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IJSDR
INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15

Issue: March 2024

Volume 9 | Issue 3

Impact factor: 8.15

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Paper Title: SMART PHISHING WEBSITE DETECTION USING CNN ALGORITHM
Authors Name: Aishwarya Sanap , Deepali Gaikwad , Saburee Randhave , Namrta Salunke , Dr. J. V. Shinde
Unique Id: IJSDR2205087
Published In: Volume 7 Issue 5, May-2022
Abstract: There are numerous sites who request that client give delicate information, for example, username, secret key or Visa subtleties and so on regularly for malignant reasons. This kind of sites is known as phishing site. There are number of clients who buy items on the web and make installment through different sites. To identify and anticipate phishing site, we proposed a keen, adaptable and compelling framework that depends on utilizing grouping Data mining calculation. We executed order calculation and strategies to separate the phishing informational collections models to group their authenticity. The phishing site can be identified dependent on some significant attributes like URL and Domain Identity, and security and encryption standards in the last phishing discovery rate. When client makes exchange through internet based when he makes installment through the site our framework will utilize information mining calculation to recognize whether or not the site is phishing site. Information mining calculation utilized in this framework gives better execution when contrasted with other customary arrangements calculations. With the assistance of this framework client can recognize phishing without a second thought. Administrator can add phishing site url or phony site url into framework where framework could access and sweep the phishing site and by utilizing calculation, it will add new dubious watchwords to dataset. Framework utilizes Deep learning strategy to add new catch phrases into information base.
Keywords: Domain, Deep learning, Phishing, Authentication, Data Mining.
Cite Article: "SMART PHISHING WEBSITE DETECTION USING CNN ALGORITHM", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 5, page no.454 - 457, May-2022, Available :http://www.ijsdr.org/papers/IJSDR2205087.pdf
Downloads: 000336256
Publication Details: Published Paper ID: IJSDR2205087
Registration ID:200439
Published In: Volume 7 Issue 5, May-2022
DOI (Digital Object Identifier):
Page No: 454 - 457
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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