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QR Code Security: Mitigating the Issue of Quishing (QR Code Phishing)

by Godwin Awuah Amoah, Hayfron-Acquah J.B.
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 184 - Number 33
Year of Publication: 2022
Authors: Godwin Awuah Amoah, Hayfron-Acquah J.B.
10.5120/ijca2022922425

Godwin Awuah Amoah, Hayfron-Acquah J.B. . QR Code Security: Mitigating the Issue of Quishing (QR Code Phishing). International Journal of Computer Applications. 184, 33 ( Oct 2022), 34-39. DOI=10.5120/ijca2022922425

@article{ 10.5120/ijca2022922425,
author = { Godwin Awuah Amoah, Hayfron-Acquah J.B. },
title = { QR Code Security: Mitigating the Issue of Quishing (QR Code Phishing) },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2022 },
volume = { 184 },
number = { 33 },
month = { Oct },
year = { 2022 },
issn = { 0975-8887 },
pages = { 34-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume184/number33/32528-2022922425/ },
doi = { 10.5120/ijca2022922425 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:23:03.956147+05:30
%A Godwin Awuah Amoah
%A Hayfron-Acquah J.B.
%T QR Code Security: Mitigating the Issue of Quishing (QR Code Phishing)
%J International Journal of Computer Applications
%@ 0975-8887
%V 184
%N 33
%P 34-39
%D 2022
%I Foundation of Computer Science (FCS), NY, USA
Abstract

To accommodate new technologies and communication methods, cybersecurity must advance. For security experts, especially those working in fields like digital forensics, new technologies provide both opportunities and challenges. New technologies like smartphones and new ways of disseminating information, like social media, might provide difficulties. Use of QR (Quick Response) codes is one of the rapidly expanding interface technologies. This paper explores privacy issues that might arise with QR codes and other information security-harming technologies. Additionally, it emphasizes the necessity for experts in the field to solve security concerns raised by the increasing use of QR codes. Each URL's words were extracted using a count vectorizer, and the URLs that were part of the QR code were used to obtain features. To distinguish between legitimate and phishing URLs, traits and words were tokenized, and naive Bayesian machine learning classification techniques were used in a recursive loop alongside logistic regression. A very accurate model was created, aiding in the reduction of quishing behaviour.

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Index Terms

Computer Science
Information Sciences

Keywords

Quick Response Code Naïve Bayes Natural Language Processing Logistic Regression Machine Learning Feature Extraction True Positive True Negative False Positive False Negative

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