Advanced DGA Detection Framework: Hybrid Transformer Architecture with TLD-Aware Multi-Task Learning

DGAterms - A vocabulary to describe information flows in the Data Governance Act (DGA)

Generation of malicious DoH traffic using Domain Generation Algorithms and DNS Tunneling tools. and classification of DoH traffic as DGA or DNS Tunneling

A Python implementation of the SUNBURST DGA Cipher for encoding and decoding messages. This tool demonstrates substitution cipher techniques and secure coding practices.

Domain generation algorithm based on stock prices

Um modelo de redes autoassociativas empilhadas para detectar faltas em transformadores de potência

Real-time AI ensemble (RF + SVM + BiLSTM) for DGA domain detection. Final Year Project.

A framework for evaluating Large Language Models in zero-shot detection of Algorithmically Generated Domains (AGDs) used by malware for Command and Control communication.

Fall21 Semester Research in Applying NLP methods to Malware Domain Generation Algorithms (DGA) to improve Command-and-Control Center identification.

An application designed to automate the calculation and visualization of Dissolved Gas Analysis (DGA) for power transformers.

Data-parallel pipeline for detecting DGA-based malware using linguistic feature extraction on multi-core CPUs. Achieves 5.75× speedup on 8 cores with 93.18% classification accuracy. Built with Python multiprocessing and Random Forest. [AMLCCZG516 — BITS Pilani]

Domain Generation Algorithms research papers, datasets and code

A daily updated list of newly registered domains from the past 14 and 30 days for blocking, monitoring and analysis.

RAMPAGE is a framework aimed at training and comparing machine learning models for the detection of Algorithmically Generated Domains.

A simple yet accurate machine learning model to detect the DGA (Domain Generational Algorithm).

Scripts associated with the manuscript "Kinetics of Phenol Escape from the Insulin R6 Hexamer"

Machine Learning based transformer fault detection using DGA data

This repository hosts specifications for data disclosure agreements as part PS-SDA project in NGI-ONTOCHAIN. The project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 957338.

Transformer Fault Type Prediction using DGA data.