Early Blocking and Bypassing for Accelerating Web Content Filtering

• Main Authors: Ming-Dao Liu, 劉明道
• Other Authors: Ying-Dar Lin
• Format: Others
• Language: en_US
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/13074375671188416253

碩士 === 國立交通大學 === 資訊科學系 === 91 === Real-time content analysis is an important technique in Web content filtering. However, it may also suffer lower accuracy and longer processing time. In this work, we present two algorithms named early blocking and early bypassing based on the Naïve Bayes method to accelerate the classification process. The former algorithm allows making the blocking decision as early as we have enough confidence that the Web document should belong to some forbidden category, while the latter helps to make the bypassing decision as soon as the document is considered as a normal one. Experiments performed on NetBSD 1.6 with Pentinum III 700 MHz CPU show our algorithms can improve the throughput over four times higher than the original Bayesian classifier, while the F1 measure shows that the accuracy remains fairly good: 92% in forbidden traffic and 96% in normal traffic.