MASQUERADE DETECTION USING IMPROVED SEMI GLOBAL POSITIONING ALGORITHM

Abstract

A masquerade attack is an attack that uses a fake identity, such as a network identity to gain unauthorized access to personal computer information. The semi-global positioning algorithm (SGA) is one of the most dynamic ways to find these type of Sybil(fake user) attacks, but it has not stretch the target and executions as expected by multi user systems. However, the problem of false positive and false negative rate have not been reduced to as expected. To improve both the effectiveness and the performances of the SGA method, we are proposing Improved SGA, ISGA approach. ISGA improves the marking systems. ISGA even allows a little change in the user command. It as well makes suitable changes in the user behavior by upgrading the signature of the user according to the current behavior. After describing about ISGA, we represent the experimental results, the result shows that the ISGA gets the hit ratio of 90 percent and above with a low false positive rate. It increases the hit ratio by about 21.9 percent. Hence, ISGA results in increasing hit ratio.