EdgeAIGuard: Agentic LLMs for Minor Protection in Digital Spaces

Social media has become integral to minors’ daily lives and is used for various purposes, such as making friends, exploring shared interests, and engaging in educational activities. However, the increase in screen time has also led to heightened challenges, including cyberbullying, online grooming, and exploitations posed by malicious actors. Traditional content moderation techniques have proven ineffective against exploiters’ evolving tactics. To address these growing challenges, we propose the EdgeAIGuard content moderation approach that is designed to protect minors from online grooming and various forms of digital exploitation. The proposed method comprises a multi-agent architecture deployed strategically at the network edge to enable rapid detection with low latency and prevent harmful content targeting minors. The experimental results show the proposed method is significantly more effective than the existing approaches.

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Institutions

Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-06-02
DOI
https://doi.org/10.1109/jiot.2025.3574961
Citations
5
Primary Topic
Digital Rights Management and Security
Type
article
Field-Weighted Citation Impact
16.23
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article

EdgeAIGuard: Agentic LLMs for Minor Protection in Digital Spaces

Sunder Ali Khowaja, Kapal Dev, Ghulam Mujtaba
5 citations
IEEE Internet of Things Journal
Digital Rights Management and Security
16.23
article

EdgeAIGuard: Agentic LLMs for Minor Protection in Digital Spaces

Sunder Ali Khowaja, Kapal Dev, Ghulam Mujtaba
article en
5 citations

Abstract

Social media has become integral to minors’ daily lives and is used for various purposes, such as making friends, exploring shared interests, and engaging in educational activities. However, the increase in screen time has also led to heightened challenges, including cyberbullying, online grooming, and exploitations posed by malicious actors. Traditional content moderation techniques have proven ineffective against exploiters’ evolving tactics. To address these growing challenges, we propose the EdgeAIGuard content moderation approach that is designed to protect minors from online grooming and various forms of digital exploitation. The proposed method comprises a multi-agent architecture deployed strategically at the network edge to enable rapid detection with low latency and prevent harmful content targeting minors. The experimental results show the proposed method is significantly more effective than the existing approaches.

IEEE Internet of Things JournalVol. 12(17)
Regis University (US), Irish Centre for High-End Computing (IE), Munster Technological University (IE), Dublin City University (IE)
Openalex Percentile: Top 1%
Digital Rights Management and Security
16.23
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