|
|||||||||||||||
|
INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
||||||||||||||
Issue: May 2024
Volume 9 | Issue 5
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.76
Issue per Year : 12
Volume Published : 9
Issue Published : 96
Article Submitted :
Article Published :
Total Authors :
Total Reviewer :
Total Countries :
Indexing Partner
Join RMS/Earn 300
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | Phishing Website Detection Using Machine Learning |
| Authors Name: | Fouziya Farheen , Balineni Ram Deepak , Nirupam Kumar Sasapu , Sagar Chanchlani |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_189732
|
| Published Paper Id: | IJNRD2303403 |
| Published In: | Volume 8 Issue 3, March-2023 |
| DOI: | |
| Abstract: | The Internet's advancement has drawn attention to network security, as a secure network environment is fundamental for the Internet's fast and healthy growth. Cybercriminals employ phishing, a malicious act of deceiving users into clicking on phishing links, stealing their information, and using it to fake logins and steal funds. Network security is an iterative issue of attack and defense, and phishing and its detection technology continually evolve. Blacklists and whitelists are traditional methods for identifying phishing links but fail to identify new ones, which necessitates predicting whether a new link is a phishing website and improving the prediction's accuracy. Machine learning has emerged as a critical tool in predicting phishing websites, with this paper offering system learning technology for the detection of phishing URLs via extracting and studying diverse functions of valid and phishing URLs. KNN Classifier, Random Forest, and Support Vector Machine algorithms are used to locate phishing websites. The paper aims to detect phishing URLs as well as narrow them down to the fine algorithm that gets to know the set of rules with the aid of using evaluating the accuracy rate. |
| Keywords: | Phishing, Phishing website detection, Machine Learning, KNN, SVM, Random Forest |
| Cite Article: | "Phishing Website Detection Using Machine Learning", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 3, page no.e13-e20, March-2023, Available :http://www.ijnrd.org/papers/IJNRD2303403.pdf |
| Downloads: | 000118762 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID:IJNRD2303403 Registration ID: 189732 Published In: Volume 8 Issue 3, March-2023 DOI (Digital Object Identifier): Page No: e13-e20 Country: Visakhapatnam, Andhra Pradesh, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2303403 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2303403 |
| Share Article: |
|
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijnrd.org
| Semantic Scholar | Microsaoft Academic | ORCID | Zenodo |
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | PUBLON |
| DRJI | SSRN | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Social Media
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Join RMS/Earn 300
| Copyright © 2024 - All Rights Reserved - IJNRD |
Facebook Twitter Instagram LinkedIn