Metainformation Extraction from Encrypted Streaming Video Packet Traces
Paper in proceeding, 2022
In this study, we present a metainformation extraction pipeline and a Proof of Concept (PoC) implementation of a recognizer capable of classifying video titles, series titles as well as video genres from encrypted video streams. We show in a promising evaluation, using the Netflix and SVT Play catalogues as examples, that our PoC is capable of learning abstract data from the packet bursts visible in DASH encrypted streams (such as if a video fingerprint is rather a Drama or a Romance movie). This is, to the best of our knowledge, the first demonstration of successful extraction of video metainformation from coarse-grain encrypted network packet traces. While advocating updates in the DASH protocol in order to preserve viewers’ privacy, our results also pave the way to future computer forensics systems capable of successful content classification over encrypted channels.
encrypted video streams
privacy
dynamic adaptive streaming over http
network traffic analysis
netflix
Author
Romaric Duvignau
Chalmers, Computer Science and Engineering (Chalmers), Computer and Network Systems
International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2022
1-6
9781665470957 (ISBN)
2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)
Malé, Maldives,
Malé, Maldives,
PAN5G: 5G Passive Attacks
Chalmers, 2022-01-01 -- 2022-06-30.
Subject Categories (SSIF 2011)
Other Computer and Information Science
Media Engineering
Computer Systems
Areas of Advance
Information and Communication Technology
Subject Categories (SSIF 2025)
Security, Privacy and Cryptography
DOI
10.1109/ICECCME55909.2022.9988476