M.S. Candidate: Zafer Şengül

Program: Cyber Security

Date: 07.08.2019 / 09:45

Place: A-212

Abstract: Malware are malicious programs that cause unwanted system behavior and usually result in damage to IT systems or its users. These effects can also be seen during military operations because high-tech military weapons, command, control and communication systems are also interconnected IT systems. This thesis employs conventional models that have been used for modeling the propagation of biological diseases to investigate the spread of malware in connected systems. In particular, it proposes a probabilistic learning approach, namely Bayesian Network analysis, for developing a framework for the investigation of mixed epidemic model and combat models to characterize the propagation of malware. Compared to the classical models, which have employed formula-based representations, the results of this thesis reveal more enriched representations of the superiority of one military force over the other in probabilistic terms.