Cover Image

Phishing Email Detection Using Inputs From Artificial Intelligence

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Paul, Mithün, Bartlett, Genevieve, Mirkovic, Jelena, Freedman, Marjorie
Format:	Preprint
Published:	2024
Subjects:	Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Context-Aware Phishing Email Detection Using Machine Learning and NLP
by: Chakravorty, Amitabh, et al.
Published: (2026)

Phishing Email Detection Using Large Language Models
by: Hasan, Najmul, et al.
Published: (2025)

Phishing Codebook: A Structured Framework for the Characterization of Phishing Emails
by: Saka, Tarini, et al.
Published: (2024)

PhishSigma++: Malicious Email Detection with Typed Entity Relations
by: Shang, Shang, et al.
Published: (2026)

E-PhishGen: Unlocking Novel Research in Phishing Email Detection
by: Pajola, Luca, et al.
Published: (2025)

Characterizing the Networks Sending Enterprise Phishing Emails
by: Luo, Elisa, et al.
Published: (2024)

URL Inspection Tasks: Helping Users Detect Phishing Links in Emails
by: Lain, Daniele, et al.
Published: (2025)

CISAF: A Framework for Estimating the Security Posture of Academic and Research Cyberinfrastructure
by: Liang, Qishen, et al.
Published: (2025)

Trustworthiness Calibration Framework for Phishing Email Detection Using Large Language Models
by: Ganiuly, Daniyal, et al.
Published: (2025)

MultiPhishGuard: An Explainable and Adaptive Multi-Agent LLM System for Phishing Email Detection
by: Xue, Yinuo, et al.
Published: (2025)

The Impact of Emerging Phishing Threats: Assessing Quishing and LLM-generated Phishing Emails against Organizations
by: Weinz, Marie, et al.
Published: (2025)

ChatSpamDetector: Leveraging Large Language Models for Effective Phishing Email Detection
by: Koide, Takashi, et al.
Published: (2024)

Robust ML-based Detection of Conventional, LLM-Generated, and Adversarial Phishing Emails Using Advanced Text Preprocessing
by: Kulal, Deeksha Hareesha, et al.
Published: (2025)

EPhishCADE: A Privacy-Aware Multi-Dimensional Framework for Email Phishing Campaign Detection
by: Kang, Wei, et al.
Published: (2025)

LLM-Powered Intent-Based Categorization of Phishing Emails
by: Eilertsen, Even, et al.
Published: (2025)

Enhancing Phishing Email Identification with Large Language Models
by: Lee, Catherine
Published: (2025)

Eyes on the Phish(er): Towards Understanding Users' Email Processing Pattern and Mental Models in Phishing Detection
by: Zhuo, Sijie, et al.
Published: (2024)

PiMRef: Detecting and Explaining Ever-evolving Spear Phishing Emails with Knowledge Base Invariants
by: Liu, Ruofan, et al.
Published: (2025)

Data Flows in You: Benchmarking and Improving Static Data-flow Analysis on Binary Executables
by: Weideman, Nicolaas, et al.
Published: (2025)

SpearBot: Leveraging Large Language Models in a Generative-Critique Framework for Spear-Phishing Email Generation
by: Qi, Qinglin, et al.
Published: (2024)

The Phish, The Spam, and The Valid: Generating Feature-Rich Emails for Benchmarking LLMs
by: Toth, Rebeka, et al.
Published: (2025)

MeAJOR Corpus: A Multi-Source Dataset for Phishing Email Detection
by: Mendes, Paulo, et al.
Published: (2025)

Explainable Transformer-Based Email Phishing Classification with Adversarial Robustness
by: P, Sajad U
Published: (2025)

Automated Phishing Detection Using URLs and Webpages
by: Wang, Huilin, et al.
Published: (2024)

Detecting Phishing Sites Using ChatGPT
by: Koide, Takashi, et al.
Published: (2023)

AdaPhish: AI-Powered Adaptive Defense and Education Resource Against Deceptive Emails
by: Meguro, Rei, et al.
Published: (2025)

Paladin: Defending LLM-enabled Phishing Emails with a New Trigger-Tag Paradigm
by: Pang, Yan, et al.
Published: (2025)

EvoMail: Self-Evolving Cognitive Agents for Adaptive Spam and Phishing Email Defense
by: Huang, Wei, et al.
Published: (2025)

A Lightweight Defense Mechanism against Next Generation of Phishing Emails using Distilled Attention-Augmented BiLSTM
by: Eskandarian, Morteza, et al.
Published: (2026)

An Explainable Transformer-based Model for Phishing Email Detection: A Large Language Model Approach
by: Uddin, Mohammad Amaz, et al.
Published: (2024)

Why People Still Fall for Phishing Emails: An Empirical Investigation into How Users Make Email Response Decisions
by: Jayatilaka, Asangi, et al.
Published: (2024)

PhishAgent: A Robust Multimodal Agent for Phishing Webpage Detection
by: Cao, Tri, et al.
Published: (2024)

PhishIntel: Toward Practical Deployment of Reference-Based Phishing Detection
by: Li, Yuexin, et al.
Published: (2024)

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector
by: Kulkarni, Aditya, et al.
Published: (2025)

PhishSSL: Self-Supervised Contrastive Learning for Phishing Website Detection
by: Li, Wenhao, et al.
Published: (2025)

PhishDebate: An LLM-Based Multi-Agent Framework for Phishing Website Detection
by: Li, Wenhao, et al.
Published: (2025)

PhishGuard: A Multi-Layered Ensemble Model for Optimal Phishing Website Detection
by: Ovi, Md Sultanul Islam, et al.
Published: (2024)

Phish-Blitz: Advancing Phishing Detection with Comprehensive Webpage Resource Collection and Visual Integrity Preservation
by: Hriday, Duddu, et al.
Published: (2025)

MemoPhishAgent: Memory-Augmented Multi-Modal LLM Agent for Phishing URL Detection
by: Chen, Xuan, et al.
Published: (2026)

SolPhishHunter: Towards Detecting and Understanding Phishing on Solana
by: Li, Ziwei, et al.
Published: (2025)