Dynamic Scalable Model For Traffic Pattern Based Content Leakage Framework

Abstract

The expanding popularity of multimedia streaming applications and services as of late has prompted the issue of trusted video conveyance to keep the undesirable leakeage of substance over the network. The regular system addresses this issue by proposing techniques in light of perception of observation of streaming traffic through out the network to keep up a high detection exactness while adapting to not very many activity varieties like system postponements and packet loss. Nonetheless, with the varieties in the video length, the detection execution of ordinary system corrupts. To conquer this issue, we propose a novel detection system of content leakage that is powerful to the differed lengths of video. We think about the distinctive lengths of recordings and decide the connection that exists between the fluctuated lengths of recordings and the similitude between them. In this manner, we improve the detection execution of the proposed plot even in a situation subjected to variety long of video. Through a trial, the viability of our proposed plan is assessed as far as variety of video length, occrurrence of postponements, packet and data loss.