Applying Machine Learning Techniques to Detect and Analyze Web Phishing Attacks

被引:4
作者
Cuzzocrea, Alfredo [1 ,2 ]
Martinelli, Fabio [3 ]
Mercaldo, Francesco [3 ]
机构
[1] Univ Trieste, Trieste, Italy
[2] ICAR CNR, Trieste, Italy
[3] IIT CNR, Pisa, Italy
来源
IIWAS2018: THE 20TH INTERNATIONAL CONFERENCE ON INFORMATION INTEGRATION AND WEB-BASED APPLICATIONS & SERVICES | 2014年
基金
欧盟地平线“2020”;
关键词
D O I
10.1145/3282373.3282422
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Phishing is a technique aimed to imitate an official websites of any company such as banks, institutes, etc. The purpose of phishing is to theft private and sensitive credentials of users such as password, username or PIN. Phishing detection is a technique to deal with this kind of malicious activity. In this paper we propose a method able to discriminate between web pages aimed to perform phishing attacks and legitimate ones. We exploit state of the art machine learning algorithms in order to build models using indicators that are able to detect phishing activities.
引用
收藏
页码:355 / 359
页数:5
相关论文
共 20 条
[1]   Phishing detection based Associative Classification data mining [J].
Abdelhamid, Neda ;
Ayesh, Aladdin ;
Thabtah, Fadi .
EXPERT SYSTEMS WITH APPLICATIONS, 2014, 41 (13) :5948-5959
[2]   Experimental Case Studies for Investigating E-Banking Phishing Techniques and Attack Strategies [J].
Aburrous, Maher ;
Hossain, M. A. ;
Dahal, Keshav ;
Thabtah, Fadi .
COGNITIVE COMPUTATION, 2010, 2 (03) :242-253
[3]  
[Anonymous], 2015, SIMPLE CART RANDOMTR
[4]  
Battista Pasquale, 2016, ICISSP 2016. 2nd International Conference on Information Systems Security and Privacy. Proceedings, P542
[5]   Metamorphic Malware Detection Using Code Metrics [J].
Canfora, Gerardo ;
Mercaldo, Francesco ;
Visaggio, Corrado Aaron ;
Di Notte, Paolo .
INFORMATION SECURITY JOURNAL, 2014, 23 (03) :57-67
[6]  
Cannataro M., 2002, WEBDYN WWW
[7]  
Cuzzocrea A., 2006, Web Intelligence and Agent Systems, V4, P289
[8]  
Fayyad U, 1996, AI MAG, V17, P37
[9]  
Jin C, 2009, ICCSSE 2009: PROCEEDINGS OF 2009 4TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE & EDUCATION, P127, DOI 10.1109/ICCSE.2009.5228509
[10]   Evaluating Convolutional Neural Network for Effective Mobile Malware Detection [J].
Martinelli, Fabio ;
Marulli, Fiammetta ;
Mercaldo, Francesco .
KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS, 2017, 112 :2372-2381