# XAI-IoT: An Explainable AI Framework for Enhancing Anomaly Detection in IoT Systems

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/xai-iot-an-explainable-ai-framework-for-enhancing-anomaly-detection-in-iot/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Anna N. Gummadi,Jerry C. Napier,Mustafa Abdallah |
| Citations | 74 |
| DOI | 10.1109/access.2024.3402446 |
| Fields | Computer Science |
| Open Access | true |
| OA Status | gold |
| OA URL | https://ieeexplore.ieee.org/ielx7/6287639/6514899/10534036.pdf |
| OpenAlex ID | https://openalex.org/W4397026497 |
| Type | article |
| Year | 2024 |

## Paper authors

- [Anna N. Gummadi](https://scholariq.org/researchers/anna-n-gummadi/)
- [Mustafa Abdallah](https://scholariq.org/researchers/mustafa-abdallah/)

## Paper journal

- [IEEE Access](https://scholariq.org/journals/ieee-access/)

## Paper primary topic

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

## Paper topics

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