Semantic Web Approach to Block Pornography Websites

Abstract

With the rapid growth of the internet a vast industry for the production and consumption of pornography has grown all over the globe. To keep people away from this kind of o ensive things, di erent kinds of Web ltering techniques are implemented. Today there are many Web lters available to solve this problem. They use di erent techniques to lter the Web. Blacklists & white-lists, keyword blocking, using rating systems and image based algorithms are the most popular ones among them. Keeping and updating a list is quite promising. Because there are thousands of new web pages are publishing in the inter- net. So checking all of them and listing is not an easy task. Sometimes using keyword blocking techniques, legitimate pages can be blocked too. The prob- lem of this is that rating is not compulsory. So it may not always available. Apart from that because of the self rating, ratings may not always accurate. Other than that the image scanning mechanisms may be very costly due to the huge processing time it needs for the classi cation. The main goal of the project is to develop an automated Web ltering mechanism, which extract the semantic web features of the web page for the classi cation process. The proposed system considers URL of a web page and the web page content to lter the page. Here new URL scanning & scoring mechanism as well as in-line page keyword scanning mechanism is introduces throughout the project. The web ltering engine is implemented as a extension for the Firefox browser. The project aims at minimizing over blocking rate while provide a fast and accurate ltering mechanism.