Your final project report should be between 2000 to 3000 words and reflect the following guidelines:
Abstract: A very brief summary of the project aims, method(s) used, and results.
Introduction: A general descriiption of the project, its applications, and any background or related studies.
Methodology: Based on the literature, describe the data mining technique(s) applied in the selected cybersecurity domain and provide technical details for
the method(s). Include a block diagram (or flowchart) that outlines all implementation steps of the method(s). Discuss the performance measures used and
results obtained by these method(s).
Data/Data Set (if applicable): Describe the characteristics of the data/data set(s) in terms of features, log files, data files, etc. in this section. If any data
preparation on the data/data set including feature selection and dimensionality reduction have been done, you should describe them in this section. The
division of the data set to training, cross validation, and test sets should be provided as well. Include direct links or any references (if applicable) to the
data/data set used for the method development.
Discussion: Discuss and compare (in the case multiple algorithms/methods) the efficiency of the methods through summarizing the evaluation experiments
available in the literature.
References: List the references you have cited in the report (using IEEE referencing style).
Extra Credit: Up to 10 extra credit points may be added to your grade for presenting a real-world data mining challenge and submitting your Python code.
Notes
Organize your report for readability and integrity, and create appendices wherever appropriate.
The report should follow SBU’s standard format (less than 10% quoted, with citations) and should include following sections:
Title Page
Table of Contents
Abstract
Introduction
Methodology
Data/Data set