Classification of Unknown Web Sites Based on Yearly Changes of Distribution Information of Malicious IP Addresses

Recently, cyber attacks through Web sites such as Drive-by download attacks or phishing attacks are increasing rapidly. The attackers can illegally acquire personal information of users by these attacks and cause economical damages. We aim to detect malicious Web sites which cause economic damages. The analysis of the features of the network address part of the IP address revealed that the features of malicious IP address has time change. Therefore, reflecting the time changes of these features, we classified unknown malicious Web sites. As a result of the evaluation experiment, classification accuracy could be improved.