Protection Against Phishing Attacks on Social Networks with Use of Selected Machine Learning - WISP 2023 Proceedings

Aug 5, 2026

Interactions have increasingly shifted to the internet, especially social media, where attackers exploit the scale of available data to conduct cyberattacks, with phishing being a key tactic. Phishing works by tricking users into clicking links, then extracting private information or delivering malware to victims’ devices. Because phishing techniques become harder to recognize each year, machine learning support is required. The paper reviews human and AI-based phishing recognition and introduces the AlexPhish algorithm for classifying phishing URLs, reporting 94.53% accuracy on the Web page phishing detection dataset.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages17

Reading Time43 min

AccessFree to download

Introduction

Phishing attacks on social media

Goals and typical attack flow

Related work and analysis

Human vs. AI phishing recognition

Proposed method

AlexPhish algorithm

Dataset and implementation on social platforms

Association for Information Systems AIS Electronic Library (AISeL) | WISP 2023 Proceedings | Pre-ICIS Workshop on Information Security and Privacy (SIGSEC) | | --- | --- | | Winter 12-10-2023
Protection Against Phishing Attacks on Social Networks with Use of Selected Machine Learning
Aneta Poniszewska-Marańda
Lodz University of Technology, [aneta.poniszewska-maranda@p.lodz.pl](aneta.poniszewska-maranda@p.lodz.pl)
Aleksander Lemiesz
Lodz University of Technology
Witold Marańda
Lodz University of Technology
Follow this and additional works at: [https://aisel.aisnet.org/wisp2023](https://aisel.aisnet.org/wisp2023) | | Recommended Citation Poniszewska-Marańda, Aneta; Lemiesz, Aleksander; and Marańda, Witold, "Protection Against Phishing Attacks on Social Networks with Use of Selected Machine Learning" (2023) . WISP 2023 Proceedings. 12. [https://aisel.aisnet.org/wisp2023/12](https://aisel.aisnet.org/wisp2023/12) This material is brought to you by the Pre-ICIS Workshop on Information Security and Privacy (SIGSEC) at AIS Electronic Library (AISeL) . It has been accepted for inclusion in WISP 2023 Proceedings by an authorized administrator of AIS Electronic Library (AISeL) . For more information, please [contact](contact elibrary@aisnet.org)[ elibrary@aisnet.org](contact elibrary@aisnet.org). Poniszewska-Marańda et al. Protection against phishing attacks on social networks Protection Against Phishing Attacks on Social Networks with Use of Selected Machine Learning Aneta Poniszewska-Marańda 1 Institute of Information Technology Lodz University of Technology, Poland Aleksander Lemiesz Institute of Information Technology Lodz University of Technology, Poland Witold Marańda Department of Microelectronics and Computer Science Lodz University of Technology, Poland ABSTRACT Nowadays, many interactions between people have moved to the Internet, mainly to social media. Due to the huge amount of data, hackers target social media by carrying out cyberattacks, especially phishing. It focuses on tricking the victim into clicking a link and then providing private information or installing malware on the victim's computer. Phishing attacks are becoming more and more difficult to recognize every year. Therefore, there is a need to support humans in this difficult task and machine learning can be used for this purpose. The paper analyzes the works on phishing recognition by humans and artificial intelligence. Then, the new AlexPhish algorithm for classifying phishing URLs was presented, along with a proposal for its implementation on social media platforms. It is trained on the “Web page phishing detection”dataset and achieves an accuracy of 94.53% . Keywords: Security, Social Media, Cyberattack, Phishing, Machine Learning. INTRODUCTION Nowadays, much of the interaction between people has moved to the Internet. In developed countries, approximately 80-90% of the population are Internet users, and this number is increasing every year. The Internet, and especially the part of it where people communicate with each other in the most accessible way, is social media. Initially, we could primarily post text [1](1 Corresponding author. aneta.poniszewska-maranda@p.lodz.pl)[ Corresponding author.](1 Corresponding author. aneta.poniszewska-maranda@p.lodz.pl)[ ](1 Corresponding author. aneta.poniszewska-maranda@p.lodz.pl)[aneta.poniszewska-maranda@p.lodz.pl](1 Corresponding author. aneta.poniszewska-maranda@p.lodz.pl) +48 426312796 Proceedings of the 18th Pre-ICIS Workshop on Information Security and Privacy, Hyderabad, India, December 10, 2023. 1 Poniszewska-Marańda et al. Protection against phishing attacks on social networks or photos on social networks. Nowadays, social media are also used to publish short videos and share and forward content published by others to other people, including links to videos, files such as documents for collaborative work, music. Attackers know many ways

FAQs

What problem does the paper address regarding social media security?

The paper addresses phishing threats on social networks, where attackers exploit users into clicking malicious links and disclosing private information or triggering malware.

How does phishing typically succeed in the described workflow?

A typical phishing attack uses a fake login page to capture credentials and may redirect victims to the real site to reduce suspicion, or deliver links that install malware in the background.

What is AlexPhish and how is it evaluated?

AlexPhish is presented as an algorithm for classifying phishing URLs. It is trained on the “Web page phishing detection” dataset and achieves 94.53% accuracy.

Aug 5, 2026

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