Sensitive and Obscene Content Blocker (SOCB)

Abstract

Abstract: In today’s digital age, the internet is a vast and diverse platform that offers a wealth of information and entertainment. However, this openness also exposes users to sensitive and obscene content, which can have a detrimental impact on individuals, particularly children and vulnerable populations. To mitigate the exposure to such content, a Sensitive and Obscene Content Blocker has been developed and tested. This paper explores the design, development, and evaluation of a comprehensive content filtering system that is aimed at identifying and blocking sensitive and obscene content across various online platforms. The system employs advanced algorithms, machine learning techniques, and real-time content analysis to ensure a reliable and robust filtering mechanism. The paper outlines the key components of the blocker, including content analysis methods, their detection and classification methods. The study presents the results of extensive testing, demonstrating the system’s efficiency in blocking inappropriate content while minimizing false positives. The Sensitive and Obscene Content Blocker serves as a powerful tool to protect individuals from harmful online content, promoting a safer and more secure digital environment. This paper provides valuable insights into the development and implementation of content blockers and their role in enhancing online safety and security.