Identification and Prevention of Masquerade Attack using DDSGA Algorithm

In the computer system masquerader is a outsider or a insider user who take the privileges or authentication to act as an legal user in system. Such user take identity of a legal user to performing some illegal or a fraud activity[3]. Till now various researches has been accomplish for detecting masqueraders. Semi-global alignment approach is one Best algorithm but it doesn’t reach to that much of accuracy and performance which is required by high scale industries. To overcome such a drawback we discover a new technique called as Data Driven Semi-Global Alignment Approach(DDSGA). In this algorithm we tries to improve security of system by adopting scoring parameter for a each user. DDSGA also minimize the alignment overhead. The process of Detection and updating is done in a parallel manner. experimental results that show that DDSGA achieves a high hit ratio of 88.4 percent with a low false positive rate of 1.7 percent.