The rapid mutation and obfuscation techniques employed by modern polymorphic botnets create a highly dynamic and non-stationary distribution of malware signatures, rendering traditional detection algorithms obsolete. This paper addresses the challenge of identifying such evasive threats by proposing a machine learning-...
Andrii Holovatiuk, Oleg Savenko· Automation, Control, and Inf...· 0 citations
Existing code analysis systems address individual aspects of software quality (complexity, duplication, style) but do not combine multi-level analysis, metric aggregation, and learning-based inference within a single formal framework, nor do they close the loop between refactoring outcomes and assessment. This paper pr...
Ihor Prokofiev, Oleg Savenko· Automation, Control, and Inf...· 0 citations
We propose a graph neural network approach to network traffic anomaly detection that focuses on four adversarial technique classes from the MITRE ATT&CK framework: command and control (T1071), data exfiltration (T1041/T1048), reconnaissance (T1046/T1018), and lateral movement (T1021). We propose representing network tr...
Oleksandr Martsenkov, Oleg Savenko· Automation, Control, and Inf...· 0 citations
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