E-Ensemble: A Novel Ensemble Classifier for Encrypted Video Identification

Abstract

In recent years, video identification within encrypted network traffic has gained popularity for many reasons. For example, a government may want to track what content is being watched by its citizens, or businesses may want to block certain content for productivity. Many such reasons advocate for the need to track users on the internet. However, with the introduction of the secure socket layer (SSL) and transport layer security (TLS), it has become difficult to analyze traffic. In addition, dynamic adaptive streaming over HTTP (DASH), which creates abnormalities due to the variable-bitrate (VBR) encoding, makes it difficult for researchers to identify videos in internet traffic. The default quality settings in browsers automatically adjust the quality of streaming videos depending on the network load. These auto-quality settings also increase the challenge in video detection. This paper presents a novel ensemble classifier, E-Ensemble, which overcomes the abnormalities in video identification in encrypted network traffic. To achieve this, three different classifiers are combined by using two different combinations of classifiers: the hard-level and soft-level combinations. To verify the performance of the proposed classifier, the classifiers were trained on a video dataset collected over one month and tested on a separate video dataset captured over 20 days at a different date and time. The soft-level combination of classifiers showed more stable results in handling abnormalities in the dataset than those of the hard-level combination. Furthermore, the soft-level classifier combination technique outperformed the hard-level combination with a high accuracy of 81.81%, even in the auto-quality mode.

Adaptive Scalable Video Streaming (ASViS): An Advanced ABR Transmission Protocol for Optimal Video Quality

“…Dynamic Adaptive Streaming over HTTP (DASH) is an open standard for transmitting video that adapts to both the network and device. In this evolving landscape, the DASH protocol, operating over the Transmission Control Protocol (TCP), has been identified as the primary delivery model for video streaming services [7][8][9]. This open-source standard, celebrated for its flexibility and codec-agnostic features, has established itself as an indispensable tool for most streaming entities [10,11].…”

“…In response to such challenges, focus within the research community has shifted towards optimizing Adaptive Bitrate (ABR) algorithms. One strategy involves having the client store chunks sent from the server on the local disk [7][8][9]. This stored content starts to play before the entire content is downloaded.…”