SIT719 - Security and Privacy Issues in Analytics

Assignment Task

Overview

During the last weeks, you have learned how machine learning algorithms can be implemented using python. Scikit learn is an open-source python library that can help to implement supervised and unsupervised machine learning models. More information can be obtained from the website.

In this task, machine learning algorithms will be used for cyber attack classification. The purpose of the task is to help students to build knowledge and skills related to the usages of supervised machine learning for security analysis, hands-on implementation and understand the overall goal of an end-to-end-project delivery in the area of cybersecurity analytics. Do you know what is an end-to-end data science project? See the lifecycle of an end-to-end data science project. If you are doing a data science application for security analysis, your problem will be related to cybersecurity and your data analysis needs to follow the below steps. See the task description for the detailed instructions.

Task Description

Instructions:

Suppose, you are working in an organization as a security analyst. You need to conduct an end to end project on “cyber-attack classification in the network traffic database”. To complete the project you follow the steps in Figure 1. Here, all of the steps are already solved for you (by the teaching team and you don’t need to take any action) except step 6 and 7. You need to complete these sections (highlighted in blue) by yourself to submit this task.

Steps

1: Business Understanding (Problem Definitions)

2: Data Gathering (Identify the source of data)

3: Data Cleaning (Filtering anomalous data)

4: Data Exploration (Understanding the data)

5: Feature Engineering (Select Important Feature)

6: Predictive Modelling (Prediction of the classes)

7: Data Visualization

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