Mathematical modeling of cyber attacks: a learning module to enhance undergraduate security curricula

Authors:
A. Herath;S. Herath;R. Goonatilake;J. Herath;Richard Stockton
Affiliations:
State College of New Jersey, NJ;State College of New Jersey, NJ;Texas A&M International University, TX;St. Cloud State University, MN;State College of New Jersey, NJ
Venue:
Journal of Computing Sciences in Colleges
Year:
2007

Citing 6
Cited 4

Intrusion Detection Through Dynamic Software Measurement

Proceedings of the Workshop on Intrusion Detection and Network Monitoring
Inside the Slammer Worm

IEEE Security and Privacy
Worm Epidemics in High-Speed Networks

Computer
A behavioral approach to worm detection

Proceedings of the 2004 ACM workshop on Rapid malcode
Search worms

Proceedings of the 4th ACM workshop on Recurring malcode
Introduction to Probability Models, Ninth Edition

Introduction to Probability Models, Ninth Edition

Intrusion detection using the chi-square goodness-of-fit test for information assurance, network, forensics and software security

Journal of Computing Sciences in Colleges - Papers of the Fourteenth Annual CCSC Midwestern Conference and Papers of the Sixteenth Annual CCSC Rocky Mountain Conference
Designing computer forensics courses using case studies to enhance computer security curricula

Journal of Computing Sciences in Colleges - Papers of the Fourteenth Annual CCSC Midwestern Conference and Papers of the Sixteenth Annual CCSC Rocky Mountain Conference
An interdisciplinary accounting forensics course to improve computer science enrollments

Journal of Computing Sciences in Colleges
e-learning of security and information assurance with sequence diagrams

Proceedings of the 2012 Joint International Conference on Human-Centered Computer Environments

Quantified Score

Hi-index	0.00

Visualization

Abstract

We have been experimenting with methods for improving undergraduate curricula and research experiences as well as the security courses for Computer Science and Information Systems students. Recent surges in attacks and intrusions reflect vulnerabilities in computer networks and emerge of sophisticated new attacks are always associated with determining evolving risks and preventing them. Innovative methods and tools can help attack defenses, prevent attack propagations, detect and respond to such attacks. Mathematical or statistical modeling of attacks is an important concept to introduce to students in security courses as they help assess vulnerability under a variety of conditions that predetermine the extent of damages to a system and, thereby, predict possible losses. This paper describes a learning module developed to help students understand basic statistical and mathematical modeling of unscrupulous attacks.