SPAM: Signal Processing to Analyze Malware
This work addresses malware analysis for computer security, offering a novel approach but appears incremental as it applies existing signal and image processing methods to a new domain.
The authors tackled malware analysis by representing malware samples as images or signals and extracting features for classification and retrieval, demonstrating efficacy in experiments.
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.