Abstract
Video-streaming applications are very popular these days. Existing studies of video streaming have attempted to identify video titles of users using machine learning techniques to identify specific patterns of video packets transmitted over the network. However, these studies have limitations when applied to actual environments where the network is congested or there are multiple users in the same network. This paper proposes Video Title Identification using open Metadata (VTIM), which identifies video titles by analyzing storyboards and Media Presentation Description (MPD) of MPEG-DASH in connection with video packets transmitted over the network. Attack was carried out using VTIM on 13,291 videos selected from actual video-streaming environment of YouTube. Our experiments show that VTIM is able to identify video titles with 100% accuracy at nearly thirty times faster than existing methods based on machine learning techniques. The paper also proposes and evaluates a countermeasure against VTIM.
Highlights
According to a forecast by Cisco, video traffic has grown on average of 33% annually and is expected to account for 82% of the Internet traffic worldwide by 2022 [1]
This paper proposes Video Title Identification using open Metadata (VTIM), which exploits open metadata from the storyboard that summarizes video playback scenes located within the video webpage’s source codes [18] and the Media Presentation Description (MPD) of MPEG-DASH that provides the necessary information for video playback of the client
WORKS This paper proposed VTIM as a method to identify the video titles of multiple victims on a network using the open metadata of the storyboard and MPD of MPEG-DASH
Summary
According to a forecast by Cisco, video traffic has grown on average of 33% annually and is expected to account for 82% of the Internet traffic worldwide by 2022 [1]. A number of studies [9]–[13] have been conducted to identify video titles watched by clients and they use mainly machine learning methods to distinguish video traffic features that change over time. This paper proposes Video Title Identification using open Metadata (VTIM), which exploits open metadata from the storyboard that summarizes video playback scenes located within the video webpage’s source codes [18] and the Media Presentation Description (MPD) of MPEG-DASH that provides the necessary information for video playback of the client. VTIM can identify video titles using open metadata from storyboards and MPDs with respect to video traffic This is in contrast to using machine learning techniques based on network video traffic features.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
