Phishing Recognition Software based on Machine Learning

Zheng  Gao; Gabriela Mogos

doi:10.1109/ICCIS63642.2024.10779406

Phishing Recognition Software based on Machine Learning

Zheng Gao, Gabriela Mogos^*

^*Corresponding author for this work

Department of Computing

School of Advanced Technology

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

Abstract

The main goal of our research is to enhance online security by accurately identifying potential phishing threats, thereby mitigating risks to users and organizations. To this end we developed and optimized a software tool to detect phishing websites in real time using advanced machine learning techniques. The software features a user-friendly interface that allows easy access to phishing detection functionality, making cybersecurity more accessible to all levels of users.

Original language	English
Title of host publication	2024 8th International Conference on Communication and Information Systems
Pages	134-139
Number of pages	5
DOIs	https://doi.org/10.1109/ICCIS63642.2024.10779406
Publication status	Published - 13 Dec 2024
Event	2024 8th International Conference on Communication and Information Systems - Shenzhen, China Duration: 18 Oct 2024 → 20 Oct 2024

Conference

Conference	2024 8th International Conference on Communication and Information Systems
Abbreviated title	ICCIS
Country/Territory	China
City	Shenzhen
Period	18/10/24 → 20/10/24

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10.1109/ICCIS63642.2024.10779406

Cite this

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title = "Phishing Recognition Software based on Machine Learning",

abstract = "The main goal of our research is to enhance online security by accurately identifying potential phishing threats, thereby mitigating risks to users and organizations. To this end we developed and optimized a software tool to detect phishing websites in real time using advanced machine learning techniques. The software features a user-friendly interface that allows easy access to phishing detection functionality, making cybersecurity more accessible to all levels of users.",

author = "Zheng Gao and Gabriela Mogos",

year = "2024",

month = dec,

day = "13",

doi = "10.1109/ICCIS63642.2024.10779406",

language = "English",

pages = "134--139",

booktitle = "2024 8th International Conference on Communication and Information Systems",

note = " 2024 8th International Conference on Communication and Information Systems , ICCIS ; Conference date: 18-10-2024 Through 20-10-2024",

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AU - Gao, Zheng

AU - Mogos, Gabriela

PY - 2024/12/13

Y1 - 2024/12/13

N2 - The main goal of our research is to enhance online security by accurately identifying potential phishing threats, thereby mitigating risks to users and organizations. To this end we developed and optimized a software tool to detect phishing websites in real time using advanced machine learning techniques. The software features a user-friendly interface that allows easy access to phishing detection functionality, making cybersecurity more accessible to all levels of users.

AB - The main goal of our research is to enhance online security by accurately identifying potential phishing threats, thereby mitigating risks to users and organizations. To this end we developed and optimized a software tool to detect phishing websites in real time using advanced machine learning techniques. The software features a user-friendly interface that allows easy access to phishing detection functionality, making cybersecurity more accessible to all levels of users.

U2 - 10.1109/ICCIS63642.2024.10779406

DO - 10.1109/ICCIS63642.2024.10779406

M3 - Conference Proceeding

SP - 134

EP - 139

BT - 2024 8th International Conference on Communication and Information Systems

T2 - 2024 8th International Conference on Communication and Information Systems

Y2 - 18 October 2024 through 20 October 2024

ER -

Phishing Recognition Software based on Machine Learning

Abstract

Conference

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Cite this