Phishsense-1B: A Technical Perspective on an AI-Powered Phishing Detection Model
Fuente:
arXiv
Guardado en:
| Autor principal: | Blake, SE |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
PhishNet: A Phishing Website Detection Tool using XGBoost
por: Kumar, Prashant, et al.
Publicado: (2024)
por: Kumar, Prashant, et al.
Publicado: (2024)
PhishGuard: A Convolutional Neural Network Based Model for Detecting Phishing URLs with Explainability Analysis
por: Islam, Md Robiul, et al.
Publicado: (2024)
por: Islam, Md Robiul, et al.
Publicado: (2024)
AntiPhishStack: LSTM-based Stacked Generalization Model for Optimized Phishing URL Detection
por: Aslam, Saba, et al.
Publicado: (2024)
por: Aslam, Saba, et al.
Publicado: (2024)
PhishVQC: Optimizing Phishing URL Detection with Correlation Based Feature Selection and Variational Quantum Classifier
por: Shahriyar, Md. Farhan, et al.
Publicado: (2025)
por: Shahriyar, Md. Farhan, et al.
Publicado: (2025)
Can Features for Phishing URL Detection Be Trusted Across Diverse Datasets? A Case Study with Explainable AI
por: Mia, Maraz, et al.
Publicado: (2024)
por: Mia, Maraz, et al.
Publicado: (2024)
Phishing Detection in the Gen-AI Era: Quantized LLMs vs Classical Models
por: Thapa, Jikesh, et al.
Publicado: (2025)
por: Thapa, Jikesh, et al.
Publicado: (2025)
Fishing for Phishers: Learning-Based Phishing Detection in Ethereum Transactions
por: Alghuried, Ahod, et al.
Publicado: (2025)
por: Alghuried, Ahod, et al.
Publicado: (2025)
The Performance of Sequential Deep Learning Models in Detecting Phishing Websites Using Contextual Features of URLs
por: Gopali, Saroj, et al.
Publicado: (2024)
por: Gopali, Saroj, et al.
Publicado: (2024)
Simple Perturbations Subvert Ethereum Phishing Transactions Detection: An Empirical Analysis
por: Alghureid, Ahod, et al.
Publicado: (2024)
por: Alghureid, Ahod, et al.
Publicado: (2024)
NoPhish: Efficient Chrome Extension for Phishing Detection Using Machine Learning Techniques
por: Thaqi, Leand, et al.
Publicado: (2024)
por: Thaqi, Leand, et al.
Publicado: (2024)
An Explainable Transformer-based Model for Phishing Email Detection: A Large Language Model Approach
por: Uddin, Mohammad Amaz, et al.
Publicado: (2024)
por: Uddin, Mohammad Amaz, et al.
Publicado: (2024)
A Lightweight Hybrid MLP-Based Framework for Real-Time Phishing URL Detection Using Structural URL Features
por: Emmanuel, Uche Unoke, et al.
Publicado: (2026)
por: Emmanuel, Uche Unoke, et al.
Publicado: (2026)
Evaluating Large Language Models for Phishing Detection, Self-Consistency, Faithfulness, and Explainability
por: Kuikel, Shova, et al.
Publicado: (2025)
por: Kuikel, Shova, et al.
Publicado: (2025)
SecureNet: A Comparative Study of DeBERTa and Large Language Models for Phishing Detection
por: Mahendru, Sakshi, et al.
Publicado: (2024)
por: Mahendru, Sakshi, et al.
Publicado: (2024)
PhishSnap: Image-Based Phishing Detection Using Perceptual Hashing
por: Minhaz, Md Abdul Ahad, et al.
Publicado: (2025)
por: Minhaz, Md Abdul Ahad, et al.
Publicado: (2025)
KnowPhish: Large Language Models Meet Multimodal Knowledge Graphs for Enhancing Reference-Based Phishing Detection
por: Li, Yuexin, et al.
Publicado: (2024)
por: Li, Yuexin, et al.
Publicado: (2024)
Deep Reinforcement Learning for Phishing Detection with Transformer-Based Semantic Features
por: Faisal, Aseer Al
Publicado: (2025)
por: Faisal, Aseer Al
Publicado: (2025)
PhreshPhish: A Real-World, High-Quality, Large-Scale Phishing Website Dataset and Benchmark
por: Dalton, Thomas, et al.
Publicado: (2025)
por: Dalton, Thomas, et al.
Publicado: (2025)
EvoMail: Self-Evolving Cognitive Agents for Adaptive Spam and Phishing Email Defense
por: Huang, Wei, et al.
Publicado: (2025)
por: Huang, Wei, et al.
Publicado: (2025)
Copyright Protection in Generative AI: A Technical Perspective
por: Ren, Jie, et al.
Publicado: (2024)
por: Ren, Jie, et al.
Publicado: (2024)
Adversarial Co-Evolution of Malware and Detection Models: A Bilevel Optimization Perspective
por: Jurečková, Olha, et al.
Publicado: (2026)
por: Jurečková, Olha, et al.
