NSF Award
#1723250: Course MaterialsProject Title: SaTC: EDU: Captivology-Stimuli-based Learning (CAPITAL) of Big Data Security (BigSec): Towards a Science/Engineering, Career-Oriented Training
NSF Award
#1723250: Course Materials
Project Title: SaTC:
EDU: Captivology-Stimuli-based Learning (CAPITAL) of Big Data Security (BigSec):
Towards a Science/Engineering, Career-Oriented Training
Course Name: ECE 693 Big Data Security:
Course content: In this course, we have covered the big data appliction, attacks and countermeasures in big data systems, and privacy preservation solutions. Labs/projects are assigned in class.
Course Syllabus: click here
Class Labs: (for solutions, the instructors may ontact the author:
Dr. Fei Hu , fei@eng.ua.edu )
Lab 1 - Identify user behavior
pattern via mobile phone data: This lab trains students how to use the big data
of mobile phone to authenticate the user or identify the behavior patterns.
Lab
1 Requirements (Note: Please decompress it in a directory
called C:/1 )
Lab
1 Help File (This tool acts like a "virtual TA". It explains the
whole lab well).
Lecture Video (in the first 10 minutes)
Lab 2 - Use Machine Learning
for User Behavior Identification: This lab further uses advanced machine learning
algorithms (Non-negative matrix factorization, Support Vector Machine, Neural
Networks) to analyze the big data and thus authenticate the user
Lab 3 - Implement "User
behavior signature detection via the belief propagation algorithm"
Lab requirements
and a sample report
Lab 4 -Implement "User behavior
signature detection via Hidden Markov Model (HMM)"
Lab
4 Requirements (decompress it)
Lab
4 Help File (This tool acts like a "virtual TA". It explains the
whole lab well).
Lab 5 - User privacy protection
(lecture slides included)
Lab 5
Requirements (decompress it)
There are 3 labs developed by the co-PI - Dr. Da Yan at UAB, please click this link.
Lecture Videos and Slides: (note: For flipped-classroom based teaching,
please ask students read slides/videos before coming to class).
Lecture
1. Introduction to Big Data
Video
(posted in YouTube) - Part 1
Lecture
2. Overview of Big Data Security
Lecture
3. Basics of Cryptography: Applied Cryptography (Symmetric): Concepts
Lecture
4. Basics of Cryptography: Applied Cryptography (Symmetric): Finite fields
Video
- Part 1 (skip the first 10 minutes)
Lecture
5. Basics of Cryptography: Applied Cryptography (Symmetric): AES
Lecture
6. Basics of Cryptography: Applied Cryptography (Asymmetric): Part 1
Lecture
7. Basics of Cryptography: Applied Cryptography (Asymmetric): Part 2
Lecture
8. Basics of Cryptography: Applied Cryptography (Asymmetric): Part 3
Lecture
9. Use big data analysis to achieve cloud security
Lecture
10. Big data machine learning for outlier detection
Lecture
11. The Science of Security & Privacy in Machine Learning
Lecture
12. When Machine Learning Meets Security
Lecture
13. Deep Learning Attacks
Lecture
14. Distillation as a defense to the deep learning attacks
Lecture
15. Overview of Big Data Privacy
Lecture
16. Big data privacy: PSI scheme
Lecture
17. Insider Attacks in Big Data Systems
Lecture
18. Driving anomaly detection