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Updated: Dec 11, 2025

Detection of Phytophthora capsici in Irrigation Water using Loop-Mediated Isothermal Amplification
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Towards a Multi-Layered Phishing Detection.

Kieran Rendall1, Antonia Nisioti2, Alexios Mylonas1

  • 1Department of Computing and Informatics, Bournemouth University, Bournemouth BH12 5BB, UK.

Sensors (Basel, Switzerland)
|August 23, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a multi-layered framework to detect spear phishing attacks more effectively. The novel approach enhances detection accuracy and feasibility for real-world deployment, improving cybersecurity defenses.

Keywords:
multi-layerphishingsupervised machine learning

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Area of Science:

  • Cybersecurity
  • Machine Learning
  • Network Security

Background:

  • Phishing, particularly spear phishing, is a primary threat in cyber intrusions.
  • Existing data-driven, single-layer supervised machine learning methods are resource-intensive and vulnerable to feature tampering.
  • The need for more robust and feasible phishing detection systems is critical.

Purpose of the Study:

  • To investigate a multi-layered detection framework for identifying phishing domains.
  • To develop a system that classifies potential phishing domains multiple times using diverse feature sets.
  • To address the limitations of current single-layer approaches in terms of resource demands and vulnerability.

Main Methods:

  • Implementation of a two-layered detection system using supervised machine learning.
  • Utilizing a multi-stage classification process where subsequent layers are activated based on confidence scores from the initial layer.
  • Evaluation using a dataset of active phishing attacks.

Main Results:

  • The proposed multi-layered framework demonstrates performance comparable to state-of-the-art methods.
  • The system effectively identifies phishing attacks while potentially managing resource demands more efficiently.
  • The layered approach offers a robust alternative to single-layer models.

Conclusions:

  • A multi-layered detection framework is a viable and effective strategy for combating phishing attacks.
  • This approach enhances the feasibility of deploying advanced detection systems in production environments.
  • Further research can explore optimizing the number of layers and feature sets for diverse threat landscapes.