Skip to main content
Florida Tech Evans Library Logo

CYB 5675 - Data Mining for Cybersecurity

Week 1 Readings

Frank Eibe, MA Hall, and IH Witten. The WEKA workbench.
online appendix for "Data Mining: Practical machine learning tools
and techniques". Morgan Kaufmann, 2016.


Hansman, S., & Hunt, R. (2005) A taxonomy of network and computer attacks. Computers & Security, 24(1):31–43.



Data Mining Chapter 1

Week 2 Readings

Erhard Rahm and Hong Hai Do. Data cleaning: Problems and
current approaches. IEEE Data Eng. Bull., 23(4):3{13, 2000.



Data Mining Chapters 2 & 8

Network Security Chapter 1


Week 3 Readings

P. Mishra, V. Varadharajan, U. Tupakula, and E. S. Pilli. A detailed
investigation and analysis of using machine learning techniques for
intrusion detection. IEEE Communications Surveys Tutorials, pages
1-1, 2018.



Data Mining Chapters 4 & 6

Week 4 Reading


Data Mining Chapter 5 and Appendix B.5

Week 5 Readings

Bhuyan, M. H., Bhattacharyya, D. K., and Kalita, J. K. (2017). Network Traffic Anomaly Detection Techniques and Systems, pages 115–169. Springer International Publishing, Cham. 




Data Mining Chapter 7 and 9.1-9.3

Week 6 Readings

Roberto Perdisci, Davide Ariu, Prahlad Fogla, Giorgio Giacinto,
and Wenke Lee. McPAD:
A multiple classifier system for accurate
payload-based anomaly detection. Computer Networks, 53(6):864-
881, 2009.



Data Mining Chapter 12


Week 7 Readings

Cynthia Dwork. The promise of differential privacy. a tutorial on
algorithmic techniques. In 52nd Annual IEEE Symposium on Foun-
dations of Computer Science, October 2011.


R. Mendes and J. P. Vilela. Privacy-preserving data mining: Meth-
ods, metrics, and applications. IEEE Access, 5:10562{10582, 2017.



Week 8 Reading

Faheem Ullah and M. Ali Babar. Architectural tactics for big data
cybersecurity analytic systems: A review, 2018.




Data Mining Chapter 13.1-13.3