# Efficient Anomaly Detection in IoT Networks Using Logistic Regression and SMOTE

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/efficient-anomaly-detection-in-iot-networks-using-logistic-regression-and-smote/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Kanegonda Ravi Chythanya,Gaurav Tuteja,Sheifali Gupta,Panchal Sandeep Govindrao,Shubham Mahajan,Anmol Rattan Singh |
| Citations | 0 |
| DOI | 10.1109/incet64471.2025.11140296 |
| Fields | Computer Science |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4413979513 |
| Type | conference-paper |
| Year | 2025 |

## Paper authors

- [Kanegonda Ravi Chythanya](https://scholariq.org/researchers/kanegonda-ravi-chythanya/)

## 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/)
- [Anomaly Detection Techniques and Applications](https://scholariq.org/topics/anomaly-detection-techniques-and-applications/)

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