Investigating the transaction Log file to detect malicious transactions

Abstract

many advantages have been provided to organizations and people by using Database applications. It provides many services and benefits to companies and people. Therefore, these organizations and users have begun using Database systems in all their works. On the other hand, they are worried about their works when they use wrong information to organize and process some jobs. The wrong and invalid information comes when someone changes or enters invalid information to a database. In this paper, a technique has been proposed to investigating the transaction Log file to detect malicious transactions. In addition, the technique uses Functional dependency between the attributes to detect the malicious transactions which are wrong information. The technique begins by studying the Log file and defining all the transactions and their attributes which are used in each transaction. In addition, frequent pattern growth technique from data mining field is used to find the malicious transactions. Frequent pattern growth technique is used to be more efficient to detect the malicious transactions.