Detect Malware Types

Donated on 6/2/2019

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Dataset Characteristics

Multivariate, Time-Series, Text

Subject Area

Computer Science

Associated Tasks

Classification

Feature Type

-

# Instances

7107

# Features

280

Dataset Information

Additional Information

This study seeks to obtain data which will help to address machine learning based malware research gaps. The specific objective of this study is to build a benchmark dataset for Windows operating system API calls of various malware. This is the first study to undertake metamorphic malware to build sequential API calls. It is hoped that this research will contribute to a deeper understanding of how metamorphic malware change their behavior (i.e. API calls) by adding meaningless opcodes with their own dissembler/assembler parts. In our research, we have translated the families produced by each of the software into 8 main malware families: Trojan, Backdoor, Downloader, Worms, Spyware Adware, Dropper, Virus. Table 1 shows the number of malware belonging to malware families in our data set. As you can see in the table, the number of samples of other malware families except AdWare is quite close to each other. There is such a difference because we don't find too much of malware from the adware malware family.

Has Missing Values?

No

Variable Information

Various Windows API calls

Dataset Files

-

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