# Using Deep Learning to Solve Computer Security Challenges: A Survey

arXiv: https://arxiv.org/abs/1912.05721 · HTML: https://mlsanity.com/paper/1912.05721/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Dec 2019.

## Built on by (most cited first, 2 of 2)

- [Semantic-aware Binary Code Representation with BERT](https://mlsanity.com/paper/2106.05478/) (2021)
- [Which Features are Learned by CodeBert: An Empirical Study of the BERT-based Source Code Representation Learning](https://mlsanity.com/paper/2301.08427/) (2023)

## Abstract (arXiv)

Although using machine learning techniques to solve computer security challenges is not a new idea, the rapidly emerging Deep Learning technology has recently triggered a substantial amount of interests in the computer security community. This paper seeks to provide a dedicated review of the very recent research works on using Deep Learning techniques to solve computer security challenges. In particular, the review covers eight computer security problems being solved by applications of Deep Learning: security-oriented program analysis, defending return-oriented programming (ROP) attacks, achieving control-flow integrity (CFI), defending network attacks, malware classification, system-event-based anomaly detection, memory forensics, and fuzzing for software security.