Malicious Domain

Malicious domain detection aims to identify internet domains used for cyberattacks, such as phishing, malware distribution, and data theft, addressing the limitations of simple blacklists. Current research heavily utilizes machine learning, employing diverse models including gradient boosting classifiers, graph neural networks, and BERT-based encoders to analyze domain names and URLs, extracting features like lexical patterns, network behavior, and semantic information. These advancements are crucial for improving cybersecurity defenses by enabling proactive identification and blocking of malicious domains, thereby mitigating the risks associated with online threats.

Papers

October 11, 2024

Refusal-Trained LLMs Are Easily Jailbroken As Browser Agents
Priyanshu Kumar, Elaine Lau, Saranya Vijayakumar, Tu Trinh, Scale Red Team, Elaine Chang, Vaughn Robinson, Sean Hendryx, Shuyan Zhou, Matt Fredrikson, Summer Yue, Zifan Wang
Large Language Model Red Teaming Web Agent Safe Agent Malicious Domain

September 13, 2024

DomURLs_BERT: Pre-trained BERT-based Model for Malicious Domains and URLs Detection and Classification
Abdelkader El Mahdaouy, Salima Lamsiyah, Meryem Janati Idrissi, Hamza Alami, Zakaria Yartaoui, Ismail Berrada
Classification Code Pre Trained BERT Code BERT Uniform Resource Locator Malicious Domain

June 12, 2024

Malicious URL Detection using optimized Hist Gradient Boosting Classifier based on grid search method
Mohammad Maftoun, Nima Shadkam, Seyedeh Somayeh Salehi Komamardakhi, Zulkefli Mansor, Javad Hassannataj Joloudari
Machine Learning Simple Classifier Grid Search Malicious Domain Url Detection Gradient Histogram

January 6, 2024

SecureReg: A Combined Framework for Proactively Exposing Malicious Domain Name Registrations
Furkan Çolhak, Mert İlhan Ecevit, Hasan Dağ, Reiner Creutzburg
Unified Framework Threat Detection Cyber Threat High Risk Domain Malicious Domain

August 22, 2023

Multi-Instance Adversarial Attack on GNN-Based Malicious Domain Detection
Mahmoud Nazzal, Issa Khalil, Abdallah Khreishah, NhatHai Phan, Yao Ma
Adversarial Example GNN Prediction Malicious Domain

May 16, 2023

A Review of Data-driven Approaches for Malicious Website Detection
Zeyuan Hu, Ziang Yuan
Data Driven Data Driven Approach Multiple Model Malicious Domain

October 15, 2022

Classification of Web Phishing Kits for early detection by platform providers
Andrea Venturi, Michele Colajanni, Marco Ramilli, Giorgio Valenziano Santangelo
Classification Code Early Detection Obfuscation Technique Anti Phishing Phishing Attack Malicious Domain Spear Phishing

October 8, 2022

Collaborative Domain Blocking: Using federated NLP To Detect Malicious Domains
Mohammad Ismail Daud
Network Programming NLP Field Multi Modal Outer Arithmetic Block Language Pattern Content Filtering Malicious Domain

September 13, 2022

Detection of Malicious Websites Using Machine Learning Techniques
Adebayo Oshingbesan, Courage Ekoh, Chukwuemeka Okobi, Aime Munezero, Kagame Richard
Machine Learning Machine Learning Model Data Detection Random Forest Malicious Domain

May 30, 2022

Detecting Unknown DGAs without Context Information
Arthur Drichel, Justus von Brandt, Ulrike Meyer
Contextual Information Multiclass Classification Malware Family Malicious Domain Domain Generation Algorithm

May 10, 2022

DNS based In-Browser Cryptojacking Detection
Rohit Kumar Sachan, Rachit Agarwal, Sandeep Kumar Shukla
Domain Name Signature Analysis Malicious Domain

November 11, 2021

Classification of URL bitstreams using Bag of Bytes
Keiichi Shima, Daisuke Miyamoto, Hiroshi Abe, Tomohiro Ishihara, Kazuya Okada, Yuji Sekiya, Hirochika Asai, Yusuke Doi
Machine Learning Classification Code Bag Prototype Sub Byte Post Compression Bitstream Malicious Domain