SPAM: Signal Processing to Analyze Malware

TL;DR

This paper introduces signal and image processing techniques for malware analysis, representing malware as signals or images to improve classification and retrieval, potentially broadening security analysis methods.

Contribution

It presents novel application of signal and image processing methods to malware analysis, demonstrating their effectiveness in classification and retrieval tasks.

Findings

Effective malware classification using image and signal features

Improved malware retrieval accuracy

Potential for broader application in computer security

Abstract

In this article, we explored orthogonal methods to analyze malware motivated by signal and image processing. Malware samples are represented as images or signals. Image and signal-based features are extracted to characterize malware. Our extensive experiments demonstrate the efficacy of our methods on malware classification and retrieval. We believe that our techniques will open the scope of signal-and image-based methods to broader fields in computer security.