Detection of Phishing Website Using Machine Learning Approach

被引:0
|
作者
Vilas, Mahajan Mayuri [1 ,2 ]
Ghansham, Kakade Prachi [1 ,2 ]
Jaypralash, Sawant Purva [1 ,2 ]
Shila, Pawar [1 ,2 ]
机构
[1] Shri Chhatrapati Shivaji Maharaj Coll Engn, Dept Comp Engn, Ahmednagar, Maharashtra, India
[2] Savitribai Phule Pune Univ, Pune, Maharashtra, India
关键词
Phishing; Extreme Learning Machine; Features Classification; URL; Information Security;
D O I
10.1109/iceeccot46775.2019.9114695
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Phishing is one kind of cyber-attack and at once, it is a most dangerous and common attack to acquire personal information, account details, credit card details, organizational details or password of a user to conduct transactions. Phishing websites seem to like the appropriate ones and it is difficult to differentiate among those websites. The motive from that study is to perform ELM derived from different 30 main components which are categorized using the ML approach. Most of the phishing URLs use HTTPS to avoid getting detected. There are three ways for the detection of website phishing. The primitive approach evaluates different items of URL, the second approach analyzing the authority of a website and calculating whether the website is introduced or not and it also analyzing who is supervising it, the third approach checking the genuineness of the website.
引用
收藏
页码:384 / +
页数:6
相关论文
共 50 条
  • [1] Phishing Website Classification and Detection Using Machine Learning
    Kumar, Jitendra
    Santhanavijayan, A.
    Janet, B.
    Rajendran, Balaji
    Bindhumadhava, B. S.
    [J]. 2020 INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATION AND INFORMATICS (ICCCI - 2020), 2020, : 473 - 478
  • [2] Intelligent phishing website detection using machine learning
    Ashish Kumar Jha
    Raja Muthalagu
    Pranav M. Pawar
    [J]. Multimedia Tools and Applications, 2023, 82 : 29431 - 29456
  • [3] Intelligent phishing website detection using machine learning
    Jha, Ashish Kumar
    Muthalagu, Raja
    Pawar, Pranav M.
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 82 (19) : 29431 - 29456
  • [4] Machine learning approach for phishing website detection : A literature survey
    Patil, Rutuja R.
    Kaur, Gagandeep
    Jain, Himank
    Tiwari, Ayush
    Joshi, Soham
    Rao, Keshav
    Sharma, Amit
    [J]. JOURNAL OF DISCRETE MATHEMATICAL SCIENCES & CRYPTOGRAPHY, 2022, 25 (03): : 817 - 827
  • [5] Phishing website detection based on effective machine learning approach
    Harinahalli Lokesh, Gururaj
    BoreGowda, Goutham
    [J]. Journal of Cyber Security Technology, 2021, 5 (01) : 1 - 14
  • [6] Phishing Website Classification: A Machine Learning Approach
    Akanbi, Oluwatobi
    Abunadi, Ahmad
    Zainal, Anazida
    [J]. JOURNAL OF INFORMATION ASSURANCE AND SECURITY, 2014, 9 (04): : 222 - 234
  • [7] Phishing Website Classification: A Machine Learning Approach
    Akanbi, Oluwatobi
    Abunadi, Ahmad
    Zainal, Anazida
    [J]. JOURNAL OF INFORMATION ASSURANCE AND SECURITY, 2014, 9 (06): : 354 - 366
  • [8] Enhancing Phishing Website Detection Using Ensemble Machine Learning Models
    Baliyan, Himanshu
    Prasath, A. Rama
    [J]. 2024 OPJU International Technology Conference on Smart Computing for Innovation and Advancement in Industry 4.0, OTCON 2024, 2024,
  • [9] Detecting Phishing Website Using Machine Learning
    Alkawaz, Mohammed Hazim
    Steven, Stephanie Joanne
    Hajamydeen, Asif Iqbal
    [J]. 2020 16TH IEEE INTERNATIONAL COLLOQUIUM ON SIGNAL PROCESSING & ITS APPLICATIONS (CSPA 2020), 2020, : 111 - 114
  • [10] Phishing Website Detection Based on Machine Learning: A Survey
    Singh, Charu
    Meenu
    [J]. 2020 6TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING AND COMMUNICATION SYSTEMS (ICACCS), 2020, : 398 - 404