Machine Learning Aided Static Malware Analysis: A Survey and Tutorial

Malware analysis and detection techniques have been evolving during the last decade as a reflection to development of different malware techniques to evade network-based and host-based security protections. The fast growth in variety and number of malware species made it very difficult for forensics investigators to provide an on time response. Therefore, Machine Learning (ML) aided malware analysis became a necessity to automate different aspects of static and dynamic malware investigation. We believe that machine learning aided static analysis can be used as a methodological approach in technical Cyber Threats Intelligence (CTI) rather than resource-consuming dynamic malware analysis that has been thoroughly studied before. In this paper, we address this research gap by conducting an in-depth survey of different machine learning methods for classification of static characteristics of 32-bit malicious Portable Executable (PE32) Windows files and develop taxonomy for better understanding of these techniques. Afterwards, we offer a tutorial on how different machine learning techniques can be utilized in extraction and analysis of a variety of static characteristic of PE binaries and evaluate accuracy and practical generalization of these techniques. Finally, the results of experimental study of all the method using common data was given to demonstrate the accuracy and complexity. This paper may serve as a stepping stone for future researchers in cross-disciplinary field of machine learning aided malware forensics.Comment: 37 Page

Metronidazole induced encephalopathy: A rare side effect with a common drug

In hospitals, seizures and encephalopathy are one of the common complications observed in critically ill patients. Drug intoxication, metabolic derangements, and anatomical abnormalities can cause altered mental status. We encountered an uncommon case with a diagnostic dilemma due to persistent encephalopathy, where metronidazole toxicity was an etiological factor. A 45-year-old male, who was admitted with the diagnosis of ruptured amoebic liver abscess. During the course of his management, he developed seizures and altered sensorium. After excluding other etiologies for in-hospital de novo seizure, a suspicion of metronidazole toxicity was considered. MRI brain was done which suggested the same. Metronidazole induced encephalopathy (MIE) is an uncommon adverse effect of treatment with metronidazole. Diagnosis is made by identifying specific radiological findings. It characteristically affects the cerebellum and subcortical structures. While the clinical and neuroimaging changes are usually reversible, persistent encephalopathy with poor outcomes may occur as seen in our case