Adult content filtering using Machine Learning

Gala, Mahavir Mukesh (2024) Adult content filtering using Machine Learning. Masters thesis, Dublin, National College of Ireland.

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Abstract

This research addresses the problem of filtering adult content online, concentrating on the limits of traditional methods as well as looking into sophisticated artificial intelligence techniques. Traditional content filtering methods, including domain based and keyword-based blocking, are actually usually poor because of their static attributes and failure to adjust to brand-new content. This research study looks into the application of Convolutional Neural Networks (CNNs), particularly the VGG16 architecture, for real-time, correct classification of adult content. CNNs give considerable renovations in detecting subtle patterns as well as conforming to evolving content. Furthermore, the study highlights the importance of integrating vulnerability scanning to attend to security risks related to adult content websites. Through CNN-based filtering along with real-time vulnerability scanning, this work targets to improve online safety and deliver a comprehensive solution for shielding users from inappropriate content and security threats. The findings recommend promising instructions for future analysis as well as technological advancements in content moderation and cybersecurity.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Aleburu, Joel UNSPECIFIED
Uncontrolled Keywords:	Adult Content Detection; Convolutional Neural Networks (CNNs); VGG16; Image Classification; Machine Learning; Data Augmentation; Transfer Learning; Content Filtering; TensorFlow; Keras; Google Colab; Image Preprocessing; Model Evaluation; Feature Extraction; Content Moderation
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software > Computer Security T Technology > T Technology (General) > Information Technology > Computer software > Computer Security Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Cyber Security
Depositing User:	Ciara O'Brien
Date Deposited:	29 Jul 2025 16:04
Last Modified:	29 Jul 2025 16:04
URI:	https://norma.ncirl.ie/id/eprint/8311

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