Feng Li
ABSTRACT
Video streaming traffic often dominates mobile wireless networks, forcing Internet Service Providers (ISPs) to deploy video shaping to identify and then manage traffic during congested periods Unfortunately, the increasing use of end-to-end encryption (e.g., TSL/SSL) makes it difficult to identify video flows even with deep packet inspection. As an alternative, this paper presents Silhouette -- a real-time, lightweight video classification method suitable for ISP middle-boxes. Silhouette uses only flow statistics (i.e., "shape") for video identification making it payload-agnostic, effective for identifying video flow even when encrypted. Preliminary results with pre-classified YouTube traffic shows the promise of the Silhouette approach, yielding high identification accuracy over a range of video content and encoding qualities.
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Index Terms
- Silhouette: Identifying YouTube Video Flows from Encrypted Traffic
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