Modelling the effects of malware propagation on military operations by using bayesian network framework

Download
2019
Şengül, Zafer
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.

Suggestions

Detecting malicious behavior in binary programs using dynamic symbolic execution and API call sequences
Tatar, Fatih Tamer; Betin Can, Aysu; Department of Bioinformatics (2021-6)
Program analysis becomes an important part of malware detection as malware become stealthier and more complex. For example, modern malware may detect whether they are under analysis and they may use certain triggers such as time to avoid detection. However, current detection techniques turn out to be insufficient as they have limitations to detect new, obfuscated, and intelligent malware. In this thesis, we propose a behavior based malware detection methodology using API call sequence analysis. In our metho...
DETECTING MALICIOUS API CALL SEQUENCES IN BINARY PROGRAMS USING DYNAMIC SYMBOLIC EXECUTION
Tatar, Fatih Tamer; Betin Can, Aysu (2022-10-01)
As malicious software gets more stealthy and smarter, software analysis has become an essential part of malware detection. Modern malware does not immediately display its malicious behavior, especially if they are aware that it is being analyzed. For instance, malware can detect the runtime environment and use certain triggers, such as time, to avoid detection. Static analysis fails on obfuscated code whereas dynamic analysis struggles to find the right actions and conditions to trigger malicious act...
A faster intrusion detection method for high-speed computer networks
Tarım, Mehmet Cem; Schmidt, Şenan Ece; Department of Electrical and Electronics Engineering (2011)
The malicious intrusions to computer systems result in the loss of money, time and hidden information which require deployment of intrusion detection systems. Existing intrusion detection methods analyze packet payload to search for certain strings and to match them with a rule database which takes a long time in large size packets. Because of buffer limits, packets may be dropped or the system may stop working due to high CPU load. In this thesis, we investigate signature based intrusion detection with sig...
Malicious code detection: run trace analysis by LSTM
Şırlancı, Melih; Acartürk, Cengiz; Gürkan Balıkçıoğlu, Pınar; Department of Cybersecurity (2021-6)
Malicious software threats and their detection have been gaining importance as a subdomain of information security due to the expansion of ICT applications in daily settings. A major challenge in designing and developing anti-malware systems is the coverage of the detection, particularly the development of dynamic analysis methods that can detect polymorphic and metamorphic malware efficiently. In the present study, we propose a methodological framework for detecting malicious code by analyzing run trace ou...
Improving the security and flexibility of one-time passwords by signature chains
Bıçakçı, Kemal; Baykal, Nazife (TÜBİTAK, 2003)
While the classical attack of ``monitor the network and intercept the password'' can be avoided by advanced protocols like SSH, one-time passwords are still considered a viable alternative or a supplement for software authentica since they are the only ones that safeguard against attacks on insecure client machines. In this paper by using public-key techniques we present a method called signature chain alternative to Lamport's hash chain to improve security and flexibility of one-time passwords. Our proposi...
Citation Formats
Z. Şengül, “Modelling the effects of malware propagation on military operations by using bayesian network framework,” Thesis (M.S.) -- Graduate School of Informatics. Cyber Security., Middle East Technical University, 2019.