In general, The task is to write a Python script that creates a statistic / ML model that identifies windows computer names.
* A little bit background:
1. the scope is Secuirty windows event logs which generating by the OS as .evtx file. In the image attached ("[login to view URL]") you can see an example of the 4624 windows event log.
2. I already converted the .evtx file to .csv ("[login to view URL]" attached as well).
3. The fields of the windows event log are explained here: [login to view URL]
4. Computer name by Microsoft:
[login to view URL]
As you can see in the "[login to view URL]", this .csv file includes a lot of fields.
That is, The task is to identify windows computer names from all that fields.
In conclusion, the project is to:
1. Find \ generate a data-set for the training process.
2. Train a model (you can choose any method which you think is good for the task)
3. Measure the model with all the known functions (accuracy, precision, recall, etc.)
The required files that I need are:
1. the data-set which you train on the model (.csv file)
2. Python script which includes the pre-process, the model, and the measurements (.py / .pynb file)
3. A general conclusion of what are you doing (.pdf file)
Please write a clean code and include as many comments as you can so I will understand it.
Feel free to contact me in chat for questions.