Call for Papers:Vol.10 Issue.6

Submission
Last date		 30-Dec-2024
Acceptance Status In One Day
Paper Publish In Two Days
Submit ManuScript

News & Updates

Submit Article

Dear Authors, Article publish in our journal for Volume-10,Issue-6. For article submission on below link: Submit Manuscript


Join As Board

Dear Reviewer, You can join our Reviewer team without given any charges in our journal. Submit Details on below link: Join As Board


Paper Publication Charges

IJARIIE APP
Download Android App

For Authors

Archives

IJARIIE Board

Downloads

Android App

Download IJARIIE APP

Authors

Title: :  Lightweight URL Phishing Detection System Using SVM and Similarity
PaperId: :  16891
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 8 Issue 3 2022
DUI:    16.0415/IJARIIE-16891
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Khan Danish MusaShatabdi Institute College of Engineering
Shaikh Moaaz AhmedShatabdi Institute College of Engineering
Anwar Ismail KhanShatabdi Institute College of Engineering

Abstract

Computer Engineering
Data mining; feature selection; machine learning; optimization algorithms; phishing website; prediction; supervised algorithms.
As a criminal offense of employing technical method to thieve sensitive information of customers, phishing is presently an important risk facing the net, and losses because of phishing are developing regularly. function engineering is essential in phishing website detection answers; however, the accuracy of detection critically relies upon on earlier knowledge of features. furthermore, even though features extracted for one-of-a-kind dimensions are more comprehensive, a disadvantage is that extracting those functions calls for a massive amount of time. To address those barriers, we propose a multidimensional characteristic phishing detection method based on a quick detection approach by way of the usage of deep mastering (MFPD). within the first step, character sequence functions of the given URL are extracted and used for brief class by means of deep mastering, and this step does not require 1/3-party assistance or any prior know-how approximately phishing. inside the 2d step, we combine URL statistical functions, webpage code features, website text capabilities and the short classification end result of deep studying into multi-dimensional features. The technique can lessen the detection time for putting a threshold

Citations

Copy and paste a formatted citation or use one of the links to import into a bibliography manager and reference.

IJARIIE Khan Danish Musa, Shaikh Moaaz Ahmed, and Anwar Ismail Khan. "Lightweight URL Phishing Detection System Using SVM and Similarity" International Journal Of Advance Research And Innovative Ideas In Education Volume 8 Issue 3 2022 Page 1979-1987
MLA Khan Danish Musa, Shaikh Moaaz Ahmed, and Anwar Ismail Khan. "Lightweight URL Phishing Detection System Using SVM and Similarity." International Journal Of Advance Research And Innovative Ideas In Education 8.3(2022) : 1979-1987.
APA Khan Danish Musa, Shaikh Moaaz Ahmed, & Anwar Ismail Khan. (2022). Lightweight URL Phishing Detection System Using SVM and Similarity. International Journal Of Advance Research And Innovative Ideas In Education, 8(3), 1979-1987.
Chicago Khan Danish Musa, Shaikh Moaaz Ahmed, and Anwar Ismail Khan. "Lightweight URL Phishing Detection System Using SVM and Similarity." International Journal Of Advance Research And Innovative Ideas In Education 8, no. 3 (2022) : 1979-1987.
Oxford Khan Danish Musa, Shaikh Moaaz Ahmed, and Anwar Ismail Khan. 'Lightweight URL Phishing Detection System Using SVM and Similarity', International Journal Of Advance Research And Innovative Ideas In Education, vol. 8, no. 3, 2022, p. 1979-1987. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Lightweight_URL_Phishing_Detection_System_Using_SVM_and_Similarity_ijariie16891.pdf (Accessed : ).
Harvard Khan Danish Musa, Shaikh Moaaz Ahmed, and Anwar Ismail Khan. (2022) 'Lightweight URL Phishing Detection System Using SVM and Similarity', International Journal Of Advance Research And Innovative Ideas In Education, 8(3), pp. 1979-1987IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Lightweight_URL_Phishing_Detection_System_Using_SVM_and_Similarity_ijariie16891.pdf (Accessed : )
IEEE Khan Danish Musa, Shaikh Moaaz Ahmed, and Anwar Ismail Khan, "Lightweight URL Phishing Detection System Using SVM and Similarity," International Journal Of Advance Research And Innovative Ideas In Education, vol. 8, no. 3, pp. 1979-1987, May-Jun 2022. [Online]. Available: https://ijariie.com/AdminUploadPdf/Lightweight_URL_Phishing_Detection_System_Using_SVM_and_Similarity_ijariie16891.pdf [Accessed : ].
Turabian Khan Danish Musa, Shaikh Moaaz Ahmed, and Anwar Ismail Khan. "Lightweight URL Phishing Detection System Using SVM and Similarity." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 8 number 3 ().
Vancouver Khan Danish Musa, Shaikh Moaaz Ahmed, and Anwar Ismail Khan. Lightweight URL Phishing Detection System Using SVM and Similarity. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2022 [Cited : ]; 8(3) : 1979-1987. Available from: https://ijariie.com/AdminUploadPdf/Lightweight_URL_Phishing_Detection_System_Using_SVM_and_Similarity_ijariie16891.pdf
BibTex EndNote RefMan RefWorks

Number Of Downloads



Save in Google Drive

Similar-Paper

TitleArea of ResearchAuther NameAction
A Review on Ad Makers- Creation & Design Advertising CampaignsComputer EngineeringSwapnil Ohol1 Download
DETECTING FACIAL FORGERIES USING NOVEL FREQUENCY CONVOLUTIONAL NEURAL NETWORKComputer ScienceChikati Madhava Rao Download
Detecting Diabetes Early and Classifying Risk with Interpretable Deep Learning ModelsComputer ScienceMohmad Ahmed Ali Download
Enhance Accuracy of Medical Disease Prediction Using Machine Learning TechniquesMachine LearningSandeep Singh Sikarwar Download
Transformer-based Generative Adversarial Network (GAN) hybrid model for sentiment analysisInformation Technologyhridesh kumar Download
A Step Ahead in Operational Resilience - Integrating Observability with DevOpsComputer EngineeringAmit Sengupta Download
The Influence of Artificial Intelligence and Human-Computer Interaction on Enhancing Children's Learning ExperiencesComputer Engineering,Supriya S Kendhuli Download
Medicinal Plants Identification Using Deep LearningComputer Engineering Rohan Kumar Verma Download
“How to balance automation and ethics when rolling out AI automation in an Educational Framework”Computer SciecneSudhakar mishra Download
Microservices Fault Tolerance PatternsComputer EngineeringAmit Sengupta Download
Forecasting and Categorization of Cardiac Arrhythmia using Soft Computational ApproachesComputer Science and EngineeringDr. Sivaprakash. C Download
Enhancing CybersecurityComputer EngineeringG Tarun Download
Microservices Design PatternsComputer EngineeringAmit Sengupta Download
The Novel Approach to Detect Kidney Stones Using Deep Learning and Convolutional Neural NetworksCSEN Manjunatha Download
An investigation into the use of deep learning and image processing in the domain of diabetic medical careCSEHR Ravikumar Download
12