Cover Image

Phishing Detection in the Gen-AI Era: Quantized LLMs vs Classical Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Thapa, Jikesh, Chahal, Gurrehmat, Gabreanu, Serban Voinea, Otoum, Yazan
Format:	Preprint
Published:	2025
Subjects:	Cryptography and Security Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Differential Privacy-Driven Framework for Enhancing Heart Disease Prediction
by: Otoum, Yazan, et al.
Published: (2025)

Blockchain Meets Adaptive Honeypots: A Trust-Aware Approach to Next-Gen IoT Security
by: Otoum, Yazan, et al.
Published: (2025)

LLM-Based Threat Detection and Prevention Framework for IoT Ecosystems
by: Otoum, Yazan, et al.
Published: (2025)

Hybrid LLM-Enhanced Intrusion Detection for Zero-Day Threats in IoT Networks
by: Al-Hammouri, Mohammad F., et al.
Published: (2025)

Autonomous AI-based Cybersecurity Framework for Critical Infrastructure: Real-Time Threat Mitigation
by: Paulraj, Jenifer, et al.
Published: (2025)

NoPhish: Efficient Chrome Extension for Phishing Detection Using Machine Learning Techniques
by: Thaqi, Leand, et al.
Published: (2024)

Evaluating Large Language Models for Phishing Detection, Self-Consistency, Faithfulness, and Explainability
by: Kuikel, Shova, et al.
Published: (2025)

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

Deep Reinforcement Learning for Phishing Detection with Transformer-Based Semantic Features
by: Faisal, Aseer Al
Published: (2025)

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

PhreshPhish: A Real-World, High-Quality, Large-Scale Phishing Website Dataset and Benchmark
by: Dalton, Thomas, et al.
Published: (2025)

Teach LLMs to Phish: Stealing Private Information from Language Models
by: Panda, Ashwinee, et al.
Published: (2024)

KnowPhish: Large Language Models Meet Multimodal Knowledge Graphs for Enhancing Reference-Based Phishing Detection
by: Li, Yuexin, et al.
Published: (2024)

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

Democratising Clinical AI through Dataset Condensation for Classical Clinical Models
by: Thakur, Anshul, et al.
Published: (2026)

GenBFA: An Evolutionary Optimization Approach to Bit-Flip Attacks on LLMs
by: Das, Sanjay, et al.
Published: (2024)

GenAI-FDIA: Physics-Informed Generative Models for False Data Injection Attacks
by: Razzaque, Mohammad A., et al.
Published: (2026)

An investigation into the performances of the Current state-of-the-art Naive Bayes, Non-Bayesian and Deep Learning Based Classifier for Phishing Detection: A Survey
by: Ige, Tosin, et al.
Published: (2024)

Every Character Counts: From Vulnerability to Defense in Phishing Detection
by: Chiper, Maria, et al.
Published: (2025)

Attack Atlas: A Practitioner's Perspective on Challenges and Pitfalls in Red Teaming GenAI
by: Rawat, Ambrish, et al.
Published: (2024)

Web Phishing Net (WPN): A scalable machine learning approach for real-time phishing campaign detection
by: Zia, Muhammad Fahad, et al.
Published: (2025)

Explainable AI for Comparative Analysis of Intrusion Detection Models
by: Corea, Pap M., et al.
Published: (2024)

A Cryptographic Perspective on Mitigation vs. Detection in Machine Learning
by: Gluch, Greg, et al.
Published: (2025)

Attacking LLMs and AI Agents: Advertisement Embedding Attacks Against Large Language Models
by: Guo, Qiming, et al.
Published: (2025)

Rounding-Guided Backdoor Injection in Deep Learning Model Quantization
by: Chen, Xiangxiang, et al.
Published: (2025)

Exploiting LLM Quantization
by: Egashira, Kazuki, et al.
Published: (2024)

Attention Tracker: Detecting Prompt Injection Attacks in LLMs
by: Hung, Kuo-Han, et al.
Published: (2024)

PACZero: PAC-Private Fine-Tuning of Language Models via Sign Quantization
by: Ertan, Murat Bilgehan, et al.
Published: (2026)

Strategic Dishonesty Can Undermine AI Safety Evaluations of Frontier LLMs
by: Panfilov, Alexander, et al.
Published: (2025)

Breaking Agent Backbones: Evaluating the Security of Backbone LLMs in AI Agents
by: Bazinska, Julia, et al.
Published: (2025)

LAMD: Context-driven Android Malware Detection and Classification with LLMs
by: Qian, Xingzhi, et al.
Published: (2025)

PureGen: Universal Data Purification for Train-Time Poison Defense via Generative Model Dynamics
by: Bhat, Sunay, et al.
Published: (2024)

Investigating the Impact of Quantization on Adversarial Robustness
by: Li, Qun, et al.
Published: (2024)

Quantized Delta Weight Is Safety Keeper
by: Liu, Yule, et al.
Published: (2024)

Accelerating IoV Intrusion Detection: Benchmarking GPU-Accelerated vs CPU-Based ML Libraries
by: Çolhak, Furkan, et al.
Published: (2025)

SME-TEAM: Leveraging Trust and Ethics for Secure and Responsible Use of AI and LLMs in SMEs
by: Sarker, Iqbal H., et al.
Published: (2025)

Detecting Malicious AI Agents Through Simulated Interactions
by: Pi, Yulu, et al.
Published: (2025)

FTA generation using GenAI with an Autonomy sensor Usecase
by: Shetiya, Sneha Sudhir, et al.
Published: (2024)

Mind the Gap: A Practical Attack on GGUF Quantization
by: Egashira, Kazuki, et al.
Published: (2025)

ADR: An Agentic Detection System for Enterprise Agentic AI Security
by: Li, Chenning, et al.
Published: (2026)