mlsanityData to 14 Oct 2026

Novel Interpretable and Robust Web-based AI Platform for Phishing Email Detection

arXiv 2405.11619 ↗First posted 19 May 2024cs.LG cs.AIcited by 7

Not on the map. Why?

Abstract (arXiv)

Phishing emails continue to pose a significant threat, causing financial losses and security breaches. This study addresses limitations in existing research, such as reliance on proprietary datasets and lack of real-world application, by proposing a high-performance machine learning model for email classification. Utilizing a comprehensive and largest available public dataset, the model achieves a f1 score of 0.99 and is designed for deployment within relevant applications. Additionally, Explainable AI (XAI) is integrated to enhance user trust. This research offers a practical and highly accurate solution, contributing to the fight against phishing by empowering users with a real-time web-based application for phishing email detection.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 7 of its 46 references that are in the map. First posted on arXiv 19 May 2024.

Builds on

7 of 46 references.

References · 7

  1. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,361
  2. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,375
  3. 2018Graph Convolutional Networks for Text Classificationcited by 345
  4. 2020Evaluation of Federated Learning in Phishing Email Detectioncited by 6
  5. 2019Catching the Phish: Detecting Phishing Attacks using Recurrent Neural Networks (RNNs)cited by 4
  6. 2018Deep Learning: Computational Aspectscited by 3
  7. 2022Phishing Detection Leveraging Machine Learning and Deep Learning: A Reviewcited by 3

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 5; 2026: 1.

7 papers.

  1. 2025Fraud-R1 : A Multi-Round Benchmark for Assessing the Robustness of LLM Against Augmented Fraud and Phishing Inducementscited by 32
  2. 2024Private Synthetic Text Generation with Diffusion Modelscited by 10
  3. 2025E-PhishGen: Unlocking Novel Research in Phishing Email Detectioncited by 4
  4. 2025MeAJOR Corpus: A Multi-Source Dataset for Phishing Email Detectioncited by 1
  5. 2025Dual-Path Phishing Detection: Integrating Transformer-Based NLP with Structural URL Analysiscited by 1
  6. 2025A Robust and Explainable Transformer-Based Framework for Phishing Email Detectioncited by 0
  7. 2026PersonaTrace: Synthesizing Realistic Digital Footprints with LLM Agentscited by 0