Phishing and Intrusion Attacks: An Overview of Classification Mechanisms

Saima Tareen, Sibghat Ullah Bazai, Shafi Ullah, Rehmat Ullah, Shah Marjan, Muhmmad Imran Ghafoor

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

The digital world is becoming increasingly interconnected and cyberattacks such as phishing are becoming more common. Fraudulent emails and bogus websites are used to obtain sensitive information from online users to obtain their personal information. Cyberattacks are becoming increasingly sophisticated, which makes detecting scam attacks more difficult. In order to detect phishing attacks accurately, a variety of approaches have been examined, including rules-based systems, lists-based systems, heuristic-based systems, and content-based systems, among others, with the most effective list-based systems and machine learning systems. Over the past couple of years, Deep Learning has proven to be one of the most effective algorithms for machine learning. Specifically, this paper explores and provides an overview of existing anti-phishing approaches, as well as how fraudulent URLs can be classified using machine learning and deep learning algorithms.

Original languageEnglish
Title of host publication3rd International Informatics and Software Engineering Conference, IISEC 2022
EditorsAsaf Varol, Murat Karabatak, Cihan Varol
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665459952
DOIs
Publication statusPublished - 29 Dec 2022
Externally publishedYes
Event3rd International Informatics and Software Engineering Conference, IISEC 2022 - Ankara, Turkey
Duration: 15 Dec 202216 Dec 2022

Publication series

Name3rd International Informatics and Software Engineering Conference, IISEC 2022

Conference

Conference3rd International Informatics and Software Engineering Conference, IISEC 2022
Country/TerritoryTurkey
CityAnkara
Period15/12/2216/12/22

Keywords

  • classification
  • Cyber security
  • cyberspace
  • Deep Learning
  • intrusion
  • machine learning
  • Phishing
  • Social Engineering

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