# A machine learning approach to detection of JavaScript-based attacks using AST features and paragraph vectors

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/a-machine-learning-approach-to-detection-of-javascript-based-attacks-using-ast/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Samuel Ndichu,Sang‐Wook Kim,Seiichi Ozawa,Takeshi Misu,Kazuo Makishima |
| Citations | 77 |
| DOI | 10.1016/j.asoc.2019.105721 |
| Fields | Computer Science |
| Open Access | true |
| OA Status | hybrid |
| OA URL | https://www.sciencedirect.com/science/article/pii/S1568494619305022/pdf |
| OpenAlex ID | https://openalex.org/W2969612742 |
| Type | article |
| Year | 2019 |

## Paper authors

- [Seiichi Ozawa](https://scholariq.org/researchers/seiichi-ozawa/)

## Paper primary topic

- [Spam and Phishing Detection](https://scholariq.org/topics/spam-and-phishing-detection/)

## Paper topics

- [Spam and Phishing Detection](https://scholariq.org/topics/spam-and-phishing-detection/)
- [Advanced Malware Detection Techniques](https://scholariq.org/topics/advanced-malware-detection-techniques/)
- [Network Security and Intrusion Detection](https://scholariq.org/topics/network-security-and-intrusion-detection/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.