Spring 2020 - CMPT 318 D100

Special Topics in Computing Science (3)

Cyber Security Analytics

Class Number: 6731

Delivery Method: In Person

Overview

  • Course Times + Location:

    Jan 6 – Apr 9, 2020: Tue, 10:30–11:20 a.m.
    Burnaby

    Jan 6 – Apr 9, 2020: Thu, 9:30–11:20 a.m.
    Burnaby

  • Exam Times + Location:

    Apr 18, 2020
    Sat, 12:00–3:00 p.m.
    Burnaby

  • Prerequisites:

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

Description

CALENDAR DESCRIPTION:

Special topics in computing science at the 300 level. Topics that are of current interest or are not covered in regular curriculum will be offered from time to time depending on availability of faculty and student interest.

COURSE-LEVEL EDUCATIONAL GOALS:

This course introduces cybersecurity concepts and discusses cyber intelligence and threat analysis methods in the context of Big Data analytics. Cyber situational analysis and anomaly detection based on probabilistic modeling will play a central role. This includes using the R language and software environment for statistical computing. Fundamental concepts and principles of cybersecurity risk assessment, intrusion detection and prevention, critical infrastructure protection and beyond will be discussed in detail.

Topics

  • Probability theory
  • Discrete Markov process modeling
  • Time series analysis and forecasting
  • Intrusion detection and prevention
  • Anomaly detection methods
  • Cyber risk assessment and mitigation
  • Advanced persistent threats
  • Blockchain technology

Grading

NOTES:

The course has a midterm examination (worth 30% of the total grade), two tests (worth 20%), three graded assignments (worth 15%) and a term project organized as group project with a project report and presentation in class (worth 30%). There will also be two reading assignments and several tutorials. Class participation accounts for 5% of the total grade.

Materials

RECOMMENDED READING:

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

ISBN: 9781119085294

An Introduction to Statistical Learning: with Applications in R
Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani
Springer
2017
ISBN: 9781461471370

Registrar Notes:

SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating.  Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the University community.  Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS