Towards Developing a Tool to Detect Phishing URLs: A Machine Learning Approach

被引:14
|
作者
Basnet, Ram B. [1 ]
Doleck, Tenzin [2 ]
机构
[1] Colorado Mesa Univ, Grand Junction, CO 81501 USA
[2] McGill Univ, Montreal, PQ H3A 2T5, Canada
关键词
machine learning; phishing; tools; phishing URLs;
D O I
10.1109/CICT.2015.63
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Despite efforts to curb online fraud, there continues to be a significant proliferation of fraud in the online space. In the same vein, Phishing attacks are a significant and growing problem for users, and carrying out certain actions such as mouse hovering, clicking, etc., on malicious URLs may cause unwary users to unwittingly fall victim to identity theft and problems. In this paper, we propose a methodology that could be used towards developing an anti-phishingURL tool to thwart a phishing attack by either masking the potentially phishing URL or by alerting the user about the potential threat.
引用
收藏
页码:220 / 223
页数:4
相关论文
共 50 条
  • [1] Machine Learning Approach Based on Hybrid Features for Detection of Phishing URLs
    Ghimire, Awishkar
    Jha, Avinash Kumar
    Thapa, Surendrahikram
    Mishra, Sushruti
    Jha, Aryan Mani
    2021 11TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING, DATA SCIENCE & ENGINEERING (CONFLUENCE 2021), 2021, : 954 - 959
  • [2] A Novel Algorithm to Detect Phishing URLs
    Hawanna, Varsharani Ramdas
    Kulkarni, V. Y.
    Rane, R. A.
    2016 INTERNATIONAL CONFERENCE ON AUTOMATIC CONTROL AND DYNAMIC OPTIMIZATION TECHNIQUES (ICACDOT), 2016, : 548 - 552
  • [3] Machine Learning Algorithms Evaluation for Phishing URLs Classification
    Bouijij, Habiba
    Berqia, Amine
    2021 4TH INTERNATIONAL SYMPOSIUM ON ADVANCED ELECTRICAL AND COMMUNICATION TECHNOLOGIES (ISAECT), 2021,
  • [4] Identification of Phishing URLs Using Machine Learning Models
    Vivek, Meghashyam
    Premjith, Nithin
    Johnson, Aaron Antonio
    Maurya, Ashutosh Kumar
    Jingle, I. Diana Jeba
    FOURTH CONGRESS ON INTELLIGENT SYSTEMS, VOL 3, CIS 2023, 2024, 865 : 209 - 219
  • [5] Machine learning based phishing detection from URLs
    Sahingoz, Ozgur Koray
    Buber, Ebubekir
    Demir, Onder
    Diri, Banu
    EXPERT SYSTEMS WITH APPLICATIONS, 2019, 117 : 345 - 357
  • [6] A Novel Machine Learning Approach to Detect Phishing Websites
    Tyagi, Ishant
    Shad, Jatin
    Sharma, Shubham
    Gaur, Siddharth
    Kaur, Gagandeep
    2018 5TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND INTEGRATED NETWORKS (SPIN), 2018, : 425 - 430
  • [7] Detection of Phishing URLs Using Machine Learning Techniques
    James, Joby
    Sandhya, L.
    Thomas, Ciza
    2013 INTERNATIONAL CONFERENCE ON CONTROL COMMUNICATION AND COMPUTING (ICCC), 2013, : 304 - +
  • [8] Mining Web to Detect Phishing URLs
    Basnet, Ram B.
    Sung, Andrew H.
    2012 11TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS (ICMLA 2012), VOL 1, 2012, : 568 - 573
  • [9] Hybrid machine learning: A tool to detect phishing attacks in communication networks
    Abidoye A.P.
    Kabaso B.
    Intl. J. Adv. Comput. Sci. Appl., 2020, 6 (559-569): : 559 - 569
  • [10] Hybrid Machine Learning: A Tool to Detect Phishing Attacks in Communication Networks
    Abidoye, Ademola Philip
    Kabaso, Boniface
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2020, 11 (06) : 559 - 569