THIRD SEMESTERcoretheorySem 3
CYBER SECURITY
CSS 2205
Syllabus
- 01OWL Ontologies in Cybersecurity: Conceptual Modeling of Cyber-Knowledge: Introduction to Knowledge Engineering in Cybersecurity, Cybersecurity Taxonomies, Upper Ontologies for Cybersecurity, Formal Knowledge Representation for Cyber-Situational Awareness-Representing Network Knowledge Using Ontology Definition
- 02Representing Network Data Provenance, Vulnerability and Exploit Analysis- Likelihood of Exploitation, Time-Based Analysis, Vendor-/Platform-Based Analysis, Experimental Setup-Performance Evaluation
- 03Training the Binary Classifier for Detecting Network Attacks-Calculating and Preprocessing Network Parameters, Genetic Optimization of the Weights of the Binary Classifier, An Algorithm for Network Attack Detection
- 04Schemes for Combining the Binary Classifiers -Low-Level Schemes for Combining Detectors
- 05Machine Learning in Network Intrusion Detection
- 06Detecting Malware Using SVM - SVM: A Brief Overview, Feature Settings, Hyperparameter Tuning, Evaluation Metrics
References
- Russell, S. and Norvig P, Artificial Intelligence: A Modern Approach, (3e), Prentice-Hall, 2010.
- Clarence Chio, David Freeman, Machine Learning & Security: Protecting Systems with Data And Algorithms, (1e), Oreilly. 2018
- Elaine Rich, Kevin Knight, Shivasankar B. Nair, Artificial Intelligence, (3e), The McGraw Hill publications, 2009.
Credits Structure
3Lecture
0Tutorial
0Practical
3Total