UFCFFY-15-M Cyber Security Analytics - University of the West of England Bristol

Assignment Task

The completion of Portfolio Task 2: Conduct an investigation on a URL database to develop a DGA classification system using machine learning techniques

Portfolio Task 2: Conduct an investigation on a URL database to develop a DGA classification system using machine learning techniques.

For this task, you will be provided with a URL dataset. You will need to develop a machine learning tool using

Python and scikit-learn that can identify URLs based on D omain Generator Algorithms (DGA) widely used by command and control malware to avoid static IP blocking. You are expected to show how a suitable set of features can be derived from the data for developing a machine learning classifier using Python data science libraries. You should also compare the results of 3 different classifiers for your task using the scikit-learn library, and provide a confusion matrix and an accuracy score for each classifier. Your portfolio submission for this task should be an HTML export of your IPYNB Jupyter notebook that details your investigation using appropriate code cells to perform the required analysis and Markdown cells to explain your work. You should include the following 3 classifiers in your study:

clf = LogisticRegression(random_state=42)
clf = RandomForestClassifier(max_depth=100, random_state=42) clf = MLPClassifier(random_state=42, max_iter=300)

Dataset: Please see the folder "Portfolio Assignment" under the Assignment tab on Blackboard for further detail related to the access and download of the necessary dataset.

Attachment:- Cyber Security Analytics.rar