期刊名称：TELKOMNIKA (Telecommunication Computing Electronics and Control)
印刷版ISSN：2302-9293
出版年度：2015
卷号：13
期号：2
页码：373-380
DOI：10.12928/telkomnika.v13i2.1436
语种：English
出版社：Universitas Ahmad Dahlan
摘要：Nowadays, the most important risk and challenge in online system are online scam and phishing attacks. Phishing attacks have been always used to steal important information of users. In this kind of scam, attacker direct victim to fake pages using social engineering techniques, then, starts stealing users` important information such as passwords. In order to confronting these attacks, numerous techniques have been invented which have the ability to confront different kinds of these attacks. Our goal in this paper is to introducing new kind of phishing attacks which are not identifiable by techniques and methods which have been invented to confronting phishing attacks. Unlike other kinds of phishing attacks which target all kinds of users, researchers are the victims of these kinds of journal phishing attacks. Finally, we`ll introduce an approach based on classification algorithms to identify these kind of journal phishing attacks and then we`ll check our suggested approach in error rate.
其他摘要：Nowadays, the most important risk and challenge in online system are online scam and phishing attacks. Phishing attacks have been always used to steal important information of users. In this kind of scam, attacker direct victim to fake pages using social engineering techniques, then, starts stealing users` important information such as passwords. In order to confronting these attacks, numerous techniques have been invented which have the ability to confront different kinds of these attacks. Our goal in this paper is to introducing new kind of phishing attacks which are not identifiable by techniques and methods which have been invented to confronting phishing attacks. Unlike other kinds of phishing attacks which target all kinds of users, researchers are the victims of these kinds of journal phishing attacks. Finally, we`ll introduce an approach based on classification algorithms to identify these kind of journal phishing attacks and then we`ll check our suggested approach in error rate.
