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
Machine Learning based Authentication Scheme to secure the Phishing Attack
Authors Name:
Vidyashree
, Dr.Mohammed Abdul Waheed
Unique Id:
IJSDR2007080
Published In:
Volume 5 Issue 7, July-2020
Abstract:
One of the grave threats to smart phone users is a phishing attack. According to the latest lookout study, mobile phishing attack is rising annually by 85 per cent and will become a major threat to users of smart phones. Social engineering aims to get the password from the user by disguising himself as a trusted service provider. Many users of smart phones use the Internet infrastructure outside of the conventional firewall. Cloud-based documents are among the primary targets of mobile cloud computing for this phishing attack. Often, most Mobile users use their device's cloud storage. In order to prevent this password attack in a mobile cloud environment, we are proposing a new authentication scheme to provide novel security to the mobile cloud services. This scheme will verify the user and service provider using the Zero-knowledge proof-based authentication protocol, without password transmission. The scheme proposed will also include mutual authentication between the communications entities. The feasibility of the proposed scheme will be checked using Scyther, a protocol verification method. This project further proposes with machine learning technology for detection of phishing URLs by extracting and analyzing various features of legitimate and phishing URLs. Decision Tree algorithm, random forest algorithm and Support vector machine algorithms are used to detect phishing websites. The main theam of this paper is to detect phishing URLs as narrow down to best machine learning algorithm by comparing false positive and false negative rate and accuracy rate of each algorithm.
Keywords:
Scyther, Smart phone, Cloud, Novel Security
Cite Article:
"Machine Learning based Authentication Scheme to secure the Phishing Attack", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.5, Issue 7, page no.577 - 584, July-2020, Available :http://www.ijsdr.org/papers/IJSDR2007080.pdf
Downloads:
000337353
Publication Details:
Published Paper ID: IJSDR2007080
Registration ID:192145
Published In: Volume 5 Issue 7, July-2020
DOI (Digital Object Identifier):
Page No: 577 - 584
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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