STUDY ON PREDICTION OF MALICIOUS PROGRAM USING CLASSIFICATION BASED APPROCHES

Malicious programs pose a serious threat to computer security. Nowadays, malicious software attacks and threats against data and information security has become a complex process. The variety and range of those attacks and threats has resulted in providing numerous styles of relying ways in which against them however sadly current detection technologies of malware designers which use them to escape from anti-malware. However there is more needed to receive some better procedures which can guarantee the malware code recognition proficiently by testing strategy over an extensive arrangement of malicious executable. This paper explores the application of data mining methods to predict rootkits based on the attributes extracted from the information contained in the log files. In this paper, we proposed three algorithms name as Random Forest, Random Tree and Rep Tree using data mining techniques and the comparison of these algorithms.