Efficient discover of association rules in large databases is a we 1 studied problem and several ap-1y proaches have been proposed. However, it is non trivial to maintain the association rules current when the database is updated since, such updates could invalidate existing rules or introduce new rules. In this paper, we propose an incremental updating technique btied on tie ittive borders, for the maintenance of aSsociation ru es when new transaction data is added tof or deleted from a transaction database. An important feature of our algorithm is that it requires a full scan(exactly one) of the whole database only if the database update causes the negative border of the set of large itemsets to expand.