE'02)
A theoretical basis for perturbation methods
Statistics and Computing
Ontology-based distributed autonomous knowledge systems
Information Systems - Special issue on web data integration
How to generate and exchange secrets
SFCS '86 Proceedings of the 27th Annual Symposium on Foundations of Computer Science
Ensuring data security against knowledge discovery in distributed information systems
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
CHASE2: rule based chase algorithm for information systems of type λ
AM'03 Proceedings of the Second international conference on Active Mining
| Hi-index | 0.00 |
One of the key applications that uses the knowledge discovered by data mining is called Chase. Chase is a process that replaces null or missing values with the values predicted by the knowledge, and it is mainly used to obtain more complete information systems or to replace unknown attribute values in user queries. The process improves the quality of query answers with increased volume of reliable data, and helps the system understand user queries that would otherwise be difficult. However, a security breach may occur when a set of data in an information system is confidential. The confidential data can be hidden from the public view. However, Chase has the capability to reveal the hidden data by classifying them as null or missing. In this paper, we discuss disclosure of confidential data by Chase and protection algorithms that reduce the risk. In particular, the proposed algorithms aim to protect confidential data with the least amount of additional data hiding.