AN EFFECTIVE STUDY ON DATABASE INTRUSION USING LOG MINING
International Journal of Advance Engineering and Research Development · 2016
In database system because of insider misuse there is dangerous excruciating security problem. But today's scenario, more focus is given to external attacks because it is more visible, so some present technology are Intrusion Detection System(IDS) mechanism with Role based Access Control (RBAC). In this methodology permission are associated with roles and then intruder who is holding a specific role and system, efficiently determine role intruder but problem with it is that for extending Role base access proper planning is crucial and also effective when roles are carefully design. Next Technique is IDS using data mining. In which algorithm is develop for finding dependencies among the important item in Relational Database System (RDBMS), any transaction which does not follow dependencies are indentified as malicious, it also identify modification of sensitive attribute efficiently but disadvantage is that the high sensitivity attributes are usually access less frequently. There may not be any rule for such attribute. So, to overcome this flaws this paper intrudes idea of Log mining using intruder detection using comparative analysis We model users access patterns by profiling to keep track of users' usage habits as their forensic features and determines whether a valid login user to system or not.