AI Powered Framework for Child Protection and Digital Safety | IJCT Volume 12 – Issue 6 | IJCT-V12I6P38
International Journal of Computer Techniques
ISSN 2394-2231
Author
Nihar S, Jnanashekar M, Arpitha GT, Sachidananda Gadadar, Rakshitha P
Abstract
In today’s digital age, children are increasingly exposed to online risks such as cyberbullying, inappropriate content, and privacy breaches. Traditional methods of monitoring are often reactive and insufficient to handle evolving online threats. This study proposes an AI-powered framework that proactively detects risks, monitors digital interactions, and provides real-time interventions. Leveraging machine learning, natural language processing, and behavioral analytics, the system identifies potential threats with high accuracy. It includes automated content moderation, predictive threat detection, real-time alerts, and personalized guidance for safe online engagement. Privacy and ethical considerations are embedded through secure data governance and human-in the-loop validation. The framework promotes digital literacy, empowering children to navigate the internet responsibly. It supports collaboration between parents, educators, and authorities for comprehensive child protection. Experimental evaluations demonstrate improved detection and timely interventions compared to traditional methods. Overall, this framework provides a scalable, adaptive, and ethical solution to ensure children’s safety in the digital world.
Keywords
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Conclusion
The development of this AI-powered framework for child protection and digital safety represents a significant step toward creating a safer and more responsible online environment for young users. With the growing digital footprint of children and the increasing prevalence of cyberbullying, online exploitation, inappropriate content exposure, and other digital threats, traditional protection mechanisms are no longer sufficient. The proposed system leverages artificial intelligence, content classification, user behavior monitoring, and automated reporting workflows to detect and mitigate harmful digital activities more efficiently and accurately. The results of this project demonstrate that AI-driven solutions can substantially improve digital safety by providing real-time insights, automated moderation, and proactive defense mechanisms. Additionally, the modular architecture ensures scalability, adaptability, and future readiness—allowing the framework to evolve with emerging cyber threats and technological trends. While the system shows promising performance, continuous refinement, ethical compliance, and user privacy protection remain critical considerations. With further advancements, integration with global safety policies, and AI enhancements, this framework has the potential to serve as a powerful tool for parents, educators, institutions, and governments in promoting a secure digital ecosystem for children.
References
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How to Cite This Paper
Nihar S, Jnanashekar M, Arpitha GT, Sachidananda Gadadar, Rakshitha P (2025). AI Powered Framework for Child Protection and Digital Safety. International Journal of Computer Techniques, 12(6). ISSN: 2394-2231.
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