# Malware Detection and Analysis: Challenges and Research Opportunities

arXiv: https://arxiv.org/abs/2101.08429 · HTML: https://mlsanity.com/paper/2101.08429/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Jan 2021.

## Built on by (most cited first, 1 of 1)

- [On the impact of dataset size and class imbalance in evaluating machine-learning-based windows malware detection techniques](https://mlsanity.com/paper/2206.06256/) (2022)

## Abstract (arXiv)

Malwares are continuously growing in sophistication and numbers. Over the last decade, remarkable progress has been achieved in anti-malware mechanisms. However, several pressing issues (e.g., unknown malware samples detection) still need to be addressed adequately. This article first presents a concise overview of malware along with anti-malware and then summarizes various research challenges. This is a theoretical and perspective article that is hoped to complement earlier articles and works.