KNOWLEDGE DISCOVERY IN NEGATIVE DATABASE

Over the few recent years Knowledge discovery (data mining) has been establishing itself as one of the major disciplines in computer science with growing industrial environment. Research in data mining will continue and even increase over coming decades. In the other hand the need for data to still private against any hacking still growing dramatically. This paper considers the concept of data privacy through applying data mining techniques on negative database. The most important concept of a negative database is that a set of records (database) is represented by its complement set. That is, all the records not in DB are represented and DB itself is not explicitly stored. It is shown that a database consisting of n records, I-bit-length records can be represented negatively using its complement records. It is also shown that membership queries applied on DB can be processed over the negative representation itself This paper proposes a new data mining approach which is applied on a set of negative database (NDB). This approach enhances the security level for important internet applications