# A hybrid deep learning model for efficient intrusion detection in big data environment

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/a-hybrid-deep-learning-model-for-efficient-intrusion-detection-in-big-data/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Mohammad Mehedi Hassan,Abdu Gumaei,Ahmed Alsanad,Majed Alrubaian,Giancarlo Fortino |
| Citations | 404 |
| DOI | 10.1016/j.ins.2019.10.069 |
| Fields | Computer Science |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W2986055611 |
| Type | article |
| Year | 2019 |

## Paper authors

- [Abdu Gumaei](https://scholariq.org/researchers/abdu-gumaei/)

## Paper primary topic

- [Network Security and Intrusion Detection](https://scholariq.org/topics/network-security-and-intrusion-detection/)

## Paper topics

- [Network Security and Intrusion Detection](https://scholariq.org/topics/network-security-and-intrusion-detection/)
- [Internet Traffic Analysis and Secure E-voting](https://scholariq.org/topics/internet-traffic-analysis-and-secure-e-voting/)
- [Advanced Malware Detection Techniques](https://scholariq.org/topics/advanced-malware-detection-techniques/)

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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.