Detecting Phishing Attacks Using Natural Language Processing and Machine Learning

被引：43
|
作者：
Peng, Tianrui [1 ]
Harris, Ian G. [2 ]
Sawa, Yuki [2 ]
机构：
[1] Columbia Univ, New York, NY 10027 USA
[2] Univ Calif Irvine, Irvine, CA USA
来源：
2018 IEEE 12TH INTERNATIONAL CONFERENCE ON SEMANTIC COMPUTING (ICSC) | 2018年
关键词：
D O I：
10.1109/ICSC.2018.00056
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Phishing attacks are one of the most common and least defended security threats today. We present an approach which uses natural language processing techniques to analyze text and detect inappropriate statements which are indicative of phishing attacks. Our approach is novel compared to previous work because it focuses on the natural language text contained in the attack, performing semantic analysis of the text to detect malicious intent. To demonstrate the effectiveness of our approach, we have evaluated it using a large benchmark set of phishing emails.
引用
收藏
页码：300 / 301
页数：2
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