Devising Malware Characterstics using Transformers

TL;DR

This paper explores using Transformer models to automatically extract relevant malware behavior information from cybersecurity reports, aiming to streamline malware analysis.

Contribution

It introduces a novel approach applying Transformer-based techniques to malware behavior extraction from security reports, marking an initial step in this direction.

Findings

Transformer models can identify relevant malware behavior mentions

The approach improves efficiency in malware report analysis

First attempt to apply Transformers in malware behavior extraction

Abstract

With the increasing number of cybersecurity threats, it becomes more difficult for researchers to skim through the security reports for malware analysis. There is a need to be able to extract highly relevant sentences without having to read through the entire malware reports. In this paper, we are finding relevant malware behavior mentions from Advanced Persistent Threat Reports. This main contribution is an opening attempt to Transformer the approach for malware behavior analysis.