Publicado: (2026)
Llama-3.1-FoundationAI-SecurityLLM-Reasoning-8B Technical Report
por: Yang, Zhuoran, et al.
Publicado: (2026)
por: Yang, Zhuoran, et al.
Publicado: (2026)
Privacy-Preserving EHR Data Transformation via Geometric Operators: A Human-AI Co-Design Technical Report
por: Wang, Maolin, et al.
Publicado: (2026)
por: Wang, Maolin, et al.
Publicado: (2026)
Detection Latencies of Anomaly Detectors: An Overlooked Perspective ?
por: Puccetti, Tommaso, et al.
Publicado: (2024)
por: Puccetti, Tommaso, et al.
Publicado: (2024)
Every Character Counts: From Vulnerability to Defense in Phishing Detection
por: Chiper, Maria, et al.
Publicado: (2025)
por: Chiper, Maria, et al.
Publicado: (2025)
Prompted Contextual Vectors for Spear-Phishing Detection
por: Nahmias, Daniel, et al.
Publicado: (2024)
por: Nahmias, Daniel, et al.
Publicado: (2024)
Explainable Transformer-Based Email Phishing Classification with Adversarial Robustness
por: P, Sajad U
Publicado: (2025)
por: P, Sajad U
Publicado: (2025)
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
por: Ige, Tosin, et al.
Publicado: (2024)
por: Ige, Tosin, et al.
Publicado: (2024)
A Zero Trust Framework for Realization and Defense Against Generative AI Attacks in Power Grid
por: Munir, Md. Shirajum, et al.
Publicado: (2024)
por: Munir, Md. Shirajum, et al.
Publicado: (2024)
Quantum-Augmented AI/ML for O-RAN: Hierarchical Threat Detection with Synergistic Intelligence and Interpretability (Technical Report)
por: Le, Tan, et al.
Publicado: (2025)
por: Le, Tan, et al.
Publicado: (2025)
STRisk: A Socio-Technical Approach to Assess Hacking Breaches Risk
por: Hammouchi, Hicham, et al.
Publicado: (2024)
por: Hammouchi, Hicham, et al.
Publicado: (2024)
CSTS: A Canonical Security Telemetry Substrate for AI-Native Cyber Detection
por: Rahman, Abdul
Publicado: (2026)
por: Rahman, Abdul
Publicado: (2026)
Enhanced Anomaly Detection in IoMT Networks using Ensemble AI Models on the CICIoMT2024 Dataset
por: Chandekar, Prathamesh, et al.
Publicado: (2025)
por: Chandekar, Prathamesh, et al.
Publicado: (2025)
Cycle-Space Informed Detection of Autoencoded Blind False Data Injection Attacks on Power Systems
por: Li, Xin, et al.
Publicado: (2026)
por: Li, Xin, et al.
Publicado: (2026)
Cloud Security Leveraging AI: A Fusion-Based AISOC for Malware and Log Behaviour Detection
por: Okonkwo, Nnamdi Philip, et al.
Publicado: (2025)
por: Okonkwo, Nnamdi Philip, et al.
Publicado: (2025)
Web Phishing Net (WPN): A scalable machine learning approach for real-time phishing campaign detection
por: Zia, Muhammad Fahad, et al.
Publicado: (2025)
por: Zia, Muhammad Fahad, et al.
Publicado: (2025)
Integrating Explainable AI for Effective Malware Detection in Encrypted Network Traffic
por: Zeleke, Sileshi Nibret, et al.
Publicado: (2025)
por: Zeleke, Sileshi Nibret, et al.
Publicado: (2025)
Interpretable Anomaly-Based DDoS Detection in AI-RAN with XAI and LLMs
por: Chatzimiltis, Sotiris, et al.
Publicado: (2025)
por: Chatzimiltis, Sotiris, et al.
Publicado: (2025)
Teach LLMs to Phish: Stealing Private Information from Language Models
por: Panda, Ashwinee, et al.
Publicado: (2024)
por: Panda, Ashwinee, et al.
Publicado: (2024)
PhishGuard: A Multi-Layered Ensemble Model for Optimal Phishing Website Detection
por: Ovi, Md Sultanul Islam, et al.
Publicado: (2024)
por: Ovi, Md Sultanul Islam, et al.
Publicado: (2024)
Ejemplares similares
-
PhishNet: A Phishing Website Detection Tool using XGBoost
por: Kumar, Prashant, et al.
Publicado: (2024) -
PhishGuard: A Convolutional Neural Network Based Model for Detecting Phishing URLs with Explainability Analysis
por: Islam, Md Robiul, et al.
Publicado: (2024) -
AntiPhishStack: LSTM-based Stacked Generalization Model for Optimized Phishing URL Detection
por: Aslam, Saba, et al.
Publicado: (2024) -
PhishVQC: Optimizing Phishing URL Detection with Correlation Based Feature Selection and Variational Quantum Classifier
por: Shahriyar, Md. Farhan, et al.
Publicado: (2025) -
Can Features for Phishing URL Detection Be Trusted Across Diverse Datasets? A Case Study with Explainable AI
por: Mia, Maraz, et al.
Publicado: (2024)