On the Design of Supervised Binary Classifiers for Malware Detection Using Portable Executable Files
| Autor: | Mayank Swarnkar, Sonali Patil, Lucky Singh, Dewang Solanki, Hrushikesh Shukla, Hiren Kumar Thakkar |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Computer science
business.industry 020206 networking & telecommunications 02 engineering and technology computer.file_format computer.software_genre Upload Software 0202 electrical engineering electronic engineering information engineering Operating system Malware 020201 artificial intelligence & image processing Executable Malware analysis business computer Portable Executable |
| Zdroj: | 2019 IEEE 9th International Conference on Advanced Computing (IACC). |
| Popis: | Executable files such as .exe, .bat, .msi etc. are used to install the software in Windows-based machines. However, downloading these files from untrusted sources may have a chance of having maliciousness. Moreover, these executables are intelligently modified by the anomalous user to bypass antivirus definitions. In this paper, we propose a method to detect malicious executables by analyzing Portable Executable (PE) files extracted from executable files. We trained a supervised binary classifier using features extracted from the PE files of normal and malicious executables. We experimented our method on a large publicly available dataset and reported more than 95% of classification accuracy. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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