Instructor's Objectives

This course introduces cybersecurity and cyber situational awareness concepts and discusses cyber intelligence in the context of big data. Cyber security analytics and probabilistic modeling for threat detection and response (mitigative action) will play a central role. Coursework involves using the R language and software environment for statistical computing and graphics. Fundamental concepts and principles of cybersecurity risk assessment, intrusion detection and prevention, critical infrastructure protection and beyond will be discussed in detail.

Office Hours

• Teaching Assistants: Tuesdays, 12:00-13:00
  
• Instructor: Fridays, 13:00-14:00
  
• Office hours may end after 15 minutes in case of no attendance.

Prerequisites

CMPT 225. Additional prerequisites to be determined by the instructor subject to approval by the undergraduate program chair.

Grading

The course has three tests (worth 30% of the total grade), three graded assignments (worth 20%) and a term project organized as group project with a project report and presentation in class (worth 50%). There will also be reading assignments and several tutorials. Class participation accounts for up to 5% of the total grade. This grading scheme will be finalized in the first class, also depending on external circumstances.

Upcoming Zoom Sessions

• Lecture or Tutorial
• Office Hour - TAs
• Office Hour - Instructor

• Term Project - Presentation Schedule

Sessions on 16 April 2021

• Group 13
• Group 18
• Group 10
• Group 4
• Group 11
• Group 12

Recorded Lectures/Tutorials

• Recorded Sessions

Reading Materials

• Lecture Notes
• Tutorial Notes
• Assignments
• Term Project
• Cybersecurity

Recommended Books

• An Introduction to Statistical Learning: with Applications in R,
 Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani, Springer, 2017,
 ISBN 978-1461471370
.

• Fundamentals of Machine Learning for Predictive Data Analytics, John D. Kelleher, Brian Mac Namee, and Aoife D'Arcy, The MIT Press, 2020, ISBN 978-0262044691.

• How to Measure Anything in Cybersecurity Risk, Douglas W. Hubbard, and Richard Seiersen, John Wiley & Sons, 2016, ISBN 978-1119085294.

Important Dates

The dates listed below are tentative and may, or may not, shift depending on how the course progresses.

• JAN 19: Reading Assignment 1 posted
• JAN 27: Project Groups Finalized
• JAN 28: First Group Assignment posted
• FEB 9 : Term Project - Introduction and Overview
• FEB 9 : Reading Assignment 2 posted
• FEB 12: Man-in-the-middle Attack (Presentation: T. Charalampous)
• FEB 16: Reading break
• FEB 19: Reading break
• FEB 23: Test 1
• MAR 5: Second Group Assignment posted
• MAR 17: Third Group Assignment posted
• MAR 24: Third Group Assignment due
• APR 6: Test 2
• April 9: Guest Lecture on "Importance of Incident Response and Use of Automation to Combat Ransomware," Hardeep Mehrotara, Manager, IT Security Coast Capital Savings and Cyber Officer Canadian Forces
• APR 12: Term Project Report due (Updated!)
• APR 13: Presentation Slides due (Updated!)
• APR 13: Last Lecture
• APR 14: Project Presentations (PM)
• APR 15: Project Presentations (PM)
• APR 16: Presentation Sessions (AM,PM)
• APR 16: Test 3 (Updated!)

R Tutorials

• JAN 22: R Tutorial 1
• JAN 29: R Tutorial 2
• MAR 5: R Tutorial 3
• MAR 16: R Tutorial 4
• MAR 23: R Tutorial 5
• APR 6: R Tutorial (Q&A style)

Academic Honesty Statement

Academic honesty plays a key role in our efforts to maintain a high standard of academic excellence and integrity. Students are advised that ALL acts of intellectual dishonesty will be handled in accordance with the SFU Academic Honesty and Student Conduct Policies (http://www.sfu.ca/policies/gazette/student.html).