Privacy preservation in fuzzy association rules using rough computing and DSR

Application of DSR on Quantitative Association Rules Using Rough Set for Privacy Preservation

Customized Privacy Preservation Using Unknowns to Stymie Unearthing Of Association Rules

The explosions of new data mining techniques has augmented privacy risks because now it is probable to powerfully coalesce and cross-examine massive data stores, accessible on the web, in the rummage around of earlier unidentified hidden patterns. Consecutively to make a overtly accessible system safe and sound, we must guarantee not only that private sensitive data have been trimmed out, but a...

Computing Association Rules Using Partial Totals

The problem of extracting all association rules from within a binary database is well-known. Existing methods may involve multiple passes of the database, and cope badly with densely-packed database records because of the combinatorial explosion in the number of sets of attributes which must be considered. We present a new class of methods which use a single pass of the database to perform a pa...

Intrusion detection using fuzzy association rules

Vulnerabilities in common security components such as firewalls are inevitable. Intrusion Detection Systems (IDS) are used as another wall to protect computer systems and to identify corresponding vulnerabilities. In this paper a novel framework based on data mining techniques is proposed for designing an IDS. In this framework, the classification engine, which is actually the core of the IDS, ...

Anomaly detection using fuzzy association rules

Data mining techniques are a very important tool for extracting useful knowledge from databases. Recently, some approaches have been developed for mining novel kinds of useful information, such as anomalous rules. These kinds of rules are a good technique for the recognition of normal and anomalous behaviour, that can be of interest in several area domains such as security systems, financial da